id,description,dataset,category,subcategory,region,delay,universe,type,dateCoverage,coverage,userCount,alphaCount,pyramidMultiplier,themes,dataset_id,dataset_name,category_id,category_name,subcategory_id,subcategory_name
adjfactor,Adjustment factor applied to historical prices and dividends to account for splits and other corporate actions,"{'id': 'pv1', 'name': 'Price Volume Data for Equity'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,1.0,1.0,0,0,1.2,[],pv1,Price Volume Data for Equity,pv,Price Volume,pv-price-volume,Price Volume
adv20,Average daily volume in past 20 days,"{'id': 'pv1', 'name': 'Price Volume Data for Equity'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,1.0,1.0,807,5362,1.2,[],pv1,Price Volume Data for Equity,pv,Price Volume,pv-price-volume,Price Volume
cap,Daily market capitalization (in millions),"{'id': 'pv1', 'name': 'Price Volume Data for Equity'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,1.0,1.0,1343,13996,1.2,[],pv1,Price Volume Data for Equity,pv,Price Volume,pv-price-volume,Price Volume
close,Daily close price,"{'id': 'pv1', 'name': 'Price Volume Data for Equity'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,1.0,1.0,1979,35257,1.2,[],pv1,Price Volume Data for Equity,pv,Price Volume,pv-price-volume,Price Volume
dividend,Dividend,"{'id': 'pv1', 'name': 'Price Volume Data for Equity'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,1.0,1.0,282,3636,1.2,[],pv1,Price Volume Data for Equity,pv,Price Volume,pv-price-volume,Price Volume
high,Daily high price,"{'id': 'pv1', 'name': 'Price Volume Data for Equity'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,1.0,1.0,718,6168,1.2,[],pv1,Price Volume Data for Equity,pv,Price Volume,pv-price-volume,Price Volume
low,Daily low price,"{'id': 'pv1', 'name': 'Price Volume Data for Equity'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,1.0,1.0,559,5053,1.2,[],pv1,Price Volume Data for Equity,pv,Price Volume,pv-price-volume,Price Volume
open,Daily open price,"{'id': 'pv1', 'name': 'Price Volume Data for Equity'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,1.0,1.0,917,16295,1.2,[],pv1,Price Volume Data for Equity,pv,Price Volume,pv-price-volume,Price Volume
returns,Daily returns,"{'id': 'pv1', 'name': 'Price Volume Data for Equity'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,1.0,1.0,1929,33747,1.2,[],pv1,Price Volume Data for Equity,pv,Price Volume,pv-price-volume,Price Volume
sharesout,Daily outstanding shares (in millions),"{'id': 'pv1', 'name': 'Price Volume Data for Equity'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,1.0,1.0,372,3302,1.2,[],pv1,Price Volume Data for Equity,pv,Price Volume,pv-price-volume,Price Volume
split,Stock split ratio,"{'id': 'pv1', 'name': 'Price Volume Data for Equity'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,1.0,1.0,316,3390,1.2,[],pv1,Price Volume Data for Equity,pv,Price Volume,pv-price-volume,Price Volume
volume,Daily volume,"{'id': 'pv1', 'name': 'Price Volume Data for Equity'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,1.0,1.0,1217,8816,1.2,[],pv1,Price Volume Data for Equity,pv,Price Volume,pv-price-volume,Price Volume
vwap,Daily volume weighted average price,"{'id': 'pv1', 'name': 'Price Volume Data for Equity'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,1.0,1.0,715,5610,1.2,[],pv1,Price Volume Data for Equity,pv,Price Volume,pv-price-volume,Price Volume
session_1430to1430_final_trade_price,Last trade price recorded at the end of the 14:30 to 14:30 session.,"{'id': 'pv103', 'name': 'Interval and MOO&MOC statistics'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,339,1068,1.2,[],pv103,Interval and MOO&MOC statistics,pv,Price Volume,pv-price-volume,Price Volume
session_1430to1430_initial_trade_price,First trade price recorded at the start of the 14:30 to 14:30 session.,"{'id': 'pv103', 'name': 'Interval and MOO&MOC statistics'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,236,726,1.2,[],pv103,Interval and MOO&MOC statistics,pv,Price Volume,pv-price-volume,Price Volume
session_1430to1430_market_value,Aggregate market value of all trades during the 14:30 to 14:30 session.,"{'id': 'pv103', 'name': 'Interval and MOO&MOC statistics'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,243,926,1.2,[],pv103,Interval and MOO&MOC statistics,pv,Price Volume,pv-price-volume,Price Volume
session_1430to1430_max_trade_price,Highest trade price recorded during the 14:30 to 14:30 session.,"{'id': 'pv103', 'name': 'Interval and MOO&MOC statistics'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,213,781,1.2,[],pv103,Interval and MOO&MOC statistics,pv,Price Volume,pv-price-volume,Price Volume
session_1430to1430_min_trade_price,Lowest trade price recorded during the 14:30 to 14:30 session.,"{'id': 'pv103', 'name': 'Interval and MOO&MOC statistics'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,209,762,1.2,[],pv103,Interval and MOO&MOC statistics,pv,Price Volume,pv-price-volume,Price Volume
session_1430to1430_total_traded_volume,Total number of shares or contracts traded during the 14:30 to 14:30 session.,"{'id': 'pv103', 'name': 'Interval and MOO&MOC statistics'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,143,299,1.2,[],pv103,Interval and MOO&MOC statistics,pv,Price Volume,pv-price-volume,Price Volume
session_1430to1430_volume_weighted_avg_price,Volume-weighted average price for trades during the 14:30 to 14:30 session.,"{'id': 'pv103', 'name': 'Interval and MOO&MOC statistics'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,223,801,1.2,[],pv103,Interval and MOO&MOC statistics,pv,Price Volume,pv-price-volume,Price Volume
aggregated_slippage_metric,Comprehensive measure of slippage across multiple trades or venues.,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,93,181,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
asia_trade_cost_buy,Estimated cost incurred when buying in Asian markets.,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,30,37,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
asia_trade_cost_sell,Estimated cost incurred when selling in Asian markets.,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,15,16,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
asian_market_slippage,Slippage metric specific to Asian market trades.,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,7,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
average_spread_slippage,"Estimated portion of trade slippage attributable to crossing the bid-ask spread, i.e., the extra transaction cost versus mid-price execution when trading futures","{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,23,24,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
bid_ask_price_gap,Difference between the best bid and ask prices for a security.,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.989,49,62,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
group_buy_slippage,Slippage incurred when executing grouped buy orders.,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,16,25,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
group_order_slippage,Slippage experienced when executing grouped orders.,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,1.0,1.0,1,1,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
group_sell_slippage,Slippage incurred when executing grouped sell orders.,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,16,26,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
korean_market_slippage,"Korea-specific modeled trading slippage overlay that estimates expected execution cost for Korean equities, derived from microstructure and spread data and masked for eligibility","{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,59,105,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
price_difference_bid_ask,Unknown,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.989,49,64,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
pv106_wli_lastspread,Bid-ask spread averaged over the last 30 minutes,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.957,47,105,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
pv106_wli_lastspreadbp,Bid-ask spread over the last 30 minutes expressed in basis points,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.957,39,56,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
pv106_wli_spread,Difference between bid and ask price (raw bid-ask spread),"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9867,83,142,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
pv106_wli_spreadbp,Bid-ask spread expressed in basis points,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9867,63,111,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
slippage_at_spread_20,Slippage value calculated at a spread threshold of 20 units.,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,15,31,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
slippage_commission_2025,Estimated slippage and commission costs for the year 2025.,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,16,21,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
slippage_commission_estimate,Estimated slippage and commission costs for trades.,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,25,43,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
transaction_cost_estimate,Estimated cost incurred when executing a trade.,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,15,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
transaction_cost_maximum,Maximum estimated transaction cost for a trade.,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,31,42,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
transaction_cost_median,Median estimated transaction cost for a trade.,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,24,34,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
transaction_cost_percentile_10,Estimated transaction cost at the 10th percentile for a trade.,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,23,24,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
transaction_cost_percentile_25,Estimated transaction cost at the 25th percentile for a trade.,"{'id': 'pv106', 'name': 'Microstructure Spread Data'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,14,15,1.2,[],pv106,Microstructure Spread Data,pv,Price Volume,pv-price-volume,Price Volume
pv149_status_5,"Status code representing current state of data/record, e.g., valid, missing, suspended","{'id': 'pv149', 'name': 'Holidays and Trading Hours Calendar'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-relationship', 'name': 'Relationship'}",IND,1,TOP500,MATRIX,0.9507,1.0,94,224,1.2,[],pv149,Holidays and Trading Hours Calendar,pv,Price Volume,pv-relationship,Relationship
industry_grouping_level10_all_instruments_variant513,"Statistical cluster assignment for each stock and date, grouping all stocks in region 513 into 10 adaptive clusters based on co-movement of returns; value is cluster label (1 to 10), or -1/10000 for unclassified","{'id': 'pv29', 'name': 'Derived Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,152,274,1.2,[],pv29,Derived Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
industry_grouping_level10_india500_xjp513,"For each date and each of the top 500 Indian stocks (excluding Japan subset, version 513), this field assigns the stock to one of 10 statistically determined clusters based on historical stock return correlations, representing adaptive industry classification labels. Values from 1 to 10 indicate cluster membership; -1 or 10000 means unclassified","{'id': 'pv29', 'name': 'Derived Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9261,80,141,1.2,[],pv29,Derived Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
industry_grouping_level10_top800_xjp513,"Cluster membership assignment for each stock (per date) in the top 800 ex-Japan universe, based on statistical analysis of return co-movement, split into 10 groups","{'id': 'pv29', 'name': 'Derived Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.1674,9,9,1.2,[],pv29,Derived Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
industry_grouping_level20_all_instruments_variant513,"Statistical cluster assignment for each stock and date, grouping all stocks in region 513 into 20 adaptive clusters based on co-movement of returns; value is cluster label (1 to 20), or -1/10000 for unclassified","{'id': 'pv29', 'name': 'Derived Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,86,169,1.2,[],pv29,Derived Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
