November 18, 2025

Mean Reversion Trading Strategies That Actually Work — From RSI Bounces to VWAP Pullbacks

By HorizonAI Team

Most traders chase breakouts and big trends—but markets spend a lot of time mean‑reverting.
If you can identify when price has stretched too far from “fair value,” mean reversion strategies can offer high win rates and clean entries.

In this guide you’ll learn:

What “mean reversion” really means in trading (and what “the mean” actually is)
How to use RSI, Bollinger Bands, and VWAP for mean reversion setups
When mean reversion works best (and when it fails badly)
How to start automating these ideas in Pine Script v6 on TradingView
How HorizonAI can generate, test, and optimize your mean reversion strategies for you

By the end, you’ll have several ready‑to‑test frameworks you can run on stocks, forex, indices, or crypto.

What Is Mean Reversion in Trading?

In simple terms, mean reversion assumes:

Price tends to oscillate around a “fair value” or mean—and extreme moves away from that mean are likely to revert.

The “mean” can be:

A moving average (e.g., 20 SMA/EMA)
VWAP (Volume‑Weighted Average Price)
A Bollinger Bands middle line
A range midline or 50% equilibrium (premium/discount style)

Mean reversion strategies:

Buy dips below the mean (expecting price to snap back up)
Sell rallies above the mean (expecting price to snap back down)

They tend to have:

Higher win rates (lots of small wins)
Risk of big losses if you fade a move that keeps trending

When Mean Reversion Works (and When It Doesn’t)

Mean reversion works best when:

The market is range‑bound or rotating
There’s no strong trend on higher timeframes
Volume and volatility are moderate (not in “explosive” mode)

It fails when:

Strong trends are in play (price walks away from the mean)
There’s a fundamental catalyst (news, earnings, macro events)
You hold losers without a stop (“it has to come back”)

Key takeaway:
Mean reversion is powerful when you respect trends and risk—and deadly if you average down blindly.

Strategy #1: RSI Mean Reversion Bounces

Indicator: RSI (Relative Strength Index)
Concept: Buy oversold, sell overbought in ranging conditions.

Basic Rules (Long Only)

Timeframe: 15m or 1H
Market: liquid stock, index, or FX pair
Buy when:
- RSI < 30 (oversold) and price is above a higher‑timeframe support zone
Sell (exit) when:
- RSI crosses back above 50
- Or price hits a pre‑defined profit target (e.g., 1.5–2R)

Simple RSI Mean Reversion in Pine Script

//@version=5
strategy("RSI Mean Reversion (Basic)", overlay = true,
     initial_capital = 10000, commission_type = strategy.commission.percent, commission_value = 0.01)

length  = input.int(14, "RSI Length")
oversold = input.int(30, "Oversold Level")
overbought = input.int(70, "Overbought Level")

// RSI calculation
rsiValue = ta.rsi(close, length)

// Entry: RSI oversold and price above 200 SMA (avoid counter‑trend shorts)
sma200 = ta.sma(close, 200)
longCondition = rsiValue < oversold and close > sma200

// Exit: RSI back above 50
exitCondition = ta.crossover(rsiValue, 50)

if longCondition and barstate.isconfirmed
    strategy.entry("Long", strategy.long)

if exitCondition
    strategy.close("Long")

// Plot RSI zone highlights
plot(sma200, "200 SMA", color = color.orange, linewidth = 2)

This isn’t “optimized”—it’s a starting point. You can:

Add volatility filters (ATR)
Use fixed RR exits instead of RSI only
Restrict trades to specific sessions

HorizonAI can generate more advanced versions with position sizing and risk management built in.

Strategy #2: Bollinger Band Bounces

Indicator: Bollinger Bands
Concept: Price tends to revert from the outer bands back to the middle band.

How It Works

Bollinger Bands (standard settings):

Middle band: 20‑period SMA
Upper band: middle + 2 × standard deviation
Lower band: middle − 2 × standard deviation

Mean reversion idea:

Buy when price touches or pierces the lower band and then bounces
Sell when price returns to the middle or upper band

Simple Bollinger Mean Reversion in Pine

//@version=5
strategy("Bollinger Mean Reversion", overlay = true)

length = input.int(20, "BB Length")
mult   = input.float(2.0, "Std Dev")

basis = ta.sma(close, length)
dev   = mult * ta.stdev(close, length)
upper = basis + dev
lower = basis - dev

// Entry: close below lower band (oversold)
longCondition = close < lower

// Exit: price back to middle band
exitCondition = ta.crossover(close, basis)

if longCondition and barstate.isconfirmed
    strategy.entry("Long", strategy.long)

if exitCondition
    strategy.close("Long")

plot(basis, "Middle", color = color.blue)
plot(upper, "Upper", color = color.red)
plot(lower, "Lower", color = color.green)

You can improve this by:

Adding RSI confirmation (only buy if RSI < 30)
Only taking trades in the direction of higher‑timeframe structure
Avoiding high‑volatility news periods

HorizonAI can combine these filters for you and test which combinations perform best.

