Stock Price Forecasting Using the Jumping Frog Algorithm between Two types of Stock Market Trader Personality.

Abstract

The main mechanism of the stock market is based on the transaction, and buyers and sellers enter into this market with their price offerings, and capital market activists believe that the purpose of creating this platform is to facilitate people's transactions. In general, people active in the capital market can be divided into 2 personality types^[1], including investors and traders who have their own special characteristics, and it cannot consider a general recommendation for all who act in this market because each person's personality is unique to him and among two personality types of trader and investor, there are successful people because today, many people are interested in the trading job, and involved in several decisions in various markets on a daily basis, and any suggestion that can improve the accuracy of the decision or reduce the decision-making time is attractive and valuable to them. One of the markets that is booming today, and the advantages of decision support systems are very evident in it, is money and capital markets, including the stock market. The actors of this market buy and sell the shares of companies in that market in which, by accepting the future risk of shares, they bring profit or loss for themselves. In this study, after gathering data from the stock-exchange database, the main characteristics of data were extracted using the wavelet transform method and applied as inputs for prediction to the Multilayer Perceptron Neural Network (MLP-NN) trained by the frog leaping algorithm, and the results were compared with the Basic-Radial Neural Network (BR-NN) trained with frog leaping algorithms.