多因子选股＋指标择时 python3.7+tushare pro

因子选股＋指标择时 python3.7+tushare pro"/>

多因子选股＋指标择时 python3.7+tushare pro

import tushare as ts
import pandas as pd
import timets.set_token('**************************')
pro=ts.pro_api()
# 获取股票池
hs300_all_stock = []stocks = []df = pro.index_weight(index_code='399300.SZ', start_date='202011011')hs300_all_stock = df['con_code'].values.tolist()index_num = []for i in range(len(hs300_all_stock)):index_num.append(i)data=pd.DataFrame(index=index_num,columns=['code','turn_over','total_mv','attack'])data.code = hs300_all_stock
# 获取股票池所有股票信息    len(hs300_all_stock)
for num in range(100):#turn_over:换手率  total_mv:总市值   attack：攻击波stock_data = pro.bak_daily(ts_code = data.code[num],start_date = '20201110',\end_date = '20201111',fields='turn_over,total_mv,attack')data.turn_over[num] = stock_data['turn_over'][0]data.total_mv[num] = stock_data['total_mv'][0]data.attack[num] = stock_data['attack'][0]time.sleep(6)
data.to_excel('沪深300换手率冲击波1.xlsx')
# 通过市值升序排列 取100个，通过换手率降序排列取出前30，通过攻击波取前10名，短线操作
data.sort_values(by=["total_mv"],ascending=True)
data1 = data.head(int(len(data)/3))  data1.sort_values(by=["turn_over"],ascending=False)
data2 = data1.head(int(len(data1)/3))    data2.sort_values(by=["attack"],ascending=False)
data3 = data2.head(int(len(data2)/3))  stocks = data3['code'].values.tolist()   
print(stocks)
# 获取十日平均，和5日平均，及当前价
for stock in stocks:df1 = pro.daily(ts_code=stock, start_date='20201001', end_date='20201111')df1=df1.sort_values(by=["trade_date"],ascending=True)df1.index = df1.iloc[:,1]df1.index = pd.to_datetime(df1.index,format='%Y-%m-%d')data4 = pd.DataFrame(index=df1.index,columns=['close','mean5','mean10'])data4['close'] = df1.closedata4['mean5']=data4.close.rolling(5).mean()data4['mean10']=data4.close.rolling(10).mean()if data4['close'][-1] < data4['mean5'][-1] and data4['close'][-1] < data4['mean5'][-1]:stocks.remove(stock)print(stocks)