Overall Statistics
Total Trades
2725
Average Win
0.09%
Average Loss
-0.02%
Compounding Annual Return
13.949%
Drawdown
10.400%
Expectancy
3.627
Net Profit
269.458%
Sharpe Ratio
1.168
Probabilistic Sharpe Ratio
66.915%
Loss Rate
15%
Win Rate
85%
Profit-Loss Ratio
4.46
Alpha
0.033
Beta
0.542
Annual Standard Deviation
0.084
Annual Variance
0.007
Information Ratio
-0.303
Tracking Error
0.075
Treynor Ratio
0.181
Total Fees
$2745.91
Estimated Strategy Capacity
$41000.00
Lowest Capacity Asset
VXZB WRBPJAJZ2Q91
import numpy as np

class spyVXXAlgo(QCAlgorithm):

    def Initialize(self):
        
        self.SetStartDate(2012,1, 1) # Set Start Date
        self.SetEndDate(2022,1,1)    # Set End Date
        self.SetCash(100000)         # Set Strategy Cash

        # Define the security universe
        self.tickers = ["SPY","VXZ"]
        for symbol in self.tickers:
            self.AddEquity(symbol, Resolution.Daily)
        

    def OnData(self, data):
            # Rebalance portfolio daily
            for symbol in self.tickers:
                if symbol=="SPY":
                    self.SetHoldings(symbol,0.74)
                else:
                    self.SetHoldings(symbol,0.25)