Strategy library · Mean reversion
RSI mean reversion: buying oversold dips in stocks still trending up
By Anoop Thomas · Last updated
In short
An RSI mean reversion strategy buys when the Relative Strength Index shows a stock is short-term oversold and sells when price bounces back toward its recent average. The textbook trigger is RSI(14) below 30; for short swing trades many systematic traders use a 2- or 3-period RSI below 10. Most versions only buy stocks above their 200-day average, so they buy dips in uptrends rather than falling stocks.
Trend systems buy strength. RSI mean reversion buys weakness, but only in stocks whose longer trend is still up. The idea is that a few sharp down days in a healthy stock are often noise, and price snaps back toward its recent average. When that idea is wrong, you are holding a stock that is falling for a reason.
It suits swing traders who can hold for a few days and are comfortable buying when the chart looks ugly. It doesn’t suit anyone who needs a high reward-to-risk on every trade: the target is a bounce, the stop has to be wide, and the arithmetic in the example shows what that means.
The rules, step by step
A sensible starting template, not a proven system. Change any number, then test it before trusting it.
- 1
Setup
Daily candles on a fixed list of liquid stocks (Nifty 100, say). Trade only stocks closing above their 200-day simple moving average.
- 2
Entry
Buy at the next open after RSI(2) closes below 10. (Textbook variant: RSI(14) below 30, which fires far less often in stocks above their 200-day.)
- 3
Exit
Sell at the next open after the stock closes above its 5-day simple moving average.
- 4
Stop and time stop
Exit if the close falls 3 × ATR(14) below entry, or after 10 trading days, whichever comes first.
- 5
Position sizing
Risk 1% of capital per trade based on the 3 × ATR stop. At most 5 open positions, and no more than two from the same sector.
- 6
Filters
Skip a stock with quarterly results due inside the holding window. Take no new entries while Nifty itself is below its 200-day average.
Say it in plain English
Paste this into INDfolio’s AI strategy builder and it becomes a backtestable strategy.
On daily candles for Nifty 100 stocks that close above their 200-day SMA, buy at the next open when the 2-period RSI closes below 10. Sell at the next open after the stock closes above its 5-day SMA. Exit if the close falls 3 times the 14-day ATR below my entry, or after 10 trading days. Risk 1% of capital per trade with at most 5 positions, and take no new trades when Nifty is below its 200-day SMA.Backtest this free
Free plan · no card · NSE data included
One hypothetical RSI trade, and why the reward is smaller than the risk
A stock above its 200-day average falls four days running and RSI(2) closes at 6. The next open is ₹600, ATR(14) is ₹15 and the 5-day average sits around ₹622 (all hypothetical). Capital is ₹5 lakh at 1% risk.
| Item | Value | Working |
|---|---|---|
| Risk per trade | ₹5,000 | 1% of ₹5,00,000 |
| Stop distance | ₹45 | 3 × ATR of ₹15 |
| Entry / stop | ₹600 / ₹555 | Entry minus stop distance |
| Quantity | 111 shares | 5,000 ÷ 45 = 111.1, rounded down |
| Position value | ₹66,600 | 111 × 600 |
| Gain if it reaches the 5-day average | ₹2,442 gross | 111 × ₹22 |
| Loss if the stop is hit | ₹4,995 gross | 111 × ₹45 |
| Delivery charges, round trip | about ₹166 | STT 0.1% on each side (about ₹136), stamp duty, exchange charges, GST, DP charge |
Hypothetical prices for arithmetic only, not a backtest. Delivery charges at NSE rates as of September 2026 with a ₹15.34 DP charge; check your broker in the brokerage calculator.
RSI(14) at 30, or RSI(2) at 10?
The 30/70 levels belong to the standard 14-period RSI, and they are fine for reading a chart. As a mean-reversion trigger in strong stocks they have a practical problem: a stock above its 200-day average doesn’t often fall far enough for RSI(14) to reach 30, so you get very few trades. Short lookbacks like RSI(2) or RSI(3) react to a few days of selling, which is exactly the dip this strategy wants to buy.
The trade-off is that a short RSI fires more often and on smaller moves, so costs per trade matter more and any edge per trade is thinner. Test both. I’d expect the short version to be the more useful one for swing trading, but that is a hypothesis for your data, not a promise.
The arithmetic that makes or breaks it
Look at the example again: risk ₹4,995 to make ₹2,442. That is a reward-to-risk of about 0.5 to 1, which means about two trades in three have to reach the target just to break even before costs. Mean reversion systems often have that shape. It is fine, provided your test shows the hit rate is real and not an artefact of a calm sample.
Tight stops don’t fix it. Buying a stock that is falling and stopping out ₹10 lower often means selling near the low. That’s why the rules use a wide ATR stop plus a time stop: if the bounce hasn’t come in 10 days, the premise is gone.
Where it fails
Falling knives. The 200-day filter keeps you out of long downtrends, but it can’t see a stock dropping on bad results or a governance problem, and RSI looks “oversold” all the way down. That’s why the rules skip results windows. Market-wide selloffs are the other case: in a broad fall every stock on your list turns oversold at once, and five positions become one bet on the market. The sector cap and the Nifty filter limit this without removing it.
Costs, tax and testing on NSE data
Delivery costs are the main drag because each trade is small and short. In the example, about ₹166 of charges is nearly 7% of the target gain. Tax comes on top: gains on shares held under a year are short-term, and frequent trading can be treated differently again, so talk to a CA about your own case.
For the test you need daily data for the whole universe over several years, using the index members as they were at each date if your tool allows it, because today’s Nifty 100 has already dropped the stocks that kept falling. Ask any platform, including us, how it handles that. Vary the RSI period (2–5), the threshold (5–20), the exit average (3–10 days) and the time stop. Read the result by year; a strategy that made all its money in one recovery rally is a recovery-rally strategy.
INDfolio’s backtesting runs daily NSE equity tests with delivery costs deducted (we build it, so weigh that accordingly).
Educational content, not investment advice. The rules and numbers on this page are an illustrative template, not a backtest result or a recommendation. Derivatives carry a high risk of loss — SEBI’s own studies of F&O traders found that the large majority of individuals lose money. We build INDfolio AI, so weigh our view accordingly.
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