Stochastic RSI strategy — on every asset
Stochastic RSI applies the Stochastic formula to RSI instead of to price: it shows where the current RSI sits within its own recent high-low range, on a 0 to 1 scale (below 0.2 'oversold', above 0.8 'overbought'). Because it stretches an already-smoothed indicator, it is faster and noisier than plain RSI - it hits the extremes more often and whipsaws more. Buy when it is oversold, betting on a bounce, and exit when it becomes overbought. Like the RSI Reversion rule already in this library, it is a mean-reversion oscillator that fights the trend, so a strong move can run it over (a falling knife); it reads how stretched momentum is, not a prediction of a turn.
An illustration of where the rule triggers — not real prices, and not a signal to act. The dashed forks mean the outcome is undetermined; whether the rule made money is what a backtest measures.
When price is stretched from its mean — By construction it fades a stretched move — it enters oversold and exits overbought; it is faster and noisier than plain RSI, so it re-decides more often.
In a sustained one-way move — Because it stretches an already-smoothed indicator it whipsaws more and hits the extremes often; a sustained one-way move runs it over — it fights the trend and can buy a falling knife.
Whether that behaviour produced excess return on your asset over your window is exactly what your backtest measures — we publish no profit claims.
How it works — step by step
- • Entry — Go long when it reads oversold (below ~0.2), betting on a bounce.
- • Exit — Go flat when it reads overbought (above ~0.8).
- • Fills, scoring & data — Every backtest fills at the next real open and scores on the real price against a real buy-and-hold, never a smoothed or derived series; a NaN warm-up sits flat rather than fabricating a reading.
Most of these did not beat buy & hold — but a real few did, and finding out which is the whole point. This one strategy was tested on 91 different assets. With that many attempts, some will beat buy & hold by chance alone — which is why these are listed neutrally, not ranked by which ones came out ahead. To see whether any single result survives scrutiny, run the out-of-sample, walk-forward and multiple-testing checks on its backtest.
Of the 91 with enough data to judge, 21 beat buy & hold. Results are simulated backtests over the last ~5 years (less for younger assets), shown whole — losses included — not live or future performance. These are famous names that still trade today. Names that delisted, went bankrupt or were wound down aren't in the set (survivorship bias) — and that history isn't available from the free public data this tool runs on — so this rate isn't a representative base rate for every stock or ETF that has ever traded.
Listed in a neutral catalog order — not ranked by performance. Combinations we can't judge yet — too little data — are grouped separately below.
Here, “beat” means only a higher total return than buy & hold over this one past window — not risk-adjusted, not luck-checked. The out-of-sample, walk-forward and luck checks live on each individual backtest.
Past performance is not a reliable indicator of future results. This is an educational, analytical tool — not investment advice, and not a recommendation to buy or sell anything. You make all decisions and execute on your own broker.
HYPOTHETICAL OR SIMULATED PERFORMANCE RESULTS HAVE CERTAIN LIMITATIONS. UNLIKE AN ACTUAL PERFORMANCE RECORD, SIMULATED RESULTS DO NOT REPRESENT ACTUAL TRADING. ALSO, SINCE THE TRADES HAVE NOT BEEN EXECUTED, THE RESULTS MAY HAVE UNDER- OR OVER-COMPENSATED FOR THE IMPACT, IF ANY, OF CERTAIN MARKET FACTORS, SUCH AS LACK OF LIQUIDITY. SIMULATED TRADING PROGRAMS IN GENERAL ARE ALSO SUBJECT TO THE FACT THAT THEY ARE DESIGNED WITH THE BENEFIT OF HINDSIGHT. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THOSE SHOWN.
On the 91 assets with enough data to judge, the same rule swung from +90.4 pts vs buy & hold on Meta to -902 pts on Micron Technology. The typical (median) result was -28.1 pts — and even across these runs, the deepest drawdown you'd have sat through was -97% on Avalanche.
That range is the whole point: one rule is not universally good or bad — it depends entirely on the asset, and with 91 tried, some beat by chance. Shown to reveal the variation, not to pick one to trade.
Stochastic RSI on stocks
Stochastic RSI on etfs
Stochastic RSI on commodities
Stochastic RSI on crypto
Backtesting is one stage of preparing to trade, not the finish line. The full discipline runs five: Understand, Test, Stress-test, Forward-test, then Decide — eyes open. The rare idea that survives all five is the one worth taking into the market with your eyes open — and every stage before it is a place to stop, for free, as most ideas wash out in the first three. Finding that rare idea before you risk a cent is the whole point.