Name
Dynamic Adjustment Factor of Supplier Concentration
Hypothesis
The dynamic change in supplier concentration (measured by the proportion of purchases from the top 5 suppliers to total purchases) directly reflects an enterprise's ability to control supply chain risks. If a company's supplier concentration continues to decline from a high level, it indicates that it is actively diversifying supply chain dependence risks, which can effectively reduce operational shocks caused by default, price increase or supply disruption of a single supplier, thereby improving profit stability and risk resistance. Such enterprises deserve a valuation premium and are suitable for establishing long positions. Conversely, if supplier concentration continues to rise from a low level, the enterprise's dependence on a few suppliers deepens, supply chain vulnerability increases, and operational uncertainty rises, making it suitable for establishing short positions. In addition, the speed and magnitude of concentration adjustment are positively correlated with excess returns—fast and reasonable diversification adjustments have higher signal value than slow adjustments.
Implementation Plan
Calculate core indicators: Based on enterprise procurement data, measure the supplier concentration ratio (CR5 = purchase amount from top 5 suppliers / total purchase amount);
Time-series trend analysis: Use the time-series trend operator (ts_trend) to fit the change slope of CR5 over the past 12 months, and classify targets into three categories: "continuous decline (negative slope with absolute value greater than threshold)", "continuous rise (positive slope with absolute value greater than threshold)", and "stable fluctuation";
Scale and industry calibration: Divide CR5 by the logarithm of the enterprise's total purchase amount to eliminate scale effects, and calculate the deviation of the target's CR5 from the industry average;
Construct long-short strategy: Establish long positions on targets with "continuously declining CR5 + current CR5 below industry average"; establish short positions on targets with "continuously rising CR5 + current CR5 above industry average"; exclude targets with stable CR5 fluctuation and small deviation from industry average to reduce noise.
Alpha Factor Optimization Suggestions
Introduce industry-differentiated thresholds: There are significant differences in the benchmark values of supplier concentration across industries (e.g., the concentration of core material suppliers in the semiconductor industry is naturally high, while that in the consumer goods industry is low). It is recommended to use the industry quantile operator instead of fixed thresholds to judge the rationality of concentration adjustment by stratification within the industry;
Superimpose supplier quality verification: Integrate data such as supplier credit ratings and cooperation years. When the decline in concentration is accompanied by "the credit rating of new suppliers being higher than that of original suppliers", strengthen the weight of long signals; if the rise in concentration stems from "exclusive cooperation with high-quality suppliers", weaken the short signals;
Event-driven weight adjustment: Use the event trigger operator to increase the allocation weight of this factor during industry-wide supply chain crises (such as raw material price surges, material supply disruptions caused by geopolitics), capturing excess returns of supply chain-robust enterprises during crises;
Tiered weighting optimization: Use the stratification operator to divide the concentration adjustment range into three tiers: "significant adjustment", "moderate adjustment" and "minor adjustment", and set differentiated position weights for different tiers to improve the risk-return ratio of the strategy.