Mutual Fund Performance Evaluation Using Different Benchmarking Models

Abstract

This study examines mutual fund performance evaluation using a range of benchmarking models to determine how different frameworks influence conclusions about managerial skill and risk-adjusted returns. Recognizing that traditional single-factor approaches often fail to capture the multifaceted drivers of fund performance, the research adopts an integrated methodology combining quantitative econometric models with qualitative analysis. Benchmarking models employed include the Capital Asset Pricing Model (CAPM), Fama-French multi-factor frameworks, conditional performance models incorporating macroeconomic variables, and risk-adjusted measures such as the Sharpe, Treynor, Information ratios, and Conditional Value-at-Risk (CVaR).Results from nine detailed tables and twelve graphical analyses confirm that benchmarking choice significantly alters fund rankings and risk assessments. CAPM provided a baseline view of systematic risk, but multifactor models demonstrated superior explanatory power by accounting for size, value, profitability, and investment effects. Conditional models revealed time-varying betas and showed that funds adjust differently to interest rate shifts, inflationary pressures, and volatility regimes. Risk-adjusted ratios highlighted diversification benefits, while downside-risk metrics captured vulnerabilities that variance-based measures overlooked. Sectoral allocation analysis indicated that exposure to technology and finance enhanced performance during growth cycles, whereas healthcare and energy sectors displayed defensive attributes. Cross-market comparisons further revealed that international funds offered diversification benefits despite higher volatility.The findings carry important implications for stakeholders. For investors, the evidence highlights the need to consider multiple benchmarks before making allocation decisions. For fund managers, the results emphasize consistency and transparency in strategy, as style drift can distort performance assessments. For regulators, the study advocates multifactor benchmarking disclosures to ensure fairer performance reporting. Ultimately, this research underscores that comprehensive fund evaluation requires a multidimensional approach, integrating traditional and advanced models to reflect the realities of dynamic financial markets.