| Overall Statistics |
|
Total Trades 1 Average Win 0% Average Loss 0% Compounding Annual Return 51.821% Drawdown 7.500% Expectancy 0 Net Profit 5.157% Sharpe Ratio 1.916 Probabilistic Sharpe Ratio 58.691% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0.441 Beta 0.009 Annual Standard Deviation 0.233 Annual Variance 0.054 Information Ratio -0.317 Tracking Error 0.262 Treynor Ratio 48.653 Total Fees $1.54 Estimated Strategy Capacity $770000000.00 |
# MOMP test.
# ---------------------------------
STOCK = 'QQQ'; RETURN_PERIOD = 126;
# ---------------------------------
class EnergeticOrangeBat(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2021, 3, 1)
self.SetEndDate(2021, 6, 1)
self.SetCash(100000)
self.stock = self.AddEquity(STOCK, Resolution.Daily).Symbol
# Warm up with history, not automatic
self.mom0 = self.MOMP(self.stock, RETURN_PERIOD, Resolution.Daily)
history = self.History(self.stock, RETURN_PERIOD, Resolution.Daily)
for time, row in history.loc[self.stock].iterrows():
self.mom0.Update(time, row.close)
# Automatic Wwarm up with history
self.EnableAutomaticIndicatorWarmUp = True
self.mom = self.MOMP(self.stock, RETURN_PERIOD, Resolution.Daily)
self.Log(f"Starting values ref: {self.mom0.Current.Value} {self.mom0.Samples}")
self.Log(f"Starting values : {self.mom.Current.Value} {self.mom.Samples}")
self.mom_2, df = self.returns(self.stock, RETURN_PERIOD)
self.mom_3, df2 = self.returns(self.stock, RETURN_PERIOD+1)
def returns(self, symbol, period):
history = self.History(symbol, period, Resolution.Daily)
volume = history.volume
if len(volume) != period:
self.Log(f'Len = {len(volume)}')
prices = history.close
return float(100*(prices.iloc[-1]/prices.iloc[0] - 1)), history
def OnData(self, data):
if self.stock not in data.Bars:
return
if not self.Portfolio.Invested:
self.SetHoldings(self.stock, 1)
self.mom_2, df = self.returns(self.stock, RETURN_PERIOD)
self.mom_3, df2 = self.returns(self.stock, RETURN_PERIOD+1)
self.Plot("Momentum Percent", "RET", self.mom_2)
self.Plot("Momentum Percent", "RET+1", self.mom_3)
self.Plot("Momentum Percent", "MOMP", self.mom.Current.Value)
self.Plot("Momentum Percent", "MOMP Ref", self.mom0.Current.Value)
self.Log(f"Ending values: {self.mom.Current.Value} {self.mom0.Current.Value} {self.mom_2} {self.mom_3}")