| Overall Statistics |
|
Total Trades
546
Average Win
0.87%
Average Loss
-0.84%
Compounding Annual Return
1.304%
Drawdown
12.100%
Expectancy
0.146
Net Profit
35.921%
Sharpe Ratio
0.255
Probabilistic Sharpe Ratio
0.003%
Loss Rate
44%
Win Rate
56%
Profit-Loss Ratio
1.04
Alpha
0.006
Beta
0.056
Annual Standard Deviation
0.038
Annual Variance
0.001
Information Ratio
-0.321
Tracking Error
0.156
Treynor Ratio
0.173
Total Fees
$2733.54
Estimated Strategy Capacity
$400000000.00
Lowest Capacity Asset
SPY R735QTJ8XC9X
Portfolio Turnover
6.30%
|
# 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