| Overall Statistics |
|
Total Orders 1 Average Win 0% Average Loss 0% Compounding Annual Return -5.309% Drawdown 6.200% Expectancy 0 Start Equity 100000 End Equity 99126.96 Net Profit -0.873% Sharpe Ratio -0.762 Sortino Ratio -1.147 Probabilistic Sharpe Ratio 27.172% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha -0.073 Beta -1.025 Annual Standard Deviation 0.113 Annual Variance 0.013 Information Ratio -0.444 Tracking Error 0.223 Treynor Ratio 0.084 Total Fees $1.00 Estimated Strategy Capacity $530000000.00 Lowest Capacity Asset SPY R735QTJ8XC9X Portfolio Turnover 1.67% |
# region imports from AlgorithmImports import * # endregion class TestAlgorithm(QCAlgorithm): def initialize(self): self.set_start_date(2025, 1, 1) self.set_end_date(2025, 3, 1) self.set_cash(100000) self.add_equity("SPY", Resolution.SECOND) self.add_alpha(ConstantAlphaModel(InsightType.PRICE, InsightDirection.UP, timedelta(days=10))) self.add_alpha(ConstantAlphaModel(InsightType.PRICE, InsightDirection.DOWN, timedelta(days=10))) self.set_portfolio_construction(EqualWeightingPortfolioConstructionModel(lambda t: Expiry.END_OF_QUARTER(t))) self.settings.rebalance_portfolio_on_insight_changes = False self.debug_mode = True def on_end_of_algorithm(self): for insight in self.insights.get_active_insights(self.utc_time): self.log(f"Insight for {insight.symbol.value} generated at {insight.generated_time_utc} UTC by {insight.source_model}.")
