Stochastic RSI

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Strategy

Methodology

This strategy is backtested on daily OHLCV price data across major US equity indices and ETFs. Entry and exit signals are generated from the strategy's indicators with no lookahead bias — trades execute at the open of the bar following the signal.

Performance metrics are computed per symbol and shown individually. The parameter optimization section (where available) runs a grid search over the strategy's key parameters, optimizing for Sharpe ratio. Transaction costs and slippage are not modeled.

The signal logic and indicator code for this strategy is shown in the methodology code section below.

Methodology

Applies the Stochastic formula to RSI values rather than price, creating a faster and more sensitive oscillator. Enters long when Stochastic RSI is below 20 (oversold RSI), exits above 80.

Implementation

class StochasticRSI(Strategy):
    rsi_n = 14
    stoch_n = 14
    oversold = 20
    overbought = 80

    def init(self):
        rsi = _rsi(self.data.Close, self.rsi_n)
        stoch = _stoch_rsi(rsi, self.stoch_n)
        self.stoch_rsi = self.I(lambda: stoch, name="StochRSI")

    def next(self):
        if self.stoch_rsi[-1] < self.oversold and not self.position:
            self.buy()
        elif self.stoch_rsi[-1] > self.overbought and self.position:
            self.position.close()

Performance metrics

Total return+39.037%
Net profit$390,367
Gross profit$978,920
Gross loss$616,288
CAGR+8.933%
Annualized return+8.933%
Monthly average return+0.728%
Median monthly return+0.599%
Best month return+6.570%
Worst month return-7.070%
Rolling 1-month return+11.379%
Return per trade+0.745
Log return CAGR+8.112%
Compounded vs simple return difference-37.911%

Equity curves

Chart for symbol:

Charts & distributions

2024-06 → 2026-04 · 5-year daily data

Equity curve vs ^GSPC — buy/sell signals

Strategy equityIndex (normalized)▲ Buy▼ Sell

39 trades · green dashes = buy entries · red dashes = sell exits

Drawdown (underwater)

Rolling 1-month Sharpe

Rolling 1-month return (%)

Period return (≈ monthly)

Return distribution (bar returns)

MAE vs MFE (trades)

Rolling 12m Beta

Rolling 12m correlation

Monthly returns (run)

Performance Matrix

Total return+65.649%
Net profit$656,490
Gross profit$1,016,090
Gross loss$459,310
CAGR+16.389%
Annualized return+16.389%
Monthly average return+1.222%
Median monthly return+7.187%
Best month return+11.269%
Worst month return+0.359%
Rolling 1-month return+16.650%
Return per trade+1.306
Log return CAGR+65.267%
Compounded vs simple return difference-43.587%