industry_grouping_level20_india500_xjp513,"For each date and each of the top 500 Indian stocks (excluding Japan subset, version 513), this field assigns the stock to one of 20 statistically determined clusters based on historical stock return correlations, representing fine-grained industry classification labels. Values from 1 to 20 indicate cluster membership; -1 or 10000 means unclassified","{'id': 'pv29', 'name': 'Derived Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9261,70,122,1.2,[],pv29,Derived Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
industry_grouping_level20_top800_xjp513,"Cluster membership assignment for each stock (per date) in the top 800 ex-Japan universe, based on statistical analysis of return co-movement, split into 20 groups","{'id': 'pv29', 'name': 'Derived Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.1674,9,10,1.2,[],pv29,Derived Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
industry_grouping_level2_all_instruments_variant513,"Statistical cluster assignment for each stock and date, grouping all stocks in region 513 into 2 adaptive clusters based on co-movement of returns; value is cluster label (1 or 2), or -1/10000 for unclassified","{'id': 'pv29', 'name': 'Derived Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,53,78,1.2,[],pv29,Derived Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
industry_grouping_level2_india500_xjp513,"For each date and each of the top 500 Indian stocks (excluding Japan subset, version 513), this field assigns the stock to one of 2 statistically determined clusters based on historical stock return correlations, representing broad statistical industry classification labels. Values from 1 to 2 indicate cluster membership; -1 or 10000 means unclassified","{'id': 'pv29', 'name': 'Derived Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9261,103,309,1.2,[],pv29,Derived Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
industry_grouping_level2_top800_xjp513,"Cluster membership assignment for each stock (per date) in the top 800 ex-Japan universe, based on statistical analysis of return co-movement, split into 2 groups","{'id': 'pv29', 'name': 'Derived Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.1674,0,0,1.2,[],pv29,Derived Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
industry_grouping_level50_all_instruments_variant513,"Statistical cluster assignment for each stock and date, grouping all stocks in region 513 into 50 adaptive clusters based on co-movement of returns; value is cluster label (1 to 50), or -1/10000 for unclassified","{'id': 'pv29', 'name': 'Derived Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,100,240,1.2,[],pv29,Derived Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
industry_grouping_level50_india500_xjp513,"For each date and each of the top 500 Indian stocks (excluding Japan subset, version 513), this field assigns the stock to one of 50 statistically determined clusters based on historical stock return correlations, representing very fine-grained industry classification labels. Values from 1 to 50 indicate cluster membership; -1 or 10000 means unclassified","{'id': 'pv29', 'name': 'Derived Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9261,58,89,1.2,[],pv29,Derived Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
industry_grouping_level50_top800_xjp513,"Cluster membership assignment for each stock (per date) in the top 800 ex-Japan universe, based on statistical analysis of return co-movement, split into 50 groups","{'id': 'pv29', 'name': 'Derived Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.1674,7,7,1.2,[],pv29,Derived Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
industry_grouping_level5_all_instruments_variant513,"Statistical cluster assignment for each stock and date, grouping all stocks in region 513 into 5 adaptive clusters based on co-movement of returns; value is cluster label (1 to 5), or -1/10000 for unclassified","{'id': 'pv29', 'name': 'Derived Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,60,113,1.2,[],pv29,Derived Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
industry_grouping_level5_india500_xjp513,"For each date and each of the top 500 Indian stocks (excluding Japan subset, version 513), this field assigns the stock to one of 5 statistically determined clusters based on historical stock return correlations, representing intermediate-level statistical industry classification labels. Values from 1 to 5 indicate cluster membership; -1 or 10000 means unclassified","{'id': 'pv29', 'name': 'Derived Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9261,64,99,1.2,[],pv29,Derived Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
industry_grouping_level5_top800_xjp513,"Cluster membership assignment for each stock (per date) in the top 800 ex-Japan universe, based on statistical analysis of return co-movement, split into 5 groups","{'id': 'pv29', 'name': 'Derived Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.1674,7,12,1.2,[],pv29,Derived Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method1_group10,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT1 method, assigning each stock to one of 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,35,52,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method1_group2,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT1 method, assigning each stock to one of 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,12,14,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method1_group20,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT1 method, assigning each stock to one of 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,12,20,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method1_group5,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT1 method, assigning each stock to one of 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,13,17,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method1_group50,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT1 method, assigning each stock to one of 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,8,20,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method2_group10,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT2 method, assigning each stock to one of 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,10,11,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method2_group2,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT2 method, assigning each stock to one of 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,8,8,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method2_group20,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT2 method, assigning each stock to one of 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,7,8,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method2_group5,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT2 method, assigning each stock to one of 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,9,10,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method2_group50,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT2 method, assigning each stock to one of 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method3_group10,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT3 method, assigning each stock to one of 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method3_group2,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT3 method, assigning each stock to one of 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method3_group20,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT3 method, assigning each stock to one of 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method3_group5,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT3 method, assigning each stock to one of 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,4,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method3_group50,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT3 method, assigning each stock to one of 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method4_group10,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT4 method, assigning each stock to one of 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method4_group2,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT4 method, assigning each stock to one of 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method4_group20,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT4 method, assigning each stock to one of 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,7,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method4_group5,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT4 method, assigning each stock to one of 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,8,11,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_minvol1m_pca_method4_group50,"Return-based robust industry cluster assignment (categorical integer label) for Asia equities in the EQY_ASI_Supported_MinVol1M universe, computed with FACT4 method, assigning each stock to one of 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method1_group10,Asia equity principal component grouping using method 1 with 10 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method1_group2,Asia equity principal component grouping using method 1 with 2 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method1_group20,Asia equity principal component grouping using method 1 with 20 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,4,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method1_group5,Asia equity principal component grouping using method 1 with 5 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method1_group50,Asia equity principal component grouping using method 1 with 50 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,7,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method2_group10,Asia equity principal component grouping using method 2 with 10 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method2_group2,Asia equity principal component grouping using method 2 with 2 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method2_group20,Asia equity principal component grouping using method 2 with 20 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method2_group5,Asia equity principal component grouping using method 2 with 5 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method2_group50,Asia equity principal component grouping using method 2 with 50 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method3_group10,Asia equity principal component grouping using method 3 with 10 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method3_group2,Asia equity principal component grouping using method 3 with 2 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method3_group20,Asia equity principal component grouping using method 3 with 20 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method3_group5,Asia equity principal component grouping using method 3 with 5 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,8,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method3_group50,Asia equity principal component grouping using method 3 with 50 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,8,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method4_group10,Asia equity principal component grouping using method 4 with 10 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method4_group2,Asia equity principal component grouping using method 4 with 2 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method4_group20,Asia equity principal component grouping using method 4 with 20 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method4_group5,Asia equity principal component grouping using method 4 with 5 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
