Overall Statistics |
Total Orders
572
Average Win
0.85%
Average Loss
-0.82%
Compounding Annual Return
1.406%
Drawdown
12.100%
Expectancy
0.158
Start Equity
100000
End Equity
141475.52
Net Profit
41.476%
Sharpe Ratio
-0.314
Sortino Ratio
-0.08
Probabilistic Sharpe Ratio
0.004%
Loss Rate
43%
Win Rate
57%
Profit-Loss Ratio
1.03
Alpha
-0.014
Beta
0.056
Annual Standard Deviation
0.037
Annual Variance
0.001
Information Ratio
-0.353
Tracking Error
0.154
Treynor Ratio
-0.211
Total Fees
$2815.31
Estimated Strategy Capacity
$360000000.00
Lowest Capacity Asset
SPY R735QTJ8XC9X
Portfolio Turnover
6.29%
|
# 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.market: Symbol = self.AddEquity('SPY', Resolution.Minute).Symbol self.liquidate_next_day: bool = False self.Schedule.On(self.DateRules.EveryDay(self.market), self.TimeRules.BeforeMarketClose(self.market, 1), self.Purchase) def Purchase(self) -> None: alg_time = self.Time paydate = self.PaydayDate(alg_time) if alg_time.date() == paydate: self.SetHoldings(self.market, 1) self.liquidate_next_day = True if self.liquidate_next_day: self.liquidate_next_day = False return if self.Portfolio[self.market].IsLong: self.Liquidate(self.market) 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