df_stock['date']=pd.to_datetime(df_stock['time_key'])
df_stock.to_csv(path + filename)
df_stock.index = pd.to_datetime(df_stock.date)
df_stock['openinterest']=0
df_stock = df_stock[['open','high','low','close','volume','openinterest']]
df.update({stock:df_stock})
return df
if __name__ == "__main__":
start = '2017-01-09'
end = '2020-09-05'
code = ['HK.00700']
name = code
df_stock = get_stockdata(code,start,end)
df_cn = pd.read_csv('to_cn.csv',index_col=0)
df_stock = get_stockdata(code,start,end)
backtest = backtest.BackTest(Tech_roll, start, end, code, name,500000,bDraw = True)
result = backtest.run()
#result = backtest.run()
#result = backtest.optRun(myperiod = range(50,150,20))
#print(result)
print(result)
#maxindex = ret[ret == ret.max()].index
#bestResult = result.loc[maxindex,:]
#print(bestResult.loc[:, ["夏普比率", "参数名", "参数值", "年化收益率"]])
stock = tradeBar.iloc[i].成交量
commit = tradeBar.iloc[i].手续费
# 进行交易
self.__doTrade(data, name, price, stock, commit, orderType)
def next(self):
if self.order:
return
self.doTrade()
def stop(self):
self.order = self.close()
self.log("最大回撤:-%.2f%%" % self.stats.drawdown.maxdrawdown[-1], doprint=True)
if __name__ == "__main__":
# 加载数据，建立数据源
start = "2018-01-01"
end = "2020-07-05"
name = ["300ETF", "nasETF"]
code = ["510300", "513100"]
backtest = backtest.BackTest(TradeStrategy, start, end, code, name, cash = 1000)
results = backtest.run()
# backtest.output()
print(results)
#returns = backtest.getReturns()
# print(returns)
# returns[0].to_csv("1.csv")
# returns[1].to_csv("2.csv")
tradeBar = self.df_record.loc[date.strftime("%Y-%m-%d"), :]
# print("bar数据", date, data._name)
if len(tradeBar) != 0:
for i in range(len(tradeBar)):
name = tradeBar.iloc[i].证券名称
price = tradeBar.iloc[i].成交均价
stock = tradeBar.iloc[i].成交量
commit = tradeBar.iloc[i].手续费
# 进行交易
self.__doTrade(data, name, price, stock, commit, orderType)
def next(self):
if self.order:
return
self.doTrade()
def stop(self):
self.log("最大回撤:-%.2f%%" % self.stats.drawdown.maxdrawdown[-1],
doprint=True)
if __name__ == "__main__":
# 加载数据，建立数据源
start = "2018-01-01"
end = "2020-07-05"
name = ["300ETF", "nasETF"]
code = ["510300", "513100"]
backtest = backtest.BackTest(TradeStrategy, start, end, code, name)
backtest.run()
backtest.output()
import backtest
from random import randint
'''
A silly example algorithm for demonstration purposes.
BUY/SELL or HOLD based on a coin flip.
'''
class Algo:
def __init__(self):
self.holding = False
def tick(self, frame):
res = randint(0, 1)
if res == 0 and not self.holding:
self.holding = True
return 'BUY', 100
elif res == 1 and self.holding:
self.holding = False
return 'SELL', 100
else:
return 'NOTHING'
stubAlgo = Algo()
results = backtest.run(stubAlgo, currency='USDT_BTC')
print 'total profit: ' + str(sum(results[1]))