asia_equity_pca_method4_group50,Asia equity principal component grouping using method 4 with 50 clusters.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method1_group10,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT1, using 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,10,11,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method1_group2,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT1, using 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,4,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method1_group20,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT1, using 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method1_group5,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT1, using 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method1_group50,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT1, using 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,4,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method2_group10,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT2, using 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method2_group2,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT2, using 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method2_group20,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT2, using 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method2_group5,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT2, using 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,4,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method2_group50,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT2, using 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method3_group10,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT3, using 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method3_group2,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT3, using 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method3_group20,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT3, using 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,4,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method3_group5,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT3, using 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method3_group50,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT3, using 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method4_group10,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT4, using 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,8,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method4_group2,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT4, using 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method4_group20,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT4, using 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method4_group5,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT4, using 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
ex_japan_equity_pca_method4_group50,"Categorical industry cluster label (robust, return-based) for Asia (ASI) in the EQY_XJPCI_Supported_MinVol10M universe, computed with method FACT4, using 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method1_group10,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT1, with 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method1_group2,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT1, with 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method1_group20,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT1, with 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method1_group5,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT1, with 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method1_group50,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT1, with 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method2_group10,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT2, with 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method2_group2,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT2, with 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method2_group20,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT2, with 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method2_group5,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT2, with 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method2_group50,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT2, with 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,4,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method3_group10,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT3, with 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method3_group2,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT3, with 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method3_group20,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT3, with 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method3_group5,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT3, with 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method3_group50,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT3, with 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method4_group10,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT4, with 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method4_group2,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT4, with 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method4_group20,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT4, with 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method4_group5,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT4, with 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
exjapan_minvol_method4_group50,"Robust industry cluster assignment (integer label) for ASI region, universe EQY_XJPCI_Supported_MinVol1M, method FACT4, with 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor1_group10_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 10 groups, computed using the FACT1 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,20,48,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor1_group20_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 20 groups, computed using the FACT1 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,15,21,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor1_group2_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 2 groups, computed using the FACT1 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,13,17,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor1_group50_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 50 groups, computed using the FACT1 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,8,8,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor1_group5_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 5 groups, computed using the FACT1 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,12,20,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor2_group10_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 10 groups, computed using the FACT2 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,16,17,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor2_group20_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 20 groups, computed using the FACT2 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,9,13,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor2_group2_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 2 groups, computed using the FACT2 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,12,13,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor2_group50_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 50 groups, computed using the FACT2 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,9,11,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor2_group5_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 5 groups, computed using the FACT2 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,7,9,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor3_group10_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 10 groups, computed using the FACT3 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,7,12,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor3_group20_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 20 groups, computed using the FACT3 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor3_group2_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 2 groups, computed using the FACT3 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor3_group50_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 50 groups, computed using the FACT3 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,11,13,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor3_group5_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 5 groups, computed using the FACT3 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor4_group10_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 10 groups, computed using the FACT4 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor4_group20_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 20 groups, computed using the FACT4 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,7,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor4_group2_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 2 groups, computed using the FACT4 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor4_group50_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 50 groups, computed using the FACT4 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor4_group5_top800_xjp_513,"Integer categorical label indicating the stock’s membership in a robust, return-based statistical industry cluster with 5 groups, computed using the FACT4 method for the TOP800 universe under the XJP_513 configuration","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method1_10clusters,Categorical label assigning the stock to one of 10 return-based statistical industry clusters for the TOP150 universe using the FACT1 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method1_20clusters,Categorical label assigning the stock to one of 20 return-based statistical industry clusters for the TOP150 universe using the FACT1 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method1_2clusters,Categorical label assigning the stock to one of 2 return-based statistical industry clusters for the TOP150 universe using the FACT1 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method1_50clusters,Categorical label assigning the stock to one of 50 return-based statistical industry clusters for the TOP150 universe using the FACT1 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method1_5clusters,Categorical label assigning the stock to one of 5 return-based statistical industry clusters for the TOP150 universe using the FACT1 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method2_10clusters,Categorical label assigning the stock to one of 10 return-based statistical industry clusters for the TOP150 universe using the FACT2 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method2_20clusters,Categorical label assigning the stock to one of 20 return-based statistical industry clusters for the TOP150 universe using the FACT2 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method2_2clusters,Categorical label assigning the stock to one of 2 return-based statistical industry clusters for the TOP150 universe using the FACT2 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method2_50clusters,Categorical label assigning the stock to one of 50 return-based statistical industry clusters for the TOP150 universe using the FACT2 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method2_5clusters,Categorical label assigning the stock to one of 5 return-based statistical industry clusters for the TOP150 universe using the FACT2 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method3_10clusters,Categorical label assigning the stock to one of 10 return-based statistical industry clusters for the TOP150 universe using the FACT3 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method3_20clusters,Categorical label assigning the stock to one of 20 return-based statistical industry clusters for the TOP150 universe using the FACT3 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method3_2clusters,Categorical label assigning the stock to one of 2 return-based statistical industry clusters for the TOP150 universe using the FACT3 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method3_50clusters,Categorical label assigning the stock to one of 50 return-based statistical industry clusters for the TOP150 universe using the FACT3 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method3_5clusters,Categorical label assigning the stock to one of 5 return-based statistical industry clusters for the TOP150 universe using the FACT3 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method4_10clusters,Categorical label assigning the stock to one of 10 return-based statistical industry clusters for the TOP150 universe using the FACT4 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method4_20clusters,Categorical label assigning the stock to one of 20 return-based statistical industry clusters for the TOP150 universe using the FACT4 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method4_2clusters,Categorical label assigning the stock to one of 2 return-based statistical industry clusters for the TOP150 universe using the FACT4 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method4_50clusters,Categorical label assigning the stock to one of 50 return-based statistical industry clusters for the TOP150 universe using the FACT4 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
