Parameter Behavioral Finance Model Of Investor Groups Based On Statistical Approaches

This paper establishes the parameter behavioral finance model of investor groups. There are three key research steps: Firstly, using statistics and investors' investment psychology set up 15 parameters, to describe investor group behavior. Secondly, the genetic algorithm is used to optimize the value of parameters according to the historical turnover data, and optimal parameter values of the stock are given. Thirdly, the simulation method is used to simulate the behavior of different investment groups when the stock market fluctuates. Also, this method can predict the future trend of the stock market based on the simulation data. According to our tests' results, we found this model can be used to explain the fluctuation of stocks. However, it is still not stable and accurate to forecast future stock prices, thus further research is needed.(c) 2021 Board of Trustees of the University of Illinois. Published by Elsevier Inc. All rights reserved.