Overall Statistics |
Total Trades
518
Average Win
0.87%
Average Loss
-0.85%
Compounding Annual Return
1.419%
Drawdown
12.100%
Expectancy
0.156
Net Profit
37.327%
Sharpe Ratio
0.274
Probabilistic Sharpe Ratio
0.007%
Loss Rate
43%
Win Rate
57%
Profit-Loss Ratio
1.02
Alpha
0.007
Beta
0.057
Annual Standard Deviation
0.038
Annual Variance
0.001
Information Ratio
-0.294
Tracking Error
0.157
Treynor Ratio
0.185
Total Fees
$2644.61
Estimated Strategy Capacity
$430000000.00
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 from AlgorithmImports import * 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