Triangulation between Bernoulli Distribution and Laplacian Autoregressive Model to Predict Probability of Increase in Stock Price

Abstract

Stocks are one of the aspects that affect the economy in the world. In the stock market, the price of a stock changes every time. Investors who are able to predict the increase in stock prices will tend to get profit, but investors who are unable to predict the increase in stock prices will tend to experience losses. This study aims to find statistical models and use them to predict the probability of an increase in the price of a stock in the stock market. The method used in this study is a literature study regarding stochastic models and selected suitable stochastic models. This study finds stochastic models and uses them to predict the probability of an increase in stock prices. The novelty in this research lies in the stochastic model triangulation. The increase in stock prices is predicted using two stochastic models, namely: Bernoulli and autoregressive. The decision on stock prediction is determined by the results of the triangulation of the two methods. The proposed method in this study has the advantage that decision making is based on more than one stochastic model. The results of this study can be applied to the financial sector, especially in the stock market.