factor_based_industry_method4_5clusters,Categorical label assigning the stock to one of 5 return-based statistical industry clusters for the TOP150 universe using the FACT4 method (513 variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
first_method_cluster10_all,Statistical robust industry cluster assignment; integer label indicating membership in 10 clusters using FACT1 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,8,12,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
first_method_cluster5_all,Statistical robust industry cluster assignment; integer label indicating membership in 5 clusters using FACT1 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
fourth_method_cluster10_all,Statistical robust industry cluster assignment; integer label indicating membership in 10 clusters using FACT4 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,8,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
fourth_method_cluster5_all,Statistical robust industry cluster assignment; integer label indicating membership in 5 clusters using FACT4 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
global_method1_group2,Statistical robust industry cluster assignment; integer label indicating membership in 2 clusters using FACT1 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,7,10,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
global_method1_group20,Statistical robust industry cluster assignment; integer label indicating membership in 20 clusters using FACT1 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,4,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
global_method1_group50,Statistical robust industry cluster assignment; integer label indicating membership in 50 clusters using FACT1 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
global_method2_group2,Statistical robust industry cluster assignment; integer label indicating membership in 2 clusters using FACT2 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,4,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
global_method2_group20,Statistical robust industry cluster assignment; integer label indicating membership in 20 clusters using FACT2 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,10,13,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
global_method2_group50,Statistical robust industry cluster assignment; integer label indicating membership in 50 clusters using FACT2 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,9,13,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
global_method3_group2,Statistical robust industry cluster assignment; integer label indicating membership in 2 clusters using FACT3 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,8,9,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
global_method3_group20,Statistical robust industry cluster assignment; integer label indicating membership in 20 clusters using FACT3 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,7,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
global_method3_group50,Statistical robust industry cluster assignment; integer label indicating membership in 50 clusters using FACT3 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,7,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
global_method4_group2,Statistical robust industry cluster assignment; integer label indicating membership in 2 clusters using FACT4 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
global_method4_group20,Statistical robust industry cluster assignment; integer label indicating membership in 20 clusters using FACT4 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
global_method4_group50,Statistical robust industry cluster assignment; integer label indicating membership in 50 clusters using FACT4 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,7,8,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_equity_pca_method1_group2,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT1 method with 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,8,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_equity_pca_method1_group20,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT1 method with 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,7,15,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_equity_pca_method1_group5,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT1 method with 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,4,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_equity_pca_method1_group50,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT1 method with 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_equity_pca_method2_group10,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT2 method with 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_equity_pca_method2_group2,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT2 method with 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_equity_pca_method2_group20,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT2 method with 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_equity_pca_method2_group50,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT2 method with 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_equity_pca_method3_group10,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT3 method with 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_equity_pca_method3_group2,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT3 method with 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_equity_pca_method3_group5,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT3 method with 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_equity_pca_method3_group50,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT3 method with 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_equity_pca_method4_group10,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT4 method with 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_equity_pca_method4_group20,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT4 method with 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_equity_pca_method4_group5,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT4 method with 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method1_grouping10,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT1 method with 10 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method1_grouping2,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT1 method with 2 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method1_grouping20,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT1 method with 20 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method1_grouping5,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT1 method with 5 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method1_grouping50,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT1 method with 50 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method2_grouping10,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT2 method with 10 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method2_grouping2,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT2 method with 2 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method2_grouping20,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT2 method with 20 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method2_grouping5,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT2 method with 5 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method2_grouping50,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT2 method with 50 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method3_grouping10,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT3 method with 10 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method3_grouping2,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT3 method with 2 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method3_grouping20,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT3 method with 20 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method3_grouping5,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT3 method with 5 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method3_grouping50,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT3 method with 50 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method4_grouping10,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT4 method with 10 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method4_grouping2,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT4 method with 2 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method4_grouping20,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT4 method with 20 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method4_grouping5,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT4 method with 5 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_region_method4_grouping50,"Categorical robust industry cluster label for Hong Kong (HKG) TOP500 universe under ASI_HKG_TOP500Robust, using FACT4 method with 50 clusters; integer indicating cluster membership","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method1_group10,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT1 method with 10 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method1_group2,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT1 method with 2 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method1_group20,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT1 method with 20 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method1_group5,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT1 method with 5 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method1_group50,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT1 method with 50 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method2_group10,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT2 method with 10 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method2_group2,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT2 method with 2 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method2_group20,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT2 method with 20 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method2_group5,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT2 method with 5 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method2_group50,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT2 method with 50 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method3_group10,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT3 method with 10 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method3_group2,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT3 method with 2 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method3_group20,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT3 method with 20 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method3_group5,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT3 method with 5 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method3_group50,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT3 method with 50 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method4_group10,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT4 method with 10 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method4_group2,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT4 method with 2 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method4_group20,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT4 method with 20 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method4_group5,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT4 method with 5 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hk_top200_pca_method4_group50,Categorical robust industry cluster label for the Hong Kong TOP200 universe using the FACT4 method with 50 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hongkong_pca_grouping_method1_10clusters,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT1 method with 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hongkong_pca_grouping_method2_5clusters,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT2 method with 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hongkong_pca_grouping_method3_20clusters,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT3 method with 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hongkong_pca_grouping_method4_2clusters,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT4 method with 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
