Cesar Alvarez spent nine years working alongside Larry Connors, where he learned the foundations of mean reversion trading and helped popularise the 2-period RSI as a practical tool for short-term entries. After leaving Connors Research, he started his own blog and trading practice, focusing primarily on quantitative research into mean reversion strategies for stocks and ETFs.
Mean reversion holds a specific appeal for Cesar: the typical holding period of three to seven days, the win rate in the mid-60s, and the psychological fortitude it demands. In this episode – part one of a multi-part series – he walks through his complete framework for building mean reversion strategies, from defining goals to measuring pullbacks to managing the hardest part of the approach: placing orders into charts that look terrible.
Watch the full episode below, then read on for the complete breakdown.
The Characteristics of Mean Reversion Trading
Mean reversion is based on the observation that markets tend to oscillate around a central value rather than trend continuously. After a short sharp sell-off, many stocks bounce. The challenge is that mean reversion entries look awful on a chart – the stock is typically falling, and the chart suggests it will keep falling.
Cesar’s response to this is deliberate: he does not look at the charts 95% of the time before placing orders.
“If you look at these charts, you’re going to ask why you want to buy this stock. It’s clearly in a downtrend. It’s not going to bounce. And often those are actually the best ones.”
The practical numbers that make mean reversion attractive: win rates typically in the 60-65% range, average hold times of three to seven days, and occasional outsized winners that come very quickly. A 10% gain in a single day on a mean reversion bounce is not unusual. The tradeoff is that sometimes the stock does not bounce – and if you are trading a large enough universe, you will eventually experience a stock that drops 50% overnight.
The Complete Framework – Eight Steps
Cesar outlines a step-by-step framework for building any mean reversion strategy. The steps mirror good strategy design generally but have specific considerations for the mean reversion context:
- Define your goals: CAGR targets, maximum drawdown tolerance, equity curve smoothness preferences
- Select your trading universe: S&P 500, Russell 3000, or a broader universe of liquid stocks
- Measure mean reversion: choose your indicators to identify when a stock has pulled back sufficiently
- Add filters: market regime filters, additional conditions to reduce false signals
- Rank signals: when more setups occur than positions available, how do you prioritise
- Position sizing: how much to allocate per position
- Entry execution: how to get into the position after a signal fires
- Exit rules: the most important element of the whole system
Measuring Mean Reversion – Five Practical Methods
The core of the framework is measuring whether a stock has pulled back far enough to justify a mean reversion entry. Cesar describes five distinct approaches, all of which work:
2-period RSI: The indicator Cesar and Larry Connors popularised over a decade ago. Still works well despite being widely known. A 2-period RSI below 10 or 5 signals extreme short-term oversold conditions.
Bollinger Band Percent B: Measures where the close is relative to the Bollinger Band range. A value below -0.8 for two or three consecutive days signals deep oversold conditions. Cesar uses shorter periods (5 or 10) and tighter standard deviations (1 to 1.5) rather than the standard 20-period, 2 standard deviation settings.
Percent below moving average: If the close is more than 4% below the 5-day moving average for two or three consecutive days, that is a potential mean reversion setup. Simple, robust, and does not require accounting for individual stock volatility to work.
Rate of change: How much has the stock dropped over the last three to five days? A 15% decline over five days is a strong enough signal on its own to flag as a potential mean reversion candidate.
Days down / consecutive down closes: Count the number of consecutive down closes. Five days down in a row has a strong tendency to mean revert. Cesar notes this is the simplest measure, and it is also one of the most effective. You can cap it – if a stock has been down more than 10 consecutive days, it may be in a structural downtrend rather than a temporary pullback.
Multi-day closing range: Calculate the range from highest high to lowest low over five or ten days. If the most recent close is in the bottom 10% of that range, the stock is at a potential mean reversion entry point.
An Important Counterintuitive Finding on Equity Curves
Cesar shares a finding that runs counter to conventional strategy development wisdom. Most researchers and traders optimise for smooth equity curves – strategies that produce consistent, predictable returns with low variance. Cesar has been deliberately moving away from this.
His reasoning: smooth equity curves attract other traders. If your strategy produces a smooth equity curve, it is likely because many other people have already found and are trading the same edge. That popularity erodes the edge over time.
“Everybody’s looking for smooth equity curves, and therefore any strategy you find with a smooth equity curve, everybody else is going to find too. I’ve been looking at strategies that don’t have smooth equity curves because they’re likely not followed as much.”
He has only been applying this approach for about a year at the time of this interview, but early results suggest these strategies are more robust in live trading than strategies optimised for smoothness.
Universe Selection – Small Cap vs Large Cap Mean Reversion
The choice of universe matters significantly for mean reversion because it affects the size of bounces. S&P 500 stocks are more stable – a mean reversion trade on a large cap stock might produce 2-5%. A smaller, more volatile stock might bounce 10-15% or more from the same type of oversold condition.
The tradeoff: the larger the potential bounce, the larger the potential continued decline. Trading smaller, less liquid stocks means accepting the risk that a “mean reversion” candidate is actually a stock in fundamental distress. Cesar recommends that traders starting with mean reversion strategies use a larger cap universe first, accept the smaller wins, and develop conviction in the approach before moving to more volatile names.
Never Wait for Confirmation
One of Cesar’s most emphatic practical points: do not wait for a bounce confirmation before entering a mean reversion trade. The moment you add a confirmation step – waiting for a higher open, an up day, a candle that signals reversal – you destroy the edge.
“Mean reversion – waiting for a confirmation will quickly eat up your edge. I discovered this years ago. I thought, let me wait for the bounce to start. What happens is you lose a lot waiting for that confirmation.”
The edge in mean reversion is precisely in entering at the point where the stock looks worst. That is when the bounce potential is highest. Waiting for confirmation means entering after the best prices have already passed.
Get the show notes & transcript
Related episodes
- How to Build Mean Reversion Trading Strategies with Stefan Friedrichowski
- Low-Effort Trading Strategies with Cesar Alvarez
- Combining Algos Using State-Based Market Design with Richard Metzger
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