Statistics

public class AlgorithmStatisticsAlgorithm : QCAlgorithm
{
    private Symbol _spy;
    private ExponentialMovingAverage _ema;
    private List<string> _statistics = new() { "Time,Sharpe,Beta,95VaR" };

    public override void Initialize()
    {
        SetStartDate(2024, 8, 12);
        SetEndDate(2024, 9, 1);
        SetCash(1000000);

        // Request SPY data to trade.
        _spy = AddEquity("SPY").Symbol;
        // Create an EMA indicator to generate trade signals.
        _ema = EMA(_spy, 20, Resolution.Daily);
        // Warm-up indicator for immediate readiness.
        WarmUpIndicator(_spy, _ema, Resolution.Daily);
    }

    public override void OnData(Slice slice)
    {
        if (slice.Bars.TryGetValue(_spy, out var bar))
        {
            // Trend-following strategy using price above or below EMA.
            // If the price is above EMA, SPY is in an uptrend, and we buy it.
            if (bar.Close > _ema && !Portfolio[_spy].IsLong)
            {
                SetHoldings(_spy, 1m);
            }
            else if (bar.Close < _ema && !Portfolio[_spy].IsShort)
            {
                SetHoldings(_spy, -1m);
            }
        }
    }

    public override void OnEndOfDay(Symbol symbol)
    {
        // Obtain the algorithm statistics interested.
        var sharpe = Statistics.TotalPerformance.PortfolioStatistics.SharpeRatio;
        var b = Statistics.TotalPerformance.PortfolioStatistics.Beta;
        var var = Statistics.TotalPerformance.PortfolioStatistics.ValueAtRisk95;

        // Plot the statistics.
        Plot("Statistics", "Sharpe", sharpe);
        Plot("Statistics", "Beta", b);
        Plot("Statistics", "Value-at-Risk", var);

        // Write to save the statistics.
        _statistics.Add($"{Time:yyyyMMdd},{sharpe},{b},{var}");
    }

    public override void OnEndOfAlgorithm()
    {
        // Save the logged statistics for later access in the object store.
        ObjectStore.Save($"{ProjectId}/algorithm-statistics", string.Join('\n', _statistics));
    }
}

class AlgorithmStatisticsAlgorithm(QCAlgorithm):
    _statistics = ["Time,Sharpe,Beta,95VaR"]

    def initialize(self) -> None:
        self.set_start_date(2024, 8, 12)
        self.set_end_date(2024, 9, 1)
        self.set_cash(1000000)

        # Request SPY data to trade.
        self.spy = self.add_equity("SPY").symbol
        # Create an EMA indicator to generate trade signals.
        self._ema = self.ema(self.spy, 20, Resolution.DAILY)
        # Warm-up indicator for immediate readiness.
        self.warm_up_indicator(self.spy, self._ema, Resolution.DAILY)

    def on_data(self, slice: Slice) -> None:
        bar = slice.bars.get(self.spy)
        if bar:
            # Trend-following strategy using price above or below EMA.
            # If the price is above EMA, SPY is in an uptrend, and we buy it.
            if bar.close > self._ema.current.value and not self.portfolio[self.spy].is_long:
                self.set_holdings(self.spy, 1)
            elif bar.close < self._ema.current.value and not self.portfolio[self.spy].is_short:
                self.set_holdings(self.spy, -1)

    def on_end_of_day(self, symbol: Symbol) -> None:
        # Obtain the algorithm statistics interested.
        sharpe = self.statistics.total_performance.portfolio_statistics.sharpe_ratio
        b = self.statistics.total_performance.portfolio_statistics.beta
        var = self.statistics.total_performance.portfolio_statistics.value_at_risk_95

        # Plot the statistics.
        self.plot("Statistics", "Sharpe", sharpe)
        self.plot("Statistics", "Beta", b)
        self.plot("Statistics", "Value-at-Risk", var)

        # Write to save the statistics.
        self._statistics.append(f'{self.time.strftime("%Y%m%d")},{sharpe},{b},{var}')

    def on_end_of_algorithm(self) -> None:
        # Save the logged statistics for later access in the object store.
        self.object_store.save(f'{self.project_id}/algorithm-statistics', '\n'.join(self._statistics))