Modeling the Momentum Effect in Financial Stock Markets Toward New Portfolio Rebalance Algorithm

Abstract

This research has two objectives: (1) to model and analyze the momentum effect, (2) to propose a portfolio reconstruction algorithm that can use the momentum effect to obtain excess profit. The momentum effect tends to be present in the stock market, and describes the phenomenon whereby rising (declining) stocks tend to continue to rise (decline). 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 prepared an artificial data set that contained this momentum effect and constructed 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. Additionally, we confirmed that the proposed method can obtain higher excess return than the existing method when applied to artificial and real stock data sets.