back_test_date_start = (datetime.datetime.strptime(date_seq_start, '%Y-%m-%d')).strftime('%Y%m%d')
back_test_date_end = (datetime.datetime.strptime(date_seq_end, "%Y-%m-%d")).strftime('%Y%m%d')
df = pro.trade_cal(exchange_id='', is_open=1, start_date=back_test_date_start, end_date=back_test_date_end)
date_temp = list(df.iloc[:, 1])
date_seq = [(datetime.datetime.strptime(x, "%Y%m%d")).strftime('%Y-%m-%d') for x in date_temp]
print(date_seq)
#开始模拟交易
index = 1
day_index = 0
for i in range(1,len(date_seq)):
day_index += 1
# 每日推进式建模，并获取对下一个交易日的预测结果
for stock in stock_pool:
try:
ans2 = ev.model_eva(stock,date_seq[i],90,365)
# print('Date : ' + str(date_seq[i]) + ' Update : ' + str(stock))
except Exception as ex:
print(ex)
continue
# 每5个交易日更新一次配仓比例
if divmod(day_index+4,5)[1] == 0:
portfolio_pool = stock_pool
if len(portfolio_pool) < 5:
print('Less than 5 stocks for portfolio!! state_dt : ' + str(date_seq[i]))
continue
pf_src = pf.get_portfolio(portfolio_pool,date_seq[i-1],year)
# 取最佳收益方向的资产组合
risk = pf_src[1][0]
weight = pf_src[1][1]
Filter.filter_main(portfolio_pool,date_seq[i],date_seq[i-1],weight)
def daily_trade(trade_date):
for stock in Utils.stock_pool:
try:
ans2 = ev.model_eva(stock, trade_date, 90, 365)
except Exception as ex:
print('ERROR:', ex)