Mean Reversion Strategy

Numerical Method’s mean reversion strategy is loosely inspired by the following papers.

• ​Optimal Pairs Trading: A Stochastic Control Approach. Mudchanatongsuk, S., Primbs, J.A., Wong, W. Dept. of Manage. Sci. & Eng., Stanford Univ., Stanford, CA.
• ​Pairs trading. Elliott, van der Hoek, and Malcolm. Quantitative Finance, 2005

Very briefly, a good mean reversion strategy depends on its ability to:

1. estimate the current true/hidden price (the mean) so that we can estimate the disequilibrium
2. manage the risk by keep the “optimal” position based on the disequilibrium

Synthetic Assets

In practice, most single assets do not naturally exhibit mean reversion behavior (except maybe over a short horizon). We would thus have to create synthetic assets that mean revert. For example,

$Z = X - \beta * Y$

One good starting point is cointegration. However, the cointegration criterion, namely stationarity, is a very restrictive concept. It is very difficult to achieve practically. For the sake of making money, this is also unnecessary. What we really need is a concept of “close enough to stationarity so that we can make money”.