hongkong_pca_grouping_method4_50clusters,"Categorical robust industry cluster label for Hong Kong (HKG) TOP800 stocks in Asia, using FACT4 method with 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method1_group10,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,56,134,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method1_group2,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,28,50,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method1_group20,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,26,84,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method1_group5,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,14,37,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method1_group50,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,25,58,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method2_group10,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,15,39,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method2_group2,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,15,44,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method2_group20,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,21,71,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method2_group5,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,13,67,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method2_group50,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,20,41,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method3_group10,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,21,67,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method3_group2,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,11,30,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method3_group20,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,12,46,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method3_group5,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,10,35,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method3_group50,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,12,44,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method4_group10,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,14,25,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method4_group2,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,13,27,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method4_group20,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,25,60,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method4_group5,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,13,24,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
india_top500_method4_group50,statistical industry classification,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,28,63,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method1_grouping10,"Integer-coded categorical label assigning each stock to one of 10 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT1 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,8,23,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method1_grouping2,"Integer-coded categorical label assigning each stock to one of 2 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT1 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,8,11,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method1_grouping20,"Integer-coded categorical label assigning each stock to one of 20 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT1 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,9,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method1_grouping5,"Integer-coded categorical label assigning each stock to one of 5 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT1 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,6,8,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method1_grouping50,"Integer-coded categorical label assigning each stock to one of 50 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT1 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,8,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method2_grouping10,"Integer-coded categorical label assigning each stock to one of 10 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT2 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,4,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method2_grouping2,"Integer-coded categorical label assigning each stock to one of 2 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT2 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method2_grouping20,"Integer-coded categorical label assigning each stock to one of 20 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT2 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,8,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method2_grouping5,"Integer-coded categorical label assigning each stock to one of 5 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT2 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,11,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method2_grouping50,"Integer-coded categorical label assigning each stock to one of 50 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT2 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method3_grouping10,"Integer-coded categorical label assigning each stock to one of 10 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT3 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method3_grouping2,"Integer-coded categorical label assigning each stock to one of 2 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT3 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,4,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method3_grouping20,"Integer-coded categorical label assigning each stock to one of 20 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT3 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method3_grouping5,"Integer-coded categorical label assigning each stock to one of 5 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT3 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method3_grouping50,"Integer-coded categorical label assigning each stock to one of 50 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT3 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,9,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method4_grouping10,"Integer-coded categorical label assigning each stock to one of 10 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT4 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method4_grouping2,"Integer-coded categorical label assigning each stock to one of 2 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT4 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,7,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method4_grouping20,"Integer-coded categorical label assigning each stock to one of 20 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT4 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method4_grouping5,"Integer-coded categorical label assigning each stock to one of 5 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT4 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
jp_minvol_method4_grouping50,"Integer-coded categorical label assigning each stock to one of 50 robust industry clusters for the Asia region EQY_JPP_Supported_MinVol10M universe, using the FACT4 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,9,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method1_10clusters,Industry group assignment using first PCA method and 10 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method1_20clusters,Industry group assignment using first PCA method and 20 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method1_2clusters,Industry group assignment using first PCA method and 2 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method1_50clusters,Industry group assignment using first PCA method and 50 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method1_5clusters,Industry group assignment using first PCA method and 5 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method2_10clusters,Industry group assignment using second PCA method and 10 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method2_20clusters,Industry group assignment using second PCA method and 20 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method2_2clusters,Industry group assignment using second PCA method and 2 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method2_50clusters,Industry group assignment using second PCA method and 50 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method2_5clusters,Industry group assignment using second PCA method and 5 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method3_10clusters,Industry group assignment using third PCA method and 10 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method3_20clusters,Industry group assignment using third PCA method and 20 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method3_2clusters,Industry group assignment using third PCA method and 2 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method3_50clusters,Industry group assignment using third PCA method and 50 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method3_5clusters,Industry group assignment using third PCA method and 5 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method4_10clusters,Industry group assignment using fourth PCA method and 10 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method4_20clusters,Industry group assignment using fourth PCA method and 20 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method4_2clusters,Industry group assignment using fourth PCA method and 2 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method4_50clusters,Industry group assignment using fourth PCA method and 50 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
minvol_pca_grouping_method4_5clusters,Industry group assignment using fourth PCA method and 5 clusters for minimum volatility universe.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method1_10clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 10 clusters using the FACT1 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method1_20clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 20 clusters using the FACT1 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method1_2clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 2 clusters using the FACT1 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method1_50clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 50 clusters using the FACT1 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method1_5clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 5 clusters using the FACT1 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method2_10clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 10 clusters using the FACT2 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method2_20clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 20 clusters using the FACT2 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method2_2clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 2 clusters using the FACT2 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method2_50clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 50 clusters using the FACT2 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method2_5clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 5 clusters using the FACT2 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method3_10clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 10 clusters using the FACT3 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method3_20clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 20 clusters using the FACT3 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method3_2clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 2 clusters using the FACT3 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method3_50clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 50 clusters using the FACT3 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method3_5clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 5 clusters using the FACT3 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method4_10clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 10 clusters using the FACT4 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method4_20clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 20 clusters using the FACT4 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method4_2clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 2 clusters using the FACT4 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method4_50clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 50 clusters using the FACT4 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
