Overall Statistics |
Total Orders 9 Average Win 9.96% Average Loss -0.84% Compounding Annual Return 21.939% Drawdown 6.100% Expectancy 2.217 Start Equity 1000000 End Equity 1287458.35 Net Profit 28.746% Sharpe Ratio 1.339 Sortino Ratio 1.623 Probabilistic Sharpe Ratio 90.387% Loss Rate 75% Win Rate 25% Profit-Loss Ratio 11.87 Alpha 0.027 Beta 0.48 Annual Standard Deviation 0.073 Annual Variance 0.005 Information Ratio -0.646 Tracking Error 0.076 Treynor Ratio 0.203 Total Fees $111.21 Estimated Strategy Capacity $1000000000.00 Lowest Capacity Asset SPY R735QTJ8XC9X Portfolio Turnover 1.93% |
# region imports from AlgorithmImports import * # endregion class QuantLeague(QCAlgorithm): def initialize(self): self.set_start_date(2023, 1, 1) self.set_cash(1000000) self.symbol = self.add_equity("SPY", Resolution.Daily).Symbol self.fast_moving_average = self.sma(self.symbol, 50, Resolution.Daily) self.last_action = None def on_data(self, data): # Ensure we have enough data to calculate the moving average if not self.fast_moving_average.is_ready: return price = data[self.symbol].Close # Buy if the price is above the moving average if price > self.fast_moving_average.current.value: if not self.portfolio.invested or self.last_action == "Sell": self.set_holdings(self.symbol, 1) self.last_action = "Buy" # Sell if the price is below the moving average elif price < self.fast_moving_average.current.value: if self.portfolio.invested and self.last_action == "Buy": self.liquidate(self.symbol) self.last_action = "Sell"