Overall Statistics |
Total Trades 500 Average Win 0.87% Average Loss -0.83% Compounding Annual Return 1.635% Drawdown 12.200% Expectancy 0.182 Net Profit 42.143% Sharpe Ratio 0.378 Probabilistic Sharpe Ratio 0.449% Loss Rate 42% Win Rate 58% Profit-Loss Ratio 1.05 Alpha 0.012 Beta 0.057 Annual Standard Deviation 0.046 Annual Variance 0.002 Information Ratio -0.403 Tracking Error 0.188 Treynor Ratio 0.306 Total Fees $2578.92 Estimated Strategy Capacity $250000000.00 Lowest Capacity Asset SPY R735QTJ8XC9X |
# https://quantpedia.com/strategies/payday-anomaly/ # # The investment universe consists of the S&P500 index. Simply, buy and hold the index during the 16th day in the month during each month of the year. from dateutil.relativedelta import relativedelta class PayDayAnomaly(QCAlgorithm): def Initialize(self): self.SetStartDate(2000, 1, 1) self.SetCash(100000) self.symbol = self.AddEquity('SPY', Resolution.Minute).Symbol self.liquidate_next_day = False self.Schedule.On(self.DateRules.EveryDay(self.symbol), self.TimeRules.BeforeMarketClose(self.symbol, 1), self.Purchase) def Purchase(self): alg_time = self.Time paydate = self.PaydayDate(alg_time) if alg_time.date() == paydate: self.SetHoldings(self.symbol, 1) self.liquidate_next_day = True # self.algorithm.EmitInsights(Insight.Price(self.symbol, timedelta(days=1), InsightDirection.Up, None, None, None, self.weight)) if self.liquidate_next_day: self.liquidate_next_day = False return if self.Portfolio[self.symbol].IsLong: self.Liquidate(self.symbol) def PaydayDate(self, date_time): payday = date(date_time.year, date_time.month, 1) + relativedelta(day=15) if payday.weekday() == 5: # Is saturday. payday = payday - timedelta(days=1) elif payday.weekday() == 6: # Is sunday. payday = payday - timedelta(days=2) return payday