An analysis of Indian mutual funds’ capacity for market timing during 2010–2023
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Author(s)Mafruza SultanaLink to ORCID Index: https://orcid.org/0000-0002-5482-3163
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Pooja GuptaLink to ORCID Index: https://orcid.org/0000-0002-3480-3579
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Asit K. BarmaLink to ORCID Index: https://orcid.org/0000-0002-6672-1447
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Swarnalakshmi UmamaheswaranLink to ORCID Index: https://orcid.org/0000-0003-1140-3756
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Preetham Karthik M. DontiLink to ORCID Index: https://orcid.org/0009-0006-7228-100X
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DOIhttp://dx.doi.org/10.21511/imfi.22(2).2025.18
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Article InfoVolume 22 2025, Issue #2, pp. 218-237
- 62 Views
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14 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
The Indian economy, often described as cost-sensitive, has seen significant growth in investments in mutual funds and witnessed an increase in the number of investors and total assets under management from 2010 to 2023. This study aims to evaluate the effectiveness of mutual funds in India by identifying those that outperform benchmark indices, assessing the stock selection skills of fund managers, and examining their market timing abilities.
The study further investigates the function of market efficiency by looking into two major areas of fund management – market timing and stock selection. Stock selection measures a portfolio manager’s skill in selecting stocks, and market timing measures a portfolio’s ability to increase exposure to the portfolio in expectation of better movements during a defined period. The study uses the Sharpe ratio, Information Ratio, and Treynor-Mazuy model to analyze mutual fund data. The results indicate that over 80 percent of mutual funds are market independent, with high stock picking ability. Nonetheless, 8% of the funds that showed a market timing ability had little else in terms of active trading, indicating a long-term outlook of investments as opposed to short-term trade strategies. The study concludes that Indian mutual funds have exhibited market timing capabilities and generated positive alpha, signifying risk-adjusted outperformance relative to the market.
- Keywords
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JEL Classification (Paper profile tab)G10, G11, G12, G19
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References34
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Tables10
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Figures0
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- Table 1. Information ratio
- Table 2. Annual MF returns during 2010–2023
- Table 3. Sharpe ratio descriptives for MFs
- Table 4. Top 5 MFs based on Sharpe Ratio
- Table 5. Information ratio descriptives for MFs
- Table 6. Mutual funds ranked based on the Information ratio
- Table 7. Top 5 MFs based on Information ratio
- Table 8. Regression results for the TM model (only significant results considered)
- Table 9. Top 10 MFs based on the TM Model
- Table A1. List of 135 Indian open-ended mutual fund schemes for 14 years, June 2010 to June 2023
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Investment motives and preferences – An empirical inquiry during COVID-19
K. Riyazahmed
doi: http://dx.doi.org/10.21511/imfi.18(2).2021.01
Investment Management and Financial Innovations Volume 18, 2021 Issue #2 pp. 1-11 Views: 2094 Downloads: 1969 TO CITE АНОТАЦІЯFollowing the COVID-19 breakout, investment in shares, mutual funds, and life insurance are witnessing a growing trend in India. Hence, examining the determinants of investor preferences is necessary to maintain a positive trend. This study analyzes the impact of investor motives and awareness on investor preferences using the data collected from 753 Indian investors in 2020. Factor analysis grouped the investment motives into six categories, namely Nature of investments, Future financial needs, Investor personal characteristics, Safety and stability of investments, Investor behavioral aspects, and Investor’s options. The regression model used to find the impact of the investment motives and the awareness on the investor preferences explains 52.3% of changes in investor preference. Investment factors like Nature of investments, Investor personal characteristics, Investor behavior, Investor options, Awareness of mutual funds, and shares have a significant impact on investor preferences. Further, the awareness level of mutual funds and the stock market are the major variables contributing to Investors’ preference rather than identified investment factors. Investors’ personal characteristics like knowledge, confidence, ability, responsibility, and belief negatively influence investor preferences. This study adds to the existing literature by analyzing investment motives and preferences during the pandemic.
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Firm characteristics and capital structure adjustment
Winston Pontoh ,
Novi Swandari Budiarso
doi: http://dx.doi.org/10.21511/imfi.15(2).2018.12
Investment Management and Financial Innovations Volume 15, 2018 Issue #2 pp. 129-144 Views: 1975 Downloads: 467 TO CITE АНОТАЦІЯThe adjustment for the firm capital structure is unclear from perspectives of trade-off theory, pecking order theory, life cycle theory, market timing theory, and free cash flow theory, since many research findings contradict each other. Adjustments for the capital structure are complex, since the conditions for each firm are different. The objective of this study is to provide empirical evidence of how firms adjust capital structure in relationship with maturity in context of trade-off, pecking order, free cash flow, and market timing theory. In terms of hypotheses testing, this study conducts logistic regression analysis with 138 Indonesian public firms as the sample in the observed period from 2010 to 2015. To distinguish the results, this study controls the sample by size and age based on the median. The study reports that preferences for the source of funds based on the cost of capital, internal conflict, and firm maturity indicate adjustments for the firm capital structure. Based on Indonesian firms, the form of capital structure in developing countries can refer to a single model or a combination of the trade-off model and pecking order model, as well as market timing.
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Performance evaluation of Saudi equity mutual funds: Fama decomposition model
Investment Management and Financial Innovations Volume 15, 2018 Issue #4 pp. 158-168 Views: 1663 Downloads: 923 TO CITE АНОТАЦІЯThis paper is in pursuit of analyzing and elongating prior research on the performance evaluation of mutual funds by a comparative analysis with three categories of 82 Saudi equity funds during 2011 to 2016 using Fama’s decomposition model. The paper also made an attempt to explore the relationship with the risk reward ratio to the relative performance measure in predicting the future performance of the Saudi equity fund returns. The empirical results show that Saudi local equity funds perform better followed by Arabian and international/global equity funds in terms of expected signs and diagnostic tests.
