Development of modified Geometric Brownian Motion models by using stock price data and basic statistics Original Research Article

We employ a classical model building process to develop modified stochastic linear models. In this work, by utilizing the stock price data, we examine the correctness of the existing Geometric Brownian Motion model under standard statistical tests. Then we demonstrate the development of the modified linear models under different data partitionings, with or without jumps. Empirical comparison between the constructed models and GBM models is outlined via a Monte Carlo technique.