In finance and trading, some technical terms can sound cryptic at best. One of these is the “standard deviation.” We often hear this phrase in discussions about market volatility, risk, and price fluctuations. But what is a standard deviation, and why do traders put so much emphasis on it? More specifically, how does measuring two standard deviations of the Average True Range (ATR) help traders put the odds in their favor when trading reversions? Let’s break it down.
Understanding Standard Deviation
In simple terms, a standard deviation is a statistical measure that tells us how far a set of numbers deviates from the average (or mean) of that set. When applied to trading, the standard deviation gauges the volatility or variability of price movement over a certain period. Higher standard deviations mean that prices are more spread out from the mean, indicating higher volatility, while lower standard deviations signify less variability and tighter clustering around the mean.
In trading, the standard deviation helps in understanding the “normal” range of price movement. Price action beyond this range can suggest either an overextended trend or an anomaly, opening up opportunities for strategic trades.
The Role of Average True Range (ATR)
The Average True Range (ATR), developed by J. Welles Wilder, is another measure traders use to assess volatility, but with a slightly different purpose. ATR measures the range within which a security’s price typically fluctuates over a given period, considering the highs and lows. Unlike the standard deviation, which looks at overall dispersion, ATR focuses more on the “true” range, capturing gaps and sharp moves that might be missed in a simple range calculation.
ATR essentially shows the level of volatility without specifying a direction. For instance, a high ATR indicates high volatility, but it doesn’t necessarily mean the price is trending up or down. By looking at ATR, traders can better gauge the intensity of market movement, which becomes critical for timing entries and exits.
Why 2 Standard Deviations?
A measurement of 2 standard deviations is a powerful tool for mean-reversion trading, particularly when combined with ATR. Here’s why:
- Statistical Probability: In a normal distribution, approximately 95% of the values fall within two standard deviations of the mean. Therefore, when a price moves beyond 2 standard deviations, it suggests an extreme move or an outlier. In other words, the price has deviated significantly from its typical range, which often signals that the move is unsustainable.
- Indicator of Overextension: By combining ATR with standard deviation, traders can measure whether a move is genuinely extended beyond its “average true range.” If a stock’s price has moved more than two standard deviations of its ATR, it may have reached an overbought or oversold level, depending on the direction. This can be a prime setup for a mean-reversion trade, where traders expect the price to revert to its average or baseline level.
- Setting Boundaries for Reversion: Using 2 standard deviations as a boundary helps traders place calculated bets on price reversals. The thinking is simple: if the price has moved so far from the mean, it’s more likely to reverse toward it rather than continue in the same extreme direction.
- Improving Risk Management: Trading reversals can be risky, as going against the trend always carries uncertainty. However, 2 standard deviations of ATR allow traders to quantify this risk. They can set stop losses or limit orders based on these extreme levels, aligning their trade management with volatility and reducing the odds of getting caught in erratic moves.
Why It Works for Reversion Trading
The concept of reversion to the mean is rooted in probability: if a price has moved far away from its average, there’s a good chance it will return. This is not always the case, as trends can override this logic, but this tendency holds in highly volatile or “mean-reverting” markets.
When the price moves beyond two standard deviations of ATR, the market will likely stretch thin in one direction. Other traders, seeing the same level of extreme deviation, might start taking profits or initiating counter-trades, reinforcing the reversion. This collective reaction can fuel the momentum toward the mean, creating a fertile ground for mean-reversion trades.
Example in Action
Imagine a stock with a 14-day ATR of $1.50. If the price moves to $3.00 (two times the ATR) away from its moving average, traders could consider this an overextended move. Whether the price has increased or decreased, they could view this deviation as a potential reversal opportunity based on the assumption that the price may revert to its average range.
Using a 2 standard deviation threshold gives traders a buffer, so they don’t react to every small fluctuation but only to substantial deviations, thereby improving their odds and reducing the likelihood of false signals.
Conclusion: Putting the Odds in Your Favor
In trading, tools that improve the probability of success are invaluable. Measuring 2 standard deviations of ATR is one such tool that can give traders an edge when trading reversions. It combines volatility and probability to signal opportunities where price action may be overextended and a reversion might be imminent.
This approach doesn’t eliminate risk but enhances the strategy’s effectiveness, as traders rely on statistical boundaries rather than subjective judgment. By waiting for the price to move two standard deviations beyond ATR, traders align themselves with patterns that are highly likely to reverse. This, in turn, allows them to approach mean-reversion trades with greater confidence and discipline, placing the odds in their favor.
To see the coursework available for trading 2SD Opening Gaps, click here.
Good Trading,
Adrian Manz