Overall Statistics |
Total Trades 208 Average Win 2.64% Average Loss -0.03% Compounding Annual Return 38.588% Drawdown 45.300% Expectancy 77.334 Net Profit 2980.031% Sharpe Ratio 1.466 Probabilistic Sharpe Ratio 74.668% Loss Rate 3% Win Rate 97% Profit-Loss Ratio 79.64 Alpha 0.212 Beta 1.572 Annual Standard Deviation 0.31 Annual Variance 0.096 Information Ratio 1.689 Tracking Error 0.178 Treynor Ratio 0.289 Total Fees $209.48 |
# Inspired by the theory here: # https://seekingalpha.com/article/4299701-leveraged-etfs-for-long-term-investing class Investment(object): def __init__(self, symbol, weight): self.symbol = symbol self.weight = weight class MultidimensionalTransdimensionalPrism(QCAlgorithm): def Initialize(self): self.SetStartDate(2010, 3, 1) self.SetCash(1600) self.AddEquity("SPY", Resolution.Hour) self.cashToAdd = 0 self.investments = [ Investment("TQQQ", 0.6), Investment("TLT", 0.4), ] # Add symbols for investment in self.investments: self.AddEquity(investment.symbol, Resolution.Hour) # Schedules self.Schedule.On(self.DateRules.MonthStart("SPY"), self.TimeRules.AfterMarketOpen("SPY", 150), self.Rebalance) self.Schedule.On(self.DateRules.MonthStart("SPY"), self.TimeRules.AfterMarketOpen("SPY", 140), self.AddCash) def OnData(self, data): pass def Rebalance(self): for investment in self.investments: self.SetHoldings(investment.symbol, investment.weight) def AddCash(self): self.Portfolio.SetCash(self.Portfolio.Cash + self.cashToAdd)