Detecting short-term mean reverting phenomenon in the stock market and OLMAR method

Abstract

In this study, we examined the “short-term Mean Reverting Phenomenon” from two aspects. First, we clarified that excess return can be obtained by using the short-term Mean Reverting Phenomenon for the On-Line Moving Average Reversion (OLMAR) method, which is a portfolio selection algorithm and reportedly exhibits high performance. Then, we examined why the method was able to maintain superiority over the long term. In addition, we proposed an evaluation index of the short-term Mean Reverting Phenomenon present in the stock price dataset and analyzed it. The OLMAR method proved that excessive return was obtained by using the characteristic property showing the mean reverting tendency, which can be selected by the moving average divergence rate. Then, we confirmed that the advantage of the OLMAR method disappears by invalidating the above property existing in the stock price dataset. In addition, we proposed an evaluation index of the Mean Reverting and analyzed the stock price dataset using it.