Overall Statistics
Total Orders
10395
Average Win
0.49%
Average Loss
-0.19%
Compounding Annual Return
6.440%
Drawdown
20.300%
Expectancy
0.101
Start Equity
100000
End Equity
253496.59
Net Profit
153.497%
Sharpe Ratio
0.336
Sortino Ratio
0.398
Probabilistic Sharpe Ratio
1.065%
Loss Rate
69%
Win Rate
31%
Profit-Loss Ratio
2.50
Alpha
-0.01
Beta
0.47
Annual Standard Deviation
0.095
Annual Variance
0.009
Information Ratio
-0.563
Tracking Error
0.101
Treynor Ratio
0.068
Total Fees
$66686.71
Estimated Strategy Capacity
$1200000.00
Lowest Capacity Asset
SHY SGNKIKYGE9NP
Portfolio Turnover
190.49%
 
# region imports
from AlgorithmImports import *
# endregion

class KellyCriterionSMACrossoverAlgorithm(QCAlgorithm):

    def initialize(self):
        self.set_start_date(2010, 1, 1)
        # Add the risky and risk-free assets.
        self._risk_asset = self.add_equity("SPY", Resolution.HOUR)
        self._rf_asset = self.add_equity('SHY', Resolution.HOUR)
        # Add some strategy-specific indicators/variables.
        self._risk_asset.short_sma = self.sma(self._risk_asset.symbol, 1)
        self._risk_asset.long_sma = self.sma(self._risk_asset.symbol, 6)
        # Add a warm-up period so we some historical performance of the strategy
        # once we start trading.
        self.set_warm_up(timedelta(365))

    def on_data(self, data: Slice):
        # Wait until the market is open.
        if not data.bars or not self.is_market_open(self._risk_asset.symbol) or self.is_warming_up:
            return
        if  not self._risk_asset.holdings.is_long and self._risk_asset.short_sma > self._risk_asset.long_sma:
            self.set_holdings([PortfolioTarget(self._risk_asset.symbol, 1)], True)
        elif self._risk_asset.holdings.is_long and self._risk_asset.short_sma < self._risk_asset.long_sma:
            self.set_holdings([PortfolioTarget(self._rf_asset.symbol, 1)], True)