Stochastic Modelling of the Philippine Stock Exchange Composite Index (PSEi)

This study investigates the stochastic modelling of the Philippine Stock Exchange Composite Index (PSEi) to gain insights into its dynamics and underlying patterns. The objective is to develop a robust model that can effectively capture the fluctuations observed in the PSEi, thereby providing investors and policymakers with valuable information for decision-making. To achieve this, we utilize various stochastic processes and statistical methods, including the Geometric Brownian Motion model, to analyze historical stock price data. By applying quantitative techniques, we extract key parameters and evaluate the model's performance based on goodness-of-fit tests. The results reveal significant insights into the volatility and trends of the PSEi, highlighting its responsiveness to economic events and global market influences. Our findings suggest that the stochastic model is capable of predicting the future behavior of the PSEi, making it a useful tool for investors seeking to navigate the complexities of the Philippine stock market. Understanding these dynamics is crucial for enhancing market efficiency and developing strategies aimed at risk management. This research contributes to the existing literature on financial modelling while addressing the specific context of the Philippine stock market. It lays the groundwork for future studies exploring advanced stochastic methods in finance.