A taxonomic evaluation of Indian mutual funds’ performance and its determinants – Post-pandemic

  • 639 Views
  • 267 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

The COVID-19 pandemic has caused significant disruption in financial markets worldwide and impacted the performance of investment avenues like mutual funds. It has been a challenging scenario for all mutual funds to sustain the pre-pandemic performance. To understand the mutual fund investment scenario further, this study focused on examining the post-pandemic performance in the year 2021 of various categories of mutual funds, the significance of scheme characteristics in determining the performance, risk-adjusted performance, and outperformance of various categories of funds. Out of 4,305 mutual fund schemes, tax planning funds (58%), sectoral funds (57%), and equity diversified funds (55%) achieved better returns. Further, using the ordinary least squares (OLS) regression, the study estimated the effect of fund characteristics like scheme category, scheme type, scheme access type along with the fund’s tracking error and corpus size on funds’ return. The results show that tax planning, sectoral, and equity diversified funds significantly outperform. Tracking error significantly reduces the fund return by 4.52%. Scheme type, scheme access type, and corpus size were not significant. Equity, index, pension, and balanced category funds exhibit risk-adjusted performance, and only bond funds were able to outperform the respective benchmarks. The study adds to the existing literature by investigating the post-pandemic performance determinants of mutual funds.

view full abstract hide full abstract
    • Figure 1. Sharpe ratio and Information ratio for different categories of funds
    • Table 1. Classification of mutual funds based on scheme category
    • Table 2. Corpus size of the mutual funds
    • Table 3. Mutual fund returns in different time frames
    • Table 4. OLS regression results
    • Conceptualization
      K. Riyazahmed
    • Data curation
      K. Riyazahmed, B. Anitha Kumari, B. Diwakar Naidu
    • Formal Analysis
      K. Riyazahmed, B. Anitha Kumari
    • Investigation
      K. Riyazahmed, B. Diwakar Naidu
    • Methodology
      K. Riyazahmed
    • Validation
      K. Riyazahmed
    • Writing – original draft
      K. Riyazahmed
    • Writing – review & editing
      K. Riyazahmed, B. Anitha Kumari, B. Diwakar Naidu
    • Resources
      B. Anitha Kumari, B. Diwakar Naidu