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73 lines
2.8 KiB
73 lines
2.8 KiB
"""
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WQC Chapter2 速通脚本
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生成20条Delay1-USA因子 -> 体检 -> 返回第一条五项全绿因子
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"""
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import pandas as pd
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import numpy as np
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from wq_core import alpha, get_univ # 网页Notebook已内置
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# ---------- 参数 ----------
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REGION = 'USA'
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DELAY = 1
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UNIV = get_univ('TOP3000') # 教学关默认宇宙
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N_FACTOR = 20
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METRICS = ['fitness','sharpe','turnover','max_weight','sub_univ_ok']
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GREEN = {'fitness':1.0, 'sharpe':1.25, 'turnover':(1,70), 'max_weight':10, 'sub_univ_ok':True}
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# ---------- 1. 因子定义池 ----------
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raw_expr = {
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'mom5' : 'rank(ts_return(close,5))',
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'mom10' : 'rank(ts_return(close,10))',
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'rev5' : 'rank(-ts_return(close,5))',
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'rev10' : 'rank(-ts_return(close,10))',
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'vol10' : 'rank(-ts_std(return,10))',
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'vol20' : 'rank(-ts_std(return,20))',
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'amt5' : 'rank(-ts_mean(amount,5))', # 短期缩量
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'amt10' : 'rank(-ts_mean(amount,10))',
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'illiq10': 'rank(ts_mean(abs(return)/amount,10))', # 非流动
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'illiq20': 'rank(ts_mean(abs(return)/amount,20))',
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# 以下再加半衰变体
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'mom5_d7': 'rank(ts_decay_linear(ts_return(close,5),7))',
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'mom5_d10':'rank(ts_decay_linear(ts_return(close,5),10))',
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'rev5_d7': 'rank(-ts_decay_linear(ts_return(close,5),7))',
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'vol10_d7':'rank(-ts_decay_linear(ts_std(return,10),7))',
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'amt5_d7': 'rank(-ts_decay_linear(ts_mean(amount,5),7))',
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'illiq10_d7':'rank(ts_decay_linear(ts_mean(abs(return)/amount,10),7))',
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# 反转+波动组合
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'rev_vol':'rank(-ts_return(close,5)*ts_std(return,10))',
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'mom_vol':'rank(ts_return(close,5)/ts_std(return,10))',
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'amt_rev':'rank(-ts_mean(amount,5)*ts_return(close,5))',
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}
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# ---------- 2. 批量生成+体检 ----------
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result = []
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for name, expr in raw_expr.items():
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fac = alpha(expr, UNIV, delay=DELAY)
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rpt = fac.test(region=REGION, delay=DELAY) # 返回dict
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rpt['name'] = name
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rpt['expr'] = expr
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result.append(rpt)
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df = pd.DataFrame(result)
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# ---------- 3. 过滤全绿 ----------
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def is_green(row):
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ok = (row.fitness >= GREEN['fitness'] and
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row.sharpe >= GREEN['sharpe'] and
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GREEN['turnover'][0] <= row.turnover <= GREEN['turnover'][1] and
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row.max_weight <= GREEN['max_weight'] and
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row.sub_univ_ok == GREEN['sub_univ_ok'])
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return ok
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greens = df[df.apply(is_green, axis=1)].reset_index(drop=True)
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# ---------- 4. 输出 ----------
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if greens.empty:
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print('>>> 暂无全绿因子，尝试调半衰期或再中性化 <<<')
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else:
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pick = greens.iloc[0] # 首条即可提交
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print('>>> 发现全绿因子！直接复制下方代码去提交页 <<<')
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print(f'# 因子名: {pick.name}')
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print(f'expression = "{pick.expr}"')
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print(f'# Fitness={pick.fitness:.2f} Sharpe={pick.sharpe:.2f} '
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f'Turnover={pick.turnover:.1f}% MaxWeight={pick.max_weight:.1f}%') |