IDEAS home Printed from https://ideas.repec.org/a/spr/inecre/v57y2022i2d10.1007_s41775-022-00155-8.html
   My bibliography  Save this article

Risk factors, uncertainty, and investment decision: evidence from mutual fund flows from India

Author

Listed:
  • Elizabeth Nedumparambil

    (T A Pai Management Institute, Manipal Academy of Higher Education)

  • Anup Kumar Bhandari

    (Indian Institute of Technology Madras)

Abstract

Asset pricing theories provide an understanding of the risk factors that determine the price of assets. The identification of risk factors assists investors in seeking out profitable investment opportunities. The difficulty in observing how investors identify such opportunities and how they react to it has largely restricted the literature from determining the factors that matter to an investor. There is a paucity of empirical studies that give insight into the investment decision-making process of an investor. Some of the recent studies that seek to fill this gap have used mutual fund flows to infer which asset pricing model investors use. The fund flows are used as a measure of investors’ response for the identification of a positive net present value investment opportunity. These studies suggest that the Capital Asset Pricing Model (CAPM) is closest to the asset pricing model used by investors in the US market. Taking this literature forward, we enquire whether investors from Indian markets exhibit a similar pattern when making investment decisions. Using the fund flows to actively managed equity schemes, we have investigated the risk factors that matter for mutual fund investors in India for the period from April 2006 to December 2019. We use alternative performance measure and then evaluate the sensitivity of fund flows to each of the performance measures. Our results suggest that investors assess the performance of competing investment opportunities based on naïve measures. Further, though uncertainty has a negative impact on fund flow, the flow–performance relation is not sensitive to the level of uncertainty.