pca_industry_grouping_method4_5clusters,Return-based robust industry cluster membership (categorical) assigning each Korea TOP600 (TRD) stock to one of 5 clusters using the FACT4 variant within the ASI_KOR module,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_0_all513,"Continuous loading on the 1st robust principal component (statistical industry factor) for the ALL universe, computed with the 513 variant","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,14,17,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_0_top1200_xjp_513,First principal component value for the top 1200 ex-Japan securities in group 513.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.3788,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_10_all513,"Continuous loading on the 11th robust principal component (statistical industry factor) for the ALL universe, computed with the 513 variant","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,7,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_10_top1200_xjp_513,Eleventh principal component value for the top 1200 ex-Japan securities in group 513.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.3788,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_11_all513,"Continuous loading on the 12th robust principal component (statistical industry factor) for the ALL universe, computed with the 513 variant","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,6,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_11_top1200_xjp_513,Twelfth principal component value for the top 1200 ex-Japan securities in group 513.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.3788,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_12_all513,"Continuous loading on the 13th robust principal component (statistical industry factor) for the ALL universe, computed with the 513 variant","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,8,9,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_12_top1200_xjp_513,Thirteenth principal component value for the top 1200 ex-Japan securities in group 513.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.3788,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_13_all513,"Continuous loading on the 14th robust principal component (statistical industry factor) for the ALL universe, computed with the 513 variant","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,6,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_13_top1200_xjp_513,Fourteenth principal component value for the top 1200 ex-Japan securities in group 513.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.3788,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_14_all513,"Continuous loading on the 15th robust principal component (statistical industry factor) for the ALL universe, computed with the 513 variant","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,4,4,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_14_top1200_xjp_513,Fifteenth principal component value for the top 1200 ex-Japan securities in group 513.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.3788,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_1_all513,"Continuous loading on the 2nd robust principal component (statistical industry factor) for the ALL universe, computed with the 513 variant","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,14,15,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_1_top1200_xjp_513,Second principal component value for the top 1200 ex-Japan securities in group 513.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.3788,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_2_all513,"Continuous loading on the 3rd robust principal component (statistical industry factor) for the ALL universe, computed with the 513 variant","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,19,24,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_2_top1200_xjp_513,Third principal component value for the top 1200 ex-Japan securities in group 513.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.3788,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_3_all513,"Continuous loading on the 4th robust principal component (statistical industry factor) for the ALL universe, computed with the 513 variant","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,15,17,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_3_top1200_xjp_513,Fourth principal component value for the top 1200 ex-Japan securities in group 513.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.3788,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_4_all513,"Continuous loading on the 5th robust principal component (statistical industry factor) for the ALL universe, computed with the 513 variant","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,35,39,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_4_top1200_xjp_513,Fifth principal component value for the top 1200 ex-Japan securities in group 513.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.3788,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_5_all513,"Continuous loading on the 6th robust principal component (statistical industry factor) for the ALL universe, computed with the 513 variant","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,10,10,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_5_top1200_xjp_513,Sixth principal component value for the top 1200 ex-Japan securities in group 513.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.3788,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_6_all513,"Continuous loading on the 7th robust principal component (statistical industry factor) for the ALL universe, computed with the 513 variant","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,11,11,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_6_top1200_xjp_513,Seventh principal component value for the top 1200 ex-Japan securities in group 513.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.3788,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_7_all513,"Continuous loading on the 8th robust principal component (statistical industry factor) for the ALL universe, computed with the 513 variant","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,19,25,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_7_top1200_xjp_513,Eighth principal component value for the top 1200 ex-Japan securities in group 513.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.3788,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_8_all513,"Continuous loading on the 9th robust principal component (statistical industry factor) for the ALL universe, computed with the 513 variant","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,13,14,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_8_top1200_xjp_513,Ninth principal component value for the top 1200 ex-Japan securities in group 513.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.3788,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_9_all513,"Continuous loading on the 10th robust principal component (statistical industry factor) for the ALL universe, computed with the 513 variant","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9426,6,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_9_top1200_xjp_513,Tenth principal component value for the top 1200 ex-Japan securities in group 513.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.3788,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method1_10clusters,"Integer cluster label assigning the stock to one of 10 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT1 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method1_20clusters,"Integer cluster label assigning the stock to one of 20 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT1 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method1_2clusters_2,"Integer cluster label assigning the stock to one of 2 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT1 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method1_50clusters,"Integer cluster label assigning the stock to one of 50 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT1 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method1_5clusters,"Integer cluster label assigning the stock to one of 5 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT1 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method2_10clusters,"Integer cluster label assigning the stock to one of 10 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT2 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method2_20clusters,"Integer cluster label assigning the stock to one of 20 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT2 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method2_2clusters_2,"Integer cluster label assigning the stock to one of 2 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT2 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method2_50clusters_2,"Integer cluster label assigning the stock to one of 50 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT2 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method2_5clusters,"Integer cluster label assigning the stock to one of 5 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT2 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method3_10clusters,Integer label assigning the stock to one of 10 return-based statistical industry clusters for the TOP1500 universe using the FACT3 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method3_10clusters_2,"Integer cluster label assigning the stock to one of 10 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT3 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method3_20clusters,Integer label assigning the stock to one of 20 return-based statistical industry clusters for the TOP1500 universe using the FACT3 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method3_20clusters_2,"Integer cluster label assigning the stock to one of 20 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT3 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method3_2clusters,"Integer cluster label assigning the stock to one of 2 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT3 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method3_50clusters,Integer label assigning the stock to one of 50 return-based statistical industry clusters for the TOP1500 universe using the FACT3 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method3_50clusters_3,"Integer cluster label assigning the stock to one of 50 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT3 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method3_5clusters,"Integer cluster label assigning the stock to one of 5 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT3 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method4_10clusters,Integer label assigning the stock to one of 10 return-based statistical industry clusters for the TOP1500 universe using the FACT4 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method4_10clusters_2,"Integer cluster label assigning the stock to one of 10 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT4 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method4_20clusters,Integer label assigning the stock to one of 20 return-based statistical industry clusters for the TOP1500 universe using the FACT4 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method4_20clusters_3,"Integer cluster label assigning the stock to one of 20 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT4 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method4_2clusters,Integer label assigning the stock to one of 2 return-based statistical industry clusters for the TOP1500 universe using the FACT4 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method4_2clusters_3,"Integer cluster label assigning the stock to one of 2 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT4 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method4_50clusters,Integer label assigning the stock to one of 50 return-based statistical industry clusters for the TOP1500 universe using the FACT4 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method4_50clusters_2,"Integer cluster label assigning the stock to one of 50 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT4 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method4_5clusters,Integer label assigning the stock to one of 5 return-based statistical industry clusters for the TOP1500 universe using the FACT4 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
