Abstract
Predicting stock price movement is generally accepted to be challenging such that until today it is continuously being attempted. This paper attempts to address the problem of stock price movement using continuous time models. Specifically, the paper provides comparative analysis of continuous time models—General Brownian Motion (GBM) and Variance Gamma (VG) in predicting the direction and accurate stock price levels using Monte Carlo methods—Quasi Monte Carlo (QMC) and Least Squares Monte Carlo (LSMC). The hit ratio and mean-absolute percentage error (MAPE) were used to evaluate the models. The empirical tests suggest that either the GBM model or VG model in any Monte Carlo method can be used to predict the direction of stock price movement. In terms of predicting the stock price values, the empirical findings suggest that the GBM model performs well in the QMC method and the VG model performs well in the LSMC method.
Highlights
In this paper we deal with the problem of prediction of stock price movement that has been there over years
This paper addressed the problem of stock price movement using continuous time models
For each performance evaluation metric, we made a comparative analysis of the models—Geometric Brownian Motion (GBM) and Variance Gamma (VG) under each simulation method—Quasi-Monte Carlo (QMC) or Least Squares Monte Carlo (LSMC)
Summary
In this paper we deal with the problem of prediction of stock price movement (increase or decrease) that has been there over years. (2015) Prediction of Stock Price Movement Using Continuous Time Models. This paper is an attempt to predict stock price movement using continuous time models. Instead of making a comparison between classification models, which predict direction based on probability, and level estimation models, which forecast the accurate price level, we resort to using continuous time models in Monte Carlo framework to achieve both objectives of predicting the direction of stock price and accurate stock price level. The major contributions of this work are comparative analysis of continuous time models to predict the direction and accurate price levels of stocks in the Monte Carlo framework. The interest to this work is the comparative analysis of continuous time models—GBM model and VG model in stock price movement.
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