Modeling the momentum effect in financial stock markets

This research has two objectives: (1) to model the momentum effect, (2) to propose a portfolio selection algorithm MESPSA that can use the momentum effect to obtain excess profit. The momentum effect is a phenomenon in which stocks that rise (decline) tend to continue to rise (decline), and momentum effect is a phenomenon often seen in the stock market. However, because existing research does not separate momentum effects from stock price fluctuations it is not always possible to obtain excess return when working with an unknown data set that contains a momentum effect. In this research, we define a new External Force Momentum Effect (EFME) model based on bias in stock price rises (declines). We prepare an artificial data set that contained this momentum effect and construct a portfolio with the proposed algorithm. The relationship between the EFME model and excess return is then analyzed to verify that excess profit can be obtained. Also, we confirm that the proposed algorithm for the actual stock price data set yields excess profits. © 2018, Japanese Society for Artificial Intelligence. All rights reserved.