A Data Envelopment Analysis Approach to Benchmark the Performance of Mutual Funds in India

TL;DR

This paper applies Data Envelopment Analysis to evaluate and benchmark the performance of Indian mutual funds, incorporating traditional and new metrics like the information ratio to provide a comprehensive efficiency assessment.

Contribution

It introduces an enhanced DEA model that includes risk, cost, return, and information ratio metrics for mutual fund performance benchmarking in India.

Findings

DEA effectively benchmarks mutual fund efficiency.

Inclusion of information ratio improves assessment accuracy.

Results align with industry ratings and reveal performance insights.

Abstract

As the Indian economy grows digitally and becomes more financially inclusive, more and more investors have started to invest in the Indian capital markets. The number of retail and institutional folios with Indian mutual fund schemes have continued to rise for the 74th consecutive month. This study considers 139 mutual fund schemes (98 equity schemes) and aims to ascertain the various metrics and parameters, retail and institutional investors continue to rely on to make investment recommendations. We compare these with the results from a data envelopment analysis model that generates an efficiency frontier based on an optimal risk, cost, and return trade-off. We further put forth an iteration of the DEA model, not only considering risk, cost, and return characteristics but also incorporating metrics such as the information ratio which hold significance for retail and institutional investors. We compare these results with traditional metrics and fund rankings published by established industry rating agencies.