Optimizing Mutual Fund Selection with Fuzzy Sharpe Ratio: An Empirical Study of Indian Markets

Abstract: Mutual funds are widely recognized for their ability to offer diversification and professional management, making them a popular choice for investors. This study explores the evaluation of mutual fund performance using advanced metrics, specifically focusing on fuzzy logic and the Fuzzy Sharpe Ratio. A comprehensive literature review highlights recent advancements, including the integration of machine learning and fuzzy logic models. The study utilizes numerical data from the Bombay Stock Exchange for the period from January 1, 2023, to August 31, 2024, to apply the Fuzzy Risk-Adjusted Return method. The results reveal that the Canara Robeco Bluechip Equity Fund ranks highest according to the Fuzzy Sharpe Ratio, indicating its superior performance compared to other funds, such as the HSBC Large Cap Fund. This analysis underscores the effectiveness of fuzzy logic in enhancing mutual fund evaluations and recommends the Canara Robeco Bluechip Equity Fund as the optimal choice for investors and fund managers.

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Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2024-09-20
DOI
https://doi.org/10.22214/ijraset.2024.64257
Primary Topic
Financial Markets and Investment Strategies
Type
article
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article

Optimizing Mutual Fund Selection with Fuzzy Sharpe Ratio: An Empirical Study of Indian Markets

S. Sathiyapriya, Kabirdoss Devi, S. Viji, V. Manopriya et al.
International Journal for Research in Applied Science and Engineering Technology
Financial Markets and Investment Strategies
article

Optimizing Mutual Fund Selection with Fuzzy Sharpe Ratio: An Empirical Study of Indian Markets

S. Sathiyapriya, Kabirdoss Devi, S. Viji, V. Manopriya, R. Brindha, P. Stanley John, S. Nithya
article en

Abstract

Abstract: Mutual funds are widely recognized for their ability to offer diversification and professional management, making them a popular choice for investors. This study explores the evaluation of mutual fund performance using advanced metrics, specifically focusing on fuzzy logic and the Fuzzy Sharpe Ratio. A comprehensive literature review highlights recent advancements, including the integration of machine learning and fuzzy logic models. The study utilizes numerical data from the Bombay Stock Exchange for the period from January 1, 2023, to August 31, 2024, to apply the Fuzzy Risk-Adjusted Return method. The results reveal that the Canara Robeco Bluechip Equity Fund ranks highest according to the Fuzzy Sharpe Ratio, indicating its superior performance compared to other funds, such as the HSBC Large Cap Fund. This analysis underscores the effectiveness of fuzzy logic in enhancing mutual fund evaluations and recommends the Canara Robeco Bluechip Equity Fund as the optimal choice for investors and fund managers.

International Journal for Research in Applied Science and Engineering TechnologyVol. 12(9)
Openalex Percentile: Top 79%
Financial Markets and Investment Strategies
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Optimizing Mutual Fund Selection with Fuzzy Sharpe Ratio: An Empirical Study of Indian Markets — S. Sathiyapriya, Kabirdoss Devi, et al. · International Journal for Research in Applied Science and Engineering Technology (2024) | TGRS Research Map | TGRS