| Overall Statistics |
|
Total Trades 1 Average Win 0% Average Loss 0% Compounding Annual Return 19.316% Drawdown 33.700% Expectancy 0 Net Profit 24.684% Sharpe Ratio 0.728 Probabilistic Sharpe Ratio 34.205% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0.251 Beta -0.23 Annual Standard Deviation 0.279 Annual Variance 0.078 Information Ratio -0.009 Tracking Error 0.438 Treynor Ratio -0.883 Total Fees $1.58 Estimated Strategy Capacity $670000000.00 |
import numpy as np
class StandardDeviation_test(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2020, 1, 1)
self.SetCash(100000)
self.spy = self.AddEquity("SPY", Resolution.Daily).Symbol
self.SetWarmUp(101)
self.std = StandardDeviation("SPY", 100)
self.std_short = self.STD("SPY", 100, Resolution.Daily)
def OnData(self, data):
if self.IsWarmingUp: return
if not self.Portfolio.Invested:
self.SetHoldings("SPY", 1)
def OnEndOfDay(self):
if self.IsWarmingUp: return
self.std.Update(self.Time, self.Securities[self.spy].Close)
self.Plot('StandardDeviation', "StandardDeviation",float(self.std.Current.Value))
self.Plot('STD', "STD", float(self.std_short.Current.Value))
std = self.History([self.spy], 100, Resolution.Daily).close.std()
self.Plot('std', 'std', float(std))