principal_component_grouping_method4_5clusters_2,"Integer cluster label assigning the stock to one of 5 statistically derived industry clusters for the TOP400 universe, computed with the robust XJP_513 configuration using the FACT4 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
robust_factor_component_0,First robust factor derived from principal component analysis of returns.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9282,24,28,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
robust_factor_component_1,Second robust factor derived from principal component analysis of returns.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9282,12,16,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
robust_factor_component_10,Eleventh robust factor derived from principal component analysis of returns.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9282,9,10,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
robust_factor_component_11,Twelfth robust factor derived from principal component analysis of returns.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9282,5,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
robust_factor_component_12,Thirteenth robust factor derived from principal component analysis of returns.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9282,12,17,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
robust_factor_component_13,Fourteenth robust factor derived from principal component analysis of returns.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9282,6,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
robust_factor_component_14,Fifteenth robust factor derived from principal component analysis of returns.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9282,11,13,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
robust_factor_component_2,Third robust factor derived from principal component analysis of returns.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9282,6,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
robust_factor_component_3,Fourth robust factor derived from principal component analysis of returns.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9282,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
robust_factor_component_4,Fifth robust factor derived from principal component analysis of returns.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9282,10,11,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
robust_factor_component_5,Sixth robust factor derived from principal component analysis of returns.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9282,5,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
robust_factor_component_6,Seventh robust factor derived from principal component analysis of returns.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9282,11,11,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
robust_factor_component_7,Eighth robust factor derived from principal component analysis of returns.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9282,9,10,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
robust_factor_component_8,Ninth robust factor derived from principal component analysis of returns.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9282,11,15,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
robust_factor_component_9,Tenth robust factor derived from principal component analysis of returns.,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,0.9282,3,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
second_method_cluster10_all,Statistical robust industry cluster assignment; integer label indicating membership in 10 clusters using FACT2 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,16,32,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
second_method_cluster5_all,Statistical robust industry cluster assignment; integer label indicating membership in 5 clusters using FACT2 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,17,29,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_equity_pca_method1_group10,"Categorical cluster label assigning each stock to one of 10 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT1 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,10,37,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_equity_pca_method1_group2,"Categorical cluster label assigning each stock to one of 2 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT1 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,10,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_equity_pca_method1_group50,"Categorical cluster label assigning each stock to one of 50 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT1 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,7,9,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_equity_pca_method3_group20,"Categorical cluster label assigning each stock to one of 20 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT3 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,12,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_equity_pca_method4_group2,"Categorical cluster label assigning each stock to one of 2 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT4 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top100_method1_group2,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT1 method with 2 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top100_method1_group20,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT1 method with 20 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top100_method1_group50,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT1 method with 50 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top100_method2_group10,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT2 method with 10 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top100_method2_group2,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT2 method with 2 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top100_method2_group20,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT2 method with 20 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,4,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top100_method2_group50,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT2 method with 50 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top100_method3_group2,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT3 method with 2 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top100_method3_group5,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT3 method with 5 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top100_method3_group50,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT3 method with 50 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top100_method4_group10,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT4 method with 10 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,4,6,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top100_method4_group20,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT4 method with 20 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top100_method4_group5,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT4 method with 5 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,5,5,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top300_method1_group20,"Categorical cluster label assigning each stock to one of 20 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT1 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top300_method1_group5,"Categorical cluster label assigning each stock to one of 5 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT1 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top300_method2_group10,"Categorical cluster label assigning each stock to one of 10 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT2 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top300_method2_group2,"Categorical cluster label assigning each stock to one of 2 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT2 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top300_method2_group20,"Categorical cluster label assigning each stock to one of 20 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT2 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top300_method2_group5,"Categorical cluster label assigning each stock to one of 5 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT2 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top300_method2_group50,"Categorical cluster label assigning each stock to one of 50 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT2 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,4,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top300_method3_group10,"Categorical cluster label assigning each stock to one of 10 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT3 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top300_method3_group2,"Categorical cluster label assigning each stock to one of 2 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT3 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top300_method3_group5,"Categorical cluster label assigning each stock to one of 5 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT3 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top300_method3_group50,"Categorical cluster label assigning each stock to one of 50 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT3 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top300_method4_group10,"Categorical cluster label assigning each stock to one of 10 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT4 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top300_method4_group20,"Categorical cluster label assigning each stock to one of 20 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT4 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top300_method4_group5,"Categorical cluster label assigning each stock to one of 5 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT4 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top300_method4_group50,"Categorical cluster label assigning each stock to one of 50 robust, return-based industry clusters for the Taiwan TOP300 universe (Asia), computed using the FACT4 method","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method1_group10,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT1 method, with 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method1_group2,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT1 method, with 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method1_group20,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT1 method, with 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method1_group5,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT1 method, with 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method1_group50,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT1 method, with 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method2_group10,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT2 method, with 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method2_group2,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT2 method, with 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method2_group20,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT2 method, with 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method2_group5,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT2 method, with 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method2_group50_500,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT2 method, with 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,8,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method3_group10,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT3 method, with 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method3_group2,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT3 method, with 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method3_group20,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT3 method, with 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method3_group5,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT3 method, with 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method3_group50,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT3 method, with 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method4_group10_500,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT4 method, with 10 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method4_group2,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT4 method, with 2 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method4_group20,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT4 method, with 20 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,7,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method4_group5,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT4 method, with 5 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
