RSI(14): what it was followed by

What a RSI(14) extreme was historically followed by, measured across our stock coverage.

What a RSI(14) extreme was historically followed by, measured across our stock coverage.

How to read this. These figures are measured only on instruments currently in our coverage — a set of companies that survived. Signals that appear to have 'worked' on the downside are conditioned on these names having recovered; a company that fell and never came back would not be here to measure. Read every number below as a property of this surviving sample, not a universal rule, and never as advice.

All figures are ‘excess’ returns — measured relative to each instrument’s own historical drift, not relative to the market. This is not alpha and not a market-beating claim; it isolates the signal from the instrument’s background trend. Measured from the first day each signal appeared (not its most extreme point), so it reflects what was knowable in real time.

Overbought / high extreme

Across 4149 past episodes where a stock was overbought on this signal, the 4138 with a complete 20-session forward window lagged a stock’s own trailing drift by 0.48 percentage points on average (45% of those 4138 beat drift).

the stock forward excess return vs its own drift after overbought RSI(14) readings, by horizon.
horizonexcess vs own driftbeat-drift rateepisodes with complete horizon
1 session-0.05%44%4149
5 sessions-0.36%45%4148
20 sessions-0.48%45%4138

Oversold / low extreme

Across 2523 past episodes where a stock was oversold on this signal, the 2516 with a complete 20-session forward window beat a stock’s own trailing drift by 0.77 percentage points on average (53% of those 2516 beat drift).

the stock forward excess return vs its own drift after oversold RSI(14) readings, by horizon.
horizonexcess vs own driftbeat-drift rateepisodes with complete horizon
1 session+0.26%51%2523
5 sessions+0.74%54%2521
20 sessions+0.77%53%2516

By instrument

Each instrument’s own history on this signal (where it has enough episodes to characterize):