A Statistic Method for the Prediction of the Succession of Bear and Bull Stock Market

Abstract

In this paper, we define an innovative method for predicting the stochastic behavior of the Bull and Bear periods of the stock market. The direct study of the prediction of possible Bull and Bear markets is a different and new approach about the analysis of stock markets. Our work is based on the collection of 40 years of data from the Italian stock market. The proposed solution is defined using the statistical analysis of the Bear and Bull Stock markets and it includes a criterion for statistically generating the most probable values of the next Bear and Bull markets, as well as especially the lengths of the time intervals corresponding to these market situations. We defined a new system for a stock market price trend prediction, where the trend of the succession of Bull and Bear markets can be described by a probability density function given by a Gaussian distribution. Furthermore, we considered the inverses of the relative time intervals as a measure of the speed with which the phenomenon of the Bear market (or, equivalently, the Bull market) develops in that interval of time and therefore, ultimately, it can represent a first statistical weight of the single percentage variation. Again, the time intervals of the individual Bear and Bull market periods are considered, calculated from 01/01/1973. This is based on the hypothesis that a secondary factor of probability is the temporal distance of the event that has already occurred. In this paper, we conduct a comprehensive evaluation of more frequently used statistical methods for evaluating Stock markets, highlighting the novelty of the described method. Simulation results show the ability of the method to define a statistical prediction of the next Bull and Bear markets.