Strategy #3: VWAP Pullbacks (Intraday Mean Reversion)

Indicator: VWAP (Volume‑Weighted Average Price)
Concept: Intraday, institutions use VWAP as a benchmark. Price often mean‑reverts to VWAP during range days.

Basic VWAP Mean Reversion Setup

Timeframe: 1m–5m intraday
Market: index futures, large cap stocks, liquid FX pairs
Idea:
- When price stretches far above VWAP and stalls, fade back toward VWAP
- When price stretches far below VWAP and stalls, fade up toward VWAP

Simple VWAP Pullback in Pine

//@version=5
strategy("VWAP Pullback Mean Reversion", overlay = true, initial_capital = 10000)

vwapValue = ta.vwap(close)
plot(vwapValue, "VWAP", color = color.yellow, linewidth = 2)

// Distance from VWAP in %
distancePct = (close - vwapValue) / vwapValue * 100
threshold   = input.float(0.5, "Distance Threshold (%)", minval = 0.1)

// Long idea: price below VWAP by X% and starting to base
longCondition  = distancePct < -threshold and close > open  // small bullish candle off lows
shortCondition = distancePct > threshold and close < open   // small bearish candle off highs

if longCondition and barstate.isconfirmed
    strategy.entry("Long", strategy.long)

if shortCondition and barstate.isconfirmed
    strategy.entry("Short", strategy.short)

// Simple exit: back to VWAP
exitLong  = ta.crossover(close, vwapValue)
exitShort = ta.crossunder(close, vwapValue)

if exitLong
    strategy.close("Long")

if exitShort
    strategy.close("Short")

This is intentionally basic:

No higher‑timeframe context
No volatility filter
No session limits

In practice, you’d want to:

Avoid strong trend days (price walking VWAP)
Only fade in range‑type conditions
Use session times (e.g., avoid open/close extremes)

HorizonAI can help add those conditions and check which filters improve your results.

Risk Management for Mean Reversion

Mean reversion feels safe because price “usually” comes back—until it doesn’t.

Rules to protect yourself:

Always use stop losses
- Fixed percentage or ATR‑based stops
- Never widen your stop “just this once”
Limit max position size
- Risk 1–2% per trade (never 5–10% on a single mean reversion idea)
Avoid Martingale
- Don’t double down after each loss
- Add only to winners (if at all), never to losers

You can embed these rules directly into Pine Script with:

Risk‑based position sizing
ATR‑based stops and 2–3× RR targets
Daily/weekly loss limits

HorizonAI can generate risk‑managed templates for any of the strategies above.

When to Prefer Mean Reversion vs Trend Following

You don’t have to choose forever—you can use both, depending on conditions.

Mean reversion tends to shine when:

Higher‑timeframe structure is sideways
Volatility is moderate
There are well‑defined ranges and obvious mean levels

Trend following tends to shine when:

Higher‑timeframe structure is clearly HH/HL or LH/LL
Breakouts hold instead of failing
Pullbacks to moving averages keep launching new legs

You can even use SMC ideas to filter:

If higher‑timeframe SMC structure is trending with strong BOS moves, lean more trend‑following
If structure is choppy and price keeps returning to equilibrium levels, lean more mean reversion

Use HorizonAI to Build and Test Mean Reversion Systems

Instead of hand‑coding every RSI, Bollinger, and VWAP variant, you can:

Describe your idea in plain English
Let HorizonAI generate Pine Script v6 strategies and indicators
Automatically include:
- Proper risk management (1–2% per trade)
- ATR or percentage‑based stops
- Take‑profit logic (fixed RR, partial exits, or dynamic targets)

Example prompts:

"Create a Pine Script v6 strategy that buys mean reversion bounces when RSI < 30 and price touches the lower Bollinger Band, only in sideways markets, with 1% risk and 2:1 RR."

"Build a VWAP mean reversion strategy for 5‑minute intraday charts that fades price when it moves more than 0.7% away from VWAP and exits at VWAP or 2× ATR, avoiding the first 15 minutes after the open."

"Generate a risk‑managed mean reversion system that combines Bollinger Bands and VWAP for large cap stocks, including daily loss limits and position sizing based on ATR."

Generate your mean reversion strategy with HorizonAI →

Final Thoughts

Mean reversion strategies can be high‑probability and forgiving—if you:

Define the mean clearly (SMA, VWAP, Bollinger middle, or equilibrium)
Focus on ranging environments, not strong trends
Combine signals (RSI, Bollinger, VWAP) instead of relying on one indicator alone
Use strict risk management (stops, position sizing, no Martingale)
Backtest and refine your rules instead of trusting intuition alone

Once you have a mean reversion idea you like, HorizonAI can turn it into Pine Script, help you iterate faster, and let you see quickly whether your strategy actually works across different markets and timeframes.

Questions about mean reversion filters, choice of mean, or combining this with SMC? Join our Discord community to discuss with other traders refining their systems.