| Overall Statistics |
|
Total Orders 582 Average Win 0.84% Average Loss -0.82% Compounding Annual Return 1.432% Drawdown 12.100% Expectancy 0.162 Start Equity 100000 End Equity 143244.25 Net Profit 43.244% Sharpe Ratio -0.326 Sortino Ratio -0.084 Probabilistic Sharpe Ratio 0.004% Loss Rate 43% Win Rate 57% Profit-Loss Ratio 1.02 Alpha -0.014 Beta 0.055 Annual Standard Deviation 0.037 Annual Variance 0.001 Information Ratio -0.344 Tracking Error 0.154 Treynor Ratio -0.22 Total Fees $2845.01 Estimated Strategy Capacity $420000000.00 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