taiwan_top500_method4_group50,"Robust return-based industry cluster assignment label for Taiwan TOP500 universe (Asia module) using FACT4 method, with 50 clusters","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,4,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
third_method_cluster10_all,Statistical robust industry cluster assignment; integer label indicating membership in 10 clusters using FACT3 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,15,37,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
third_method_cluster5_all,Statistical robust industry cluster assignment; integer label indicating membership in 5 clusters using FACT3 method for the ALL universe under the _513 variant,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,9,11,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor1_grouping10,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 10 robust, return-based industry groups using the FACT1 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor1_grouping2,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 2 robust, return-based industry groups using the FACT1 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor1_grouping20,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 20 robust, return-based industry groups using the FACT1 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor1_grouping5,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 5 robust, return-based industry groups using the FACT1 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor1_grouping50,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 50 robust, return-based industry groups using the FACT1 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor2_grouping10,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 10 robust, return-based industry groups using the FACT2 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor2_grouping2,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 2 robust, return-based industry groups using the FACT2 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor2_grouping20,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 20 robust, return-based industry groups using the FACT2 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor2_grouping5,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 5 robust, return-based industry groups using the FACT2 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor2_grouping50,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 50 robust, return-based industry groups using the FACT2 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor3_grouping10,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 10 robust, return-based industry groups using the FACT3 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor3_grouping2,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 2 robust, return-based industry groups using the FACT3 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor3_grouping20,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 20 robust, return-based industry groups using the FACT3 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor3_grouping5,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 5 robust, return-based industry groups using the FACT3 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor3_grouping50,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 50 robust, return-based industry groups using the FACT3 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor4_grouping10,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 10 robust, return-based industry groups using the FACT4 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor4_grouping2,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 2 robust, return-based industry groups using the FACT4 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor4_grouping20,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 20 robust, return-based industry groups using the FACT4 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor4_grouping5,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 5 robust, return-based industry groups using the FACT4 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1000_pca_factor4_grouping50,"Categorical cluster ID assigning each stock in the TOP1000 universe to one of 50 robust, return-based industry groups using the FACT4 method (513-window variant)","{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1500_pca_factor1_grouping10,Integer label assigning the stock to one of 10 return-based statistical industry clusters for the TOP1500 universe using the FACT1 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1500_pca_factor1_grouping2,Integer label assigning the stock to one of 2 return-based statistical industry clusters for the TOP1500 universe using the FACT1 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1500_pca_factor1_grouping20,Integer label assigning the stock to one of 20 return-based statistical industry clusters for the TOP1500 universe using the FACT1 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1500_pca_factor1_grouping5,Integer label assigning the stock to one of 5 return-based statistical industry clusters for the TOP1500 universe using the FACT1 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1500_pca_factor1_grouping50,Integer label assigning the stock to one of 50 return-based statistical industry clusters for the TOP1500 universe using the FACT1 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1500_pca_factor2_grouping10,Integer label assigning the stock to one of 10 return-based statistical industry clusters for the TOP1500 universe using the FACT2 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1500_pca_factor2_grouping2,Integer label assigning the stock to one of 2 return-based statistical industry clusters for the TOP1500 universe using the FACT2 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1500_pca_factor2_grouping20,Integer label assigning the stock to one of 20 return-based statistical industry clusters for the TOP1500 universe using the FACT2 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1500_pca_factor2_grouping5,Integer label assigning the stock to one of 5 return-based statistical industry clusters for the TOP1500 universe using the FACT2 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1500_pca_factor2_grouping50,Integer label assigning the stock to one of 50 return-based statistical industry clusters for the TOP1500 universe using the FACT2 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1500_pca_factor3_grouping2,Integer label assigning the stock to one of 2 return-based statistical industry clusters for the TOP1500 universe using the FACT3 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top1500_pca_factor3_grouping5,Integer label assigning the stock to one of 5 return-based statistical industry clusters for the TOP1500 universe using the FACT3 robust method,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method1_10,Categorical industry cluster label assigning each TOP500 stock to 1 of 10 clusters using the robust FACT1 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method1_2,Categorical industry cluster label assigning each TOP500 stock to 1 of 2 clusters using the robust FACT1 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method1_20,Categorical industry cluster label assigning each TOP500 stock to 1 of 20 clusters using the robust FACT1 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method1_5,Categorical industry cluster label assigning each TOP500 stock to 1 of 5 clusters using the robust FACT1 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method1_50,Categorical industry cluster label assigning each TOP500 stock to 1 of 50 clusters using the robust FACT1 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method2_10,Categorical industry cluster label assigning each TOP500 stock to 1 of 10 clusters using the robust FACT2 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method2_2,Categorical industry cluster label assigning each TOP500 stock to 1 of 2 clusters using the robust FACT2 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method2_20,Categorical industry cluster label assigning each TOP500 stock to 1 of 20 clusters using the robust FACT2 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method2_5,Categorical industry cluster label assigning each TOP500 stock to 1 of 5 clusters using the robust FACT2 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method2_50,Categorical industry cluster label assigning each TOP500 stock to 1 of 50 clusters using the robust FACT2 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,8,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method3_10,Categorical industry cluster label assigning each TOP500 stock to 1 of 10 clusters using the robust FACT3 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method3_2,Categorical industry cluster label assigning each TOP500 stock to 1 of 2 clusters using the robust FACT3 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method3_20,Categorical industry cluster label assigning each TOP500 stock to 1 of 20 clusters using the robust FACT3 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method3_5,Categorical industry cluster label assigning each TOP500 stock to 1 of 5 clusters using the robust FACT3 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method3_50,Categorical industry cluster label assigning each TOP500 stock to 1 of 50 clusters using the robust FACT3 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method4_10,Categorical industry cluster label assigning each TOP500 stock to 1 of 10 clusters using the robust FACT4 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method4_2,Categorical industry cluster label assigning each TOP500 stock to 1 of 2 clusters using the robust FACT4 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method4_20,Categorical industry cluster label assigning each TOP500 stock to 1 of 20 clusters using the robust FACT4 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,0,0,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method4_5,Categorical industry cluster label assigning each TOP500 stock to 1 of 5 clusters using the robust FACT4 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
top500_industry_grouping_method4_50,Categorical industry cluster label assigning each TOP500 stock to 1 of 50 clusters using the robust FACT4 method (513-window variant),"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
tw_region_method1_grouping10,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT1 method with 10 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
tw_region_method1_grouping5,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT1 method with 5 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
tw_region_method2_grouping5,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT2 method with 5 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
tw_region_method3_grouping10,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT3 method with 10 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,1,1,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
tw_region_method3_grouping20,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT3 method with 20 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,3,3,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
tw_region_method4_grouping2,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT4 method with 2 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume
tw_region_method4_grouping50,Robust industry cluster assignment (integer label) for the Taiwan TOP100 universe in Asia using the FACT4 method with 50 clusters,"{'id': 'pv30', 'name': 'Alternate Industry Classification'}","{'id': 'pv', 'name': 'Price Volume'}","{'id': 'pv-price-volume', 'name': 'Price Volume'}",IND,1,TOP500,MATRIX,0.9507,1.0,2,2,1.2,[],pv30,Alternate Industry Classification,pv,Price Volume,pv-price-volume,Price Volume