Suggested Citation

  • Elizabeth Nedumparambil & Anup Kumar Bhandari, 2022. "Risk factors, uncertainty, and investment decision: evidence from mutual fund flows from India," Indian Economic Review, Springer, vol. 57(2), pages 349-372, December.
  • Handle: RePEc:spr:inecre:v:57:y:2022:i:2:d:10.1007_s41775-022-00155-8
    DOI: 10.1007/s41775-022-00155-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s41775-022-00155-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s41775-022-00155-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lu Zheng, 1999. "Is Money Smart? A Study of Mutual Fund Investors' Fund Selection Ability," Journal of Finance, American Finance Association, vol. 54(3), pages 901-933, June.
    2. Jesse Blocher & Marat Molyboga, 2017. "The Revealed Preference of Sophisticated Investors," European Financial Management, European Financial Management Association, vol. 23(5), pages 839-872, October.
    3. Wang, Yizhong & Chen, Carl R. & Huang, Ying Sophie, 2014. "Economic policy uncertainty and corporate investment: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 227-243.
    4. Itzhak Ben-David & Jiacui Li & Andrea Rossi & Yang Song, 2022. "What Do Mutual Fund Investors Really Care About?," The Review of Financial Studies, Society for Financial Studies, vol. 35(4), pages 1723-1774.
    5. C. Wei Li & Ashish Tiwari & Lin Tong, 2017. "Investment Decisions Under Ambiguity: Evidence from Mutual Fund Investor Behavior," Management Science, INFORMS, vol. 63(8), pages 2509-2528, August.
    6. Berk, Jonathan B. & van Binsbergen, Jules H., 2016. "Assessing asset pricing models using revealed preference," Journal of Financial Economics, Elsevier, vol. 119(1), pages 1-23.
    7. John Lintner, 1965. "Security Prices, Risk, And Maximal Gains From Diversification," Journal of Finance, American Finance Association, vol. 20(4), pages 587-615, December.
    8. Li, Xiao-Ming, 2017. "New evidence on economic policy uncertainty and equity premium," Pacific-Basin Finance Journal, Elsevier, vol. 46(PA), pages 41-56.
    9. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    10. Rodrik, Dani, 1991. "Policy uncertainty and private investment in developing countries," Journal of Development Economics, Elsevier, vol. 36(2), pages 229-242, October.
    11. Ben-Rephael, Azi, 2017. "Flight-to-liquidity, market uncertainty, and the actions of mutual fund investors," Journal of Financial Intermediation, Elsevier, vol. 31(C), pages 30-44.
    12. Hillenbrand, Adrian & Schmelzer, André, 2017. "Beyond information: Disclosure, distracted attention, and investor behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 16(C), pages 14-21.
    13. Peter Bossaerts & Paolo Ghirardato & Serena Guarnaschelli & William R. Zame, 2010. "Ambiguity in Asset Markets: Theory and Experiment," The Review of Financial Studies, Society for Financial Studies, vol. 23(4), pages 1325-1359, April.
    14. Michael J. Cooper & Huseyin Gulen & P. Raghavendra Rau, 2005. "Changing Names with Style: Mutual Fund Name Changes and Their Effects on Fund Flows," Journal of Finance, American Finance Association, vol. 60(6), pages 2825-2858, December.
    15. Chung, Kee H. & Chuwonganant, Chairat, 2014. "Uncertainty, market structure, and liquidity," Journal of Financial Economics, Elsevier, vol. 113(3), pages 476-499.
    16. Brad M. Barber & Terrance Odean & Lu Zheng, 2005. "Out of Sight, Out of Mind: The Effects of Expenses on Mutual Fund Flows," The Journal of Business, University of Chicago Press, vol. 78(6), pages 2095-2120, November.
    17. You, Wanhai & Guo, Yawei & Zhu, Huiming & Tang, Yong, 2017. "Oil price shocks, economic policy uncertainty and industry stock returns in China: Asymmetric effects with quantile regression," Energy Economics, Elsevier, vol. 68(C), pages 1-18.
    18. H. Henry Cao & Tan Wang & Harold H. Zhang, 2005. "Model Uncertainty, Limited Market Participation, and Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 18(4), pages 1219-1251.
    19. Agarwal, Vikas & Green, T. Clifton & Ren, Honglin, 2018. "Alpha or beta in the eye of the beholder: What drives hedge fund flows?," Journal of Financial Economics, Elsevier, vol. 127(3), pages 417-434.
    20. Gharghori, Philip & Mudumba, Shifali & Veeraraghavan, Madhu, 2007. "How smart is money? An investigation into investor behaviour in the Australian managed fund industry," Pacific-Basin Finance Journal, Elsevier, vol. 15(5), pages 494-513, November.
    21. De Santis, Giorgio & imrohoroglu, Selahattin, 1997. "Stock returns and volatility in emerging financial markets," Journal of International Money and Finance, Elsevier, vol. 16(4), pages 561-579, August.
    22. Ftiti, Zied & Hadhri, Sinda, 2019. "Can economic policy uncertainty, oil prices, and investor sentiment predict Islamic stock returns? A multi-scale perspective," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 40-55.
    23. Brad M. Barber & Xing Huang & Terrance Odean, 2016. "Which Factors Matter to Investors? Evidence from Mutual Fund Flows," The Review of Financial Studies, Society for Financial Studies, vol. 29(10), pages 2600-2642.
    24. Antoniou, Constantinos & Harris, Richard D.F. & Zhang, Ruogu, 2015. "Ambiguity aversion and stock market participation: An empirical analysis," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 57-70.
    25. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    26. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    27. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    28. Chalmers, John & Kaul, Aditya & Phillips, Blake, 2013. "The wisdom of crowds: Mutual fund investors’ aggregate asset allocation decisions," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3318-3333.
    29. Jiang, George J. & Yuksel, H. Zafer, 2017. "What drives the “Smart-Money” effect? Evidence from investors’ money flow to mutual fund classes," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 39-58.
    30. Teodor Dyakov & Marno Verbeek, 2019. "Can Mutual Fund Investors Distinguish Good from Bad Managers?," International Review of Finance, International Review of Finance Ltd., vol. 19(3), pages 505-540, September.
    31. Zhang, Dayong & Lei, Lei & Ji, Qiang & Kutan, Ali M., 2019. "Economic policy uncertainty in the US and China and their impact on the global markets," Economic Modelling, Elsevier, vol. 79(C), pages 47-56.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Omori, Kozo & Kitamura, Tomoki, 2023. "Investor response to Morningstar's ratings, category information, and alpha in the Japanese mutual fund market," International Review of Financial Analysis, Elsevier, vol. 89(C).
    2. Nartea, Gilbert V. & Bai, Hengyu & Wu, Ji, 2020. "Investor sentiment and the economic policy uncertainty premium," Pacific-Basin Finance Journal, Elsevier, vol. 64(C).
    3. Dang, Thuy Duong & Hollstein, Fabian & Prokopczuk, Marcel, 2022. "How do corporate bond investors measure performance? Evidence from mutual fund flows," Journal of Banking & Finance, Elsevier, vol. 142(C).
    4. Luo, Di & Mishra, Tapas & Yarovaya, Larisa & Zhang, Zhuang, 2021. "Investing during a Fintech Revolution: Ambiguity and return risk in cryptocurrencies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    5. Teodor Dyakov & Marno Verbeek, 2019. "Can Mutual Fund Investors Distinguish Good from Bad Managers?," International Review of Finance, International Review of Finance Ltd., vol. 19(3), pages 505-540, September.
    6. Massa, Massimo & Cheng, Si & Zhang, Hong, 2021. "Tax Evasion and Market Efficiency: Evidence from the FATCA and Offshore Mutual Funds," CEPR Discussion Papers 15747, C.E.P.R. Discussion Papers.
    7. Chang, Xiaochen & Guo, Songlin & Huang, Junkai, 2022. "Kidnapped mutual funds: Irrational preference of naive investors and fund incentive distortion," International Review of Financial Analysis, Elsevier, vol. 83(C).
    8. Narasimhan Jegadeesh & Chandra Sekhar Mangipudi & Stijn Van Nieuwerburgh, 0. "What Do Fund Flows Reveal about Asset Pricing Models and Investor Sophistication?," Review of Economic Studies, Oxford University Press, vol. 34(1), pages 108-148.
    9. Timothy B. Riley, 2021. "Portfolios of actively managed mutual funds," The Financial Review, Eastern Finance Association, vol. 56(2), pages 205-230, May.
    10. Alsubaiei, Bader Jawid & Calice, Giovanni & Vivian, Andrew, 2024. "How does oil market volatility impact mutual fund performance?," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 1601-1621.
    11. Rakowski, David & Yamani, Ehab, 2021. "Endogeneity in the mutual fund flow–performance relationship: An instrumental variables solution," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 247-271.
    12. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2020. "Beta uncertainty," Journal of Banking & Finance, Elsevier, vol. 116(C).
    13. Wang, Xiaoxiao, 2024. "Bank affiliation and lottery-like characteristics of mutual funds," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 944-963.
    14. Hung, Pi-Hsia & Lien, Donald & Kuo, Ming-Sin, 2020. "Window dressing in equity mutual funds," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 338-354.
    15. Müller, Marcel & Rosenberger, Tobias & Uhrig-Homburg, Marliese, 2017. "Fake alpha," SFB 649 Discussion Papers 2017-001, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    16. Sebastien Valeyre & Sofiane Aboura & Denis Grebenkov, 2019. "The Reactive Beta Model," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 42(1), pages 71-113, March.
    17. Agarwal, Vikas & Green, T. Clifton & Ren, Honglin, 2018. "Alpha or beta in the eye of the beholder: What drives hedge fund flows?," Journal of Financial Economics, Elsevier, vol. 127(3), pages 417-434.
    18. Huynh, Nhan, 2023. "Unemployment beta and the cross-section of stock returns: Evidence from Australia," International Review of Financial Analysis, Elsevier, vol. 86(C).
    19. Arbaa, Ofer & Varon, Eva, 2019. "The performance and fund flows of name-change funds," Journal of Behavioral and Experimental Finance, Elsevier, vol. 22(C), pages 7-13.
    20. Hodula, Martin & Szabo, Milan & Bajzík, Josef, 2024. "Retail fund flows and performance: Insights from supervisory data," Emerging Markets Review, Elsevier, vol. 59(C).

    More about this item

    Keywords

    Mutual fund; Fund flows; Investor preference; Flow–performance relation; Uncertainty;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:inecre:v:57:y:2022:i:2:d:10.1007_s41775-022-00155-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.