Share price dynamics of listed companies on the Dhaka stock exchange using geometric Brownian motion
DOI:
https://doi.org/10.56947/amcs.v26.450Keywords:
Geometric Brownian Motion, Dhaka Stock Exchange, Share Price, MAPEAbstract
The stock prices of publicly traded companies exhibit continuous and random fluctuations over time, necessitating the inclusion of a stochastic term in dynamic models to accurately capture this behavior. This study applies the geometric Brownian motion (GBM) model to analyse the stock prices of 20 randomly selected companies listed on the Dhaka Stock Exchange (DSE). The GBM model was resolved through Monte Carlo simulation to forecast stock prices over a trading horizon of approximately 30 to 35 days. Using historical data from the first four months of 2024, we predicted the share prices for the subsequent one-and-a-half months. The comparison between forecast and actual prices demonstrated a high level of concordance, with a mean absolute percentage error (MAPE) of less than 8%. These findings underscore the efficacy of the model in providing robust predictions of share prices for selected companies.
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