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Study of Relationship between Large-Cap Equity Funds Returns in India and Benchmark Returns

Author

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  • Sanjiwani Jayant KUMAR

    (K J. Somaiya Institute of Management and Research, Mumbai, India)

  • Hitesh PUNJABI

    (K J. Somaiya Institute of Management and Research, Mumbai, India)

  • Ashish MAHADIK

    (K J. Somaiya Institute of Management and Research, Mumbai, India)

Abstract

Large cap equity funds are very popular amongst the retail investors because they offer stability and sustainable returns, over a period of time. This study investigates relationship between Indian stock market index and large cap mutual funds of growth category over the period of ten years. This study has been carried out to confirm the strength positive relationship dynamics of the mutual funds and what is the range of actual contribution of index in the returns of mutual funds. To understand as to what extend effect can be visible; various tests have been carried out across 5 open-ended Equity large cap funds. After series of tests were conducted like arithmetic mean, correlation, standard deviation, causality test, co-integration analysis and vector auto regression (VAR), which concluded that unrelated to any other factors, index returns have strong positive relationship with mutual funds returns in India and contribute significantly in majority of large cap equity mutual funds returns.

Suggested Citation

  • Sanjiwani Jayant KUMAR & Hitesh PUNJABI & Ashish MAHADIK, 2018. "Study of Relationship between Large-Cap Equity Funds Returns in India and Benchmark Returns," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 3, pages 47-56.
    • Handle: RePEc:ddj:fseeai:y:2018:i:3:p:47-56
    DOI: https://doi.org/10.26397/eai1584040916
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    References listed on IDEAS

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    1. Ioannis D Vrontos & Loukia Meligkotsidou & Spyridon D Vrontos, 2011. "Performance evaluation of mutual fund investments: The impact of non-normality and time-varying volatility," Journal of Asset Management, Palgrave Macmillan, vol. 12(4), pages 292-307, September.
    2. Sasipa Pojanavatee, 2014. "Cointegration and causality analysis of dynamic linkage between stock market and equity mutual funds in Australia," Cogent Economics & Finance, Taylor & Francis Journals, vol. 2(1), pages 1-17, December.
    3. Md. Shahadath Hossain & A.B.M. Munibur Rahman & Md. Salah Uddin Rajib, 2013. "Dynamics of Mutual Funds in Relation to Stock Market: A Vector Autoregressive Causality Analysis," International Journal of Economics and Financial Issues, Econjournals, vol. 3(1), pages 191-201.
    4. Martin Rohleder, 2015. "The Relation between Past Flows and Future Performance: Simple Investment Strategies in the Mutual Fund Sector," IJFS, MDPI, vol. 3(1), pages 1-28, February.
    5. Lanne, Markku & Saikkonen, Pentti, 2013. "Noncausal Vector Autoregression," Econometric Theory, Cambridge University Press, vol. 29(3), pages 447-481, June.
    6. Alexakis, Christos & Dasilas, Apostolos & Grose, Chris, 2013. "Asymmetric dynamic relations between stock prices and mutual fund units in Japan. An application of hidden cointegration technique," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 1-8.
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