Prediction Models of Financial Markets Based on Multiregression Algorithms

Abstract

The paper presents the results of simulations performed for predictive goals for the main Polish index named WIG20, using the historical quotes on several connected financial time series. The data (monthly and daily tested) used to predict WIG20 are such series as economical supply of money, level of unemployment, inflation and lagged series of the main index. In order to reach prediction goal, the author's algorithms were used. These algorithms are the hybrid of two methods -- simple rules and multiregression prediction. The results reveal some interesting features of regression models, indicating the prospect of further applications of the method, especially in Internet area. The main hypothesis is that markets have a short term memory which allows to create different strategies.

Keywords

• multivariate regression
• simple rules
• investigation strategy
• prediction
• trading systems
• algotrading