Trade that emphasizes FX: mean reversal effect

Today I would like to describe the FX topics that receive a lot of questions.

I believe you can invest in a way that feels right to you, but when asked what you should do, I think it can only be explained in a logical manner.

■ What is Mean Reversion

One of them is a strategy that uses mean reversion.

Mean reversion is based on the statistical “mean reversion theory.” This theory holds that even if data fluctuates randomly, it tends to return to a certain long-term average.

In trading, you enter at points where the price temporarily deviates from the average, aiming to profit as the price reverts back to the mean.

1. Price Reversion:

Mean reversion exploits the phenomenon of temporary surges or declines in prices. Prices tend to return to the long-term average.

2. Effective in markets without a clear trend:

It is particularly effective when there is no obvious trend in the market or when the market reverses direction.

3. Selection of entry points:

When using mean reversion, you enter at points where the price deviates from the average.

■ Points to note

・Mean reversion is a probabilistic method and does not guarantee 100% success.

・It is necessary to properly judge the extent and speed of the rebound.

・It is necessary to explore methods to remove noise effects.

Mean reversion, by understanding the characteristics of the market and identifying appropriate entry points, is a valid method to pursue profits in FX trading. I recommend that traders manage risk properly while utilizing mean reversion in their trading.

If you are interested, we have published a detailed version as a product, so please consider it if you are interested.

■ The Theoretical Background of Mean Reversion

Mean reversion uses phenomena where prices and volatility temporarily deviate from the average. It is an intuitive phenomenon observed in financial instruments such as stocks, currencies, and commodity futures, and in the medium to long term it tends to return to an average level. The market shows a certain degree of autocorrelation and is not completely random.

If mean reversion holds, the greater the deviation from the average level, the larger the subsequent rebound, and a contrarian investment approach is known as “return reversal.”

■ About the Ornstein-Uhlenbeck Process

To quantitatively understand mean reversion, the Ornstein–Uhlenbeck process (OU Process) is important.

The OU Process is a stationary Gaussian Markov process with a Gaussian property that oscillates around the mean and a Markov property that depends on the previous state, and on the time axis, it has a tendency to revert to the mean, hence it is also called a mean-reversion process.

Concretely, the OU Process is defined by the following stochastic differential equation:

[ X_t = μ + θ(X_t - μ)dt + σ dW_t ]

Here, (X_t) is a random variable representing asset price or a physical observation, and (W_t) is a Wiener process representing white noise.

μ is the mean of (X_t), θ is the speed at which (X_t) reverts to μ, and σ is the volatility of (X_t). This equation is also used in financial engineering as a model for interest rates.

By estimating the OU Process parameters, you can calculate future expected values and confidence intervals. Parameter estimation uses methods such as Maximum Likelihood Estimation, and by estimating OU parameters from daily stock price or FX data and testing the reversal effect, you can understand the theoretical background of mean reversion.

■ Summary

There are various discussions about indicators and technical trading, but ultimately it starts with a logical basis. First understand the reasoning, and then decide what to apply.

In practical terms, you can set up mean reversion with several indicators, and I personally have organized a strategy into a product that is for sale, so please feel free to use it if you are interested.