Overall Statistics |
Total Trades
412
Average Win
0.98%
Average Loss
-0.89%
Compounding Annual Return
1.114%
Drawdown
13.400%
Expectancy
0.126
Net Profit
22.873%
Sharpe Ratio
0.236
Loss Rate
47%
Win Rate
53%
Profit-Loss Ratio
1.11
Alpha
-0.008
Beta
1.008
Annual Standard Deviation
0.053
Annual Variance
0.003
Information Ratio
-0.143
Tracking Error
0.053
Treynor Ratio
0.012
Total Fees
$2101.71
|
import numpy as np from datetime import timedelta class PreHolidayEffectAlgorithm(QCAlgorithm): def Initialize(self): self.SetStartDate(2000, 1, 1) self.SetEndDate(2018, 8, 1) self.SetCash(100000) self.AddEquity("SPY", Resolution.Daily) def OnData(self, data): calendar1 = self.TradingCalendar.GetDaysByType(TradingDayType.PublicHoliday, self.Time, self.Time+timedelta(days=2)) calendar2 = self.TradingCalendar.GetDaysByType(TradingDayType.Weekend, self.Time, self.Time+timedelta(days=2)) holidays = [i.Date for i in calendar1] weekends = [i.Date for i in calendar2] # subtract weekends in all holidays public_holidays = list(set(holidays) - set(weekends)) if not self.Portfolio.Invested and len(public_holidays)>0: self.SetHoldings("SPY", 1) elif self.Portfolio.Invested and len(public_holidays)==0: self.Liquidate()