Mean reversion

RSI Oversold Overbought

Buys when the 14-bar RSI drops below the 30 oversold level and holds until it rises above the 70 overbought level.

Total score 30/ 100 rank 31 / 42 · mean reversion 03 / 9

How It Works

  1. Compute the 14-bar RSI of the close.
  2. Buy when the RSI drops below 30 — selling has been so one-sided the market is called oversold.
  3. Hold until the RSI rises above 70 — buying has become just as one-sided (overbought) — then sell into that strength.

Worked example. After a two-week slide the 14-bar RSI prints 27 — under the 30 oversold line — and the strategy buys. The recovery carries the RSI up through 70, where the position is sold.

The Math Behind The Indicators

Everything runs on closing prices of the traded timeframe: P is a close, Pt today's close, and N counts bars — one bar is one candle of that timeframe, so 20 bars on a 1h chart is 20 hours.

Relative Strength Index (RSI)
A 0–100 gauge of how one-sided recent moves have been. It compares G, the average size of up-moves, to L, the average size of down-moves, over the last N bars (using Wilder's smoothed averages): near 100 almost every recent bar went up, near 0 almost every bar went down, 50 is balanced.
RSIN = 100 − 1001 + G/L
Example: If over the last 14 bars up-moves averaged 2.0 and down-moves averaged 1.0, then G/L = 2 and RSI = 100 − 100 / 3 ≈ 67. Readings below 30 are called oversold, above 70 overbought.

Example Chart

Example Chart

The Metrics

Metric Calculation What it shows
Price Change % change = Plast − P0P0 × 100 The traded market's own close against its first close over the same window, as a percentage. What the market did while the rule was running — the benchmark every other row here is read against. A rule that made 40% in a market that made 120% lost to doing nothing.
Trades N = count(closed positions) How many positions the rule opened and closed over the window. The sample behind every other figure, and what the fees are charged on. Two rules with the same return are not the same rule if one took nine trades and the other took nine hundred.
Win Rate % W%n = winsnn × 100 Of the first n trades, how many closed above the cash they opened with after fees. Plotted trade by trade, so the line is the rate so far rather than a final figure. How often the rule is right, which is not how much it makes. A rule can win a third of its trades and still lead, if the third it wins pays for the two it loses.
Cumulative P&L % PnL%n = n∑i=1(fi − 1) × 100 Each trade's percentage result added up, net of fees. A sum rather than a compounding, so a 10% gain and a 10% loss cancel. What the rule returned per trade, with position size taken out of it. It answers whether the edge is in the trades themselves, where the equity curve answers what the account did with them.
Equity En = E0 n∏i=1fi The account compounded through every trade — the whole balance goes into the next position. Drawn net of fees as a solid line and gross of them as a dotted one. The account itself, which is the only figure a reader actually ends up with. The gap between the two lines is what the fees took, and it widens with every trade rather than staying a fixed share.
Cumulative Fees Fn = n∑i=1(Ci φ + Xi φ) Fee charged on the way into each position and again on the way out, at rate phi, on the capital actually committed — so the bill grows with the account as well as with the trade count. The cost of trading, in the account's own units. It is the one line here that only ever rises, and the one a rule cannot trade its way out of.
Rolling Sharpe Sharpet = mean(rdaily)sd(rdaily) × √365 Mean daily return over its deviation, annualized on a 365-day year because crypto has no weekend. Taken on the account marked to market every bar — open positions included, not just closed ones — and read off at each trade's exit. Return per unit of the swing it took to get it. It is the heaviest weight in the composite score, because an account that doubled calmly and one that doubled violently are not the same result.

Real Data

29/ 100Composite score

Metrics Per Trade

Final Metrics

Scores

Resampled Data

30/ 100Composite score

Metrics Per Trade

Final Metrics

Scores