Overall Statistics |
Total Trades
85
Average Win
12.65%
Average Loss
-7.57%
Compounding Annual Return
6.917%
Drawdown
56.100%
Expectancy
0.564
Net Profit
309.990%
Sharpe Ratio
0.412
Probabilistic Sharpe Ratio
0.118%
Loss Rate
41%
Win Rate
59%
Profit-Loss Ratio
1.67
Alpha
0.08
Beta
-0.093
Annual Standard Deviation
0.179
Annual Variance
0.032
Information Ratio
0.017
Tracking Error
0.263
Treynor Ratio
-0.797
Total Fees
$633.16
|
# https://quantpedia.com/strategies/january-effect-in-stocks/ # # Invest in small-cap stocks at the beginning of each January. Stay invested in large-cap stocks for the rest of the year. # # QC implementation changes: # - Small cap etf (IWM) and large cap etf (SPY) are used as investment assets. class JanuaryEffectInStocks(QCAlgorithm): def Initialize(self): self.SetStartDate(2000, 1, 1) self.SetCash(100000) self.large_cap = self.AddEquity('SPY', Resolution.Daily).Symbol self.small_cap = self.AddEquity('IWM', Resolution.Daily).Symbol self.Schedule.On(self.DateRules.MonthStart(self.large_cap), self.TimeRules.AfterMarketOpen(self.large_cap), self.Rebalance) def Rebalance(self): if self.Time.month == 1: if self.Portfolio[self.large_cap].Invested: self.Liquidate(self.large_cap) self.SetHoldings(self.small_cap, 1) else: if self.Portfolio[self.small_cap].Invested: self.Liquidate(self.small_cap) self.SetHoldings(self.large_cap, 1)