Financial Modelling Of Mutual Fund Returns a Data-Driven Approach to Convert Potential Investors into Consistent Wealth Builders

Abstract

Investors often allocate capital to financial markets with the objective of generating returns while minimizing the risk of capital loss. However, many retail investors lack a comprehensive understanding of market dynamics and are often influenced by behavioral factors such as fear and greed, leading to suboptimal investment decisions. Financial modelling and data-driven analysis can help investors make more informed and rational investment choices.This study aims to develop a financial model to analyze and quantify the performance of mutual funds over time. The research focuses on evaluating selected mutual fund categories, including equity, debt, and hybrid funds, with particular attention to HDFC mutual fund schemes and their comparison with the index benchmark. The model applies various financial analytics techniques to assess risk and return characteristics. Key performance indicators such as Sharpe Ratio, Alpha, Beta, Maximum Drawdown, and correlation heatmap analysis are used to evaluate fund performance and portfolio diversification. Additionally, the study examines the effectiveness of Systematic Investment Plans (SIPs) in mitigating market volatility and promoting long-term wealth creation. By identifying high-risk areas within investment portfolios, this model helps investors optimize their portfolio allocation and improve financial decision-making. The findings emphasize the importance of understanding Net Asset Value (NAV) volatility and adopting disciplined investment strategies for long-term financial growth.