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The Dynamic Connectedness between Risk and Return in the Fintech Market of India: Evidence Using the GARCH-M Approach

Author

Listed:
  • Mukul Bhatnagar

    (Commerce Department (USB), Chandigarh University, Mohali 140413, India)

  • Ercan Özen

    (Department of Finance and Banking, University of Uşak, Uşak 64000, Turkey)

  • Sanjay Taneja

    (University School of Business, Chandigarh University, Mohali 140413, India)

  • Simon Grima

    (Department of Insurance and Risk Management, Faculty of Economics, Management and Accountancy, University of Malta, MSD Msida 2080, Malta
    Faculty of Business, Management and Economics, University of Latvia, LV-1586 Riga, Latvia)

  • Ramona Rupeika-Apoga

    (Faculty of Business, Management and Economics, University of Latvia, LV-1586 Riga, Latvia)

Abstract

Fintech allows investors to explore previously unavailable investment opportunities; it provides new return opportunities while also introducing new risks. The aim of this study is to investigate the relationship between risk and return in the fintech industry in the Indian stock market. This article is based on market-based research that focuses on demonstrating the volatility in the fintech market’s prices and demystifying the opportunities. Secondary data were collected from the Bombay Stock Exchange’s official fintech industry website from January 2017 to July 2022 to determine whether there is any dynamic link between risk and return in the Indian fintech market. The variance-based Mean-GARCH (GARCH-M) model was used to determine whether there is a dynamic link between risk and return in the Indian fintech market. The findings emphasize the importance of taking the risk of investing in India’s fintech industry. The implications for stock investors’ and fund managers’ portfolio composition and holding periods of equities or market exposure are significant. Finally, depending on their investment horizons, the Indian fintech industry may yield significant profits for risk-taking individuals.

Suggested Citation

  • Mukul Bhatnagar & Ercan Özen & Sanjay Taneja & Simon Grima & Ramona Rupeika-Apoga, 2022. "The Dynamic Connectedness between Risk and Return in the Fintech Market of India: Evidence Using the GARCH-M Approach," Risks, MDPI, vol. 10(11), pages 1-16, November.
    • Handle: RePEc:gam:jrisks:v:10:y:2022:i:11:p:209-:d:962407
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    References listed on IDEAS

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    1. Juan Camilo Cardenas & Jeffrey Carpenter, 2008. "Behavioural Development Economics: Lessons from Field Labs in the Developing World," Journal of Development Studies, Taylor & Francis Journals, vol. 44(3), pages 311-338.
    2. Andreas Oehler & Matthias Horn & Stefan Wendt, 2022. "Investor Characteristics and their Impact on the Decision to use a Robo-advisor," Journal of Financial Services Research, Springer;Western Finance Association, vol. 62(1), pages 91-125, October.
    3. Chen, Gong-meng & Firth, Michael & Meng Rui, Oliver, 2002. "Stock market linkages: Evidence from Latin America," Journal of Banking & Finance, Elsevier, vol. 26(6), pages 1113-1141, June.
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. Erik Feyen & Jon Frost & Leonardo Gambacorta & Harish Natarajan & Matthew Saal, 2021. "Fintech and the digital transformation of financial services: implications for market structure and public policy," BIS Papers, Bank for International Settlements, number 117.
    6. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    7. Kroner, Kenneth F. & Lastrapes, William D., 