@jyshee 因子叠加的选股代码，仅供参考
```
def get_stock_list(context):
yesterday = str(context.previous_date)
initial_list = get_all_securities().index.tolist()
initial_list = filter_new_stock(context,initial_list)
initial_list = filter_kcb_stock(context, initial_list)
initial_list = filter_st_stock(initial_list)
factor_values = get_factor_values(initial_list, ['operating_revenue_growth_rate', #营业收入增长率
'total_profit_growth_rate', #利润总额增长率
'net_profit_growth_rate', #净利润增长率
'earnings_growth', #5年盈利增长率
'sales_growth', #5年营业收入增长率
], end_date=yesterday, count=1)
df = pd.DataFrame(index=initial_list, columns=factor_values.keys())
df['operating_revenue_growth_rate'] = list(factor_values['operating_revenue_growth_rate'].T.iloc[:,0])
df['total_profit_growth_rate'] = list(factor_values['total_profit_growth_rate'].T.iloc[:,0])
df['net_profit_growth_rate'] = list(factor_values['net_profit_growth_rate'].T.iloc[:,0])
df['earnings_growth'] = list(factor_values['earnings_growth'].T.iloc[:,0])
df['sales_growth'] = list(factor_values['sales_growth'].T.iloc[:,0])
df['total_score'] = 0.1*df['operating_revenue_growth_rate'] + 0.35*df['total_profit_growth_rate'] + 0.15*df['net_profit_growth_rate'] + 0.35*df['earnings_growth'] + 0.05*df['sales_growth']
df = df.sort_values(by=['total_score'], ascending=False)
complex_growth_list = list(df.index)[:int(0.1*len(list(df.index)))]
q = query(valuation.code,valuation.circulating_market_cap,indicator.eps).filter(valuation.code.in_(complex_growth_list)).order_by(valuation.circulating_market_cap.asc())
df = get_fundamentals(q)
df = df[df['eps']>0]
final_list = list(df.code)
return final_list
```
2021-12-18
雪球
