Jump Diffusion Modeling of Stock Prices on Ghana Stock Exchange

Abstract

The behaviour of stocks on the Ghana stock exchange is examined to show that stock prices on the exchange are subject to sudden price changes. It is shown that such unexpected events and uncertainties affecting trading on the exchange cannot be modeled solely by the conventional geometric Brownian motion outlined in the Black-Scholes model. A new concise and simpler approach is developed to derive the Jump diffusion model and consequently, its suitability to model stocks on the exchange is emphasized and given rigorous treatment. The model is subsequently used to predict the behaviour of stocks using historical stock prices as input parameters. The simulated stock returns are compared to actual returns to determine the model's suitability to predict the market. The results show that the jump diffusion model is appropriate in predicting the behaviour of approximately 25% percent of stocks listed on the exchange.

ASEAN-5 Stock Price Index Valuation after COVID-19 Outbreak through GBM-MCS and VaR-SDPP Methods

“…It also investigates the probability of the selection of different criteria (Ramadan et al 2020). Antwi et al (2020) stated that applying the Monte Carlo simulation method to the stochastic model can improve the prediction results' accuracy and eliminate the prediction results' instability. Finally, the effectiveness of the GBM-SMC model is shown through more stable prediction results, and the MAPE accuracy values for each experiment are not significantly different.…”