Introduction
Last week, one of my algos took a long trade and the day after the Nasdaq dropped more than 2-3%. However after two days, this big open drawdown had turned from a pretty big loss to a profit, this wasn't magic even though it almost felt like it, this was a concept called mean reversion.
What is a mean reversion strategy?
Mean reversion is a key concept in trading that assumes asset prices will eventually return to the long-term mean or average level. This principle can be particularly useful in spotting trading opportunities in markets that have moved excessively away from their historical averages. A mean reversion strategy is simply a strategy built on indicators and price action to capitalize on these moves. If you want to create your own strategy from scratch you will probably want to look into our post about how to create a winning mean reversion strategy.
If you want to get a backtested strategy we'll explore three of our best mean reversion strategies below that can help you capitalize on these market moves. We will compare the performance of these three strategies by looking at total trades, win rate, risk/reward and time in the market but the main ratio we'll use to measure risk-adjusted gain is the MAR Ratio, which is the CAGR divided by the MAX DD.
Strategy 1: 3 Down, 3 Up on Nasdaq
Overview of the Strategy
Nasdaq rarely goes down too many days in a row before bouncing back for a few days. To increase our chances of the downward momentum being exhausted, we add an entry condition that requires a bar with a big body.
Result
Backtest: 1986-2024
Timeframe: Daily
Total trades: 283
Win rate: 75%
Risk/Reward: 1.2
Average time in the market: 10 days, 6 hours
MAR Ratio: 0.40
Indicators
This strategy uses purely price action, there are very few rules and therefore also space for improvement for this strategy, feel free to test new conditions. We have a list for both mean reversion entries and exits.
Entry Conditions:
Three bearish days in a row: close < open
At least one of the days must have a body bigger than 70% of the size of its range
Exit Conditions:
Three bullish days in a row: close > open
Strategy 2: Oversold Intraday on DAX
Overview of the Strategy
Traders often use the DAX 40 for intraday mean-reversion strategies. This one goes long on intraday weakness, defined by two classic indicators. It doesn't have any trend filter, but has an upper limit for volatility, to avoid catching knives that fall too aggressively.
Result
Backtest: 1990-2024
Timeframe: 1 Hour
Total trades: 2 162
Win rate: 42,2%
Risk/Reward: 1.75
Average time in the market: 16 hours, 26 minutes
MAR Ratio: 0.47
Indicators
This strategy uses three indicators, Internal Bar Strength (IBS), Relative Strength Index (RSI) and the Bollinger Band.
Entry Conditions:
IBS is under 0.05
RSI2 is less than 50
50 Period Bollinger Bandwidth is less than 0.06
Exit Conditions:
Low is above the last bar's close
Strategy 3: Linear Regression Hook on SPX
Overview of the Strategy
The Linear Regression Slope is often used for trend detection, but can also work well to identify reversal points. This strategy uses a "hook" in the short-term Linear Regression Slope for entries
Result
Backtest: 1990-2024
Timeframe: Daily
Total trades: 298
Win rate: 74,2%
Risk/Reward: 0.7
Average time in the market: 7 days, 9 hours
MAR Ratio: 0.22
Indicators
This strategy uses a combination of price action and two indicators, Linear Regression Slope and Average True Range (ATR).
Entry Conditions:
Close is less than open.
The 3-period Linear Regression Slope is higher than yesterday.
Yesterday's 3-period Linear Regression Slope is lower than the day before.
The day of the week is not a Friday.
Exit Conditions:
The trade is exited when:
Close is above the upper custom-made ATR band (take profit).
Close is below the lower custom-made ATR band (stop loss).
Additional Links
(Code for each strategy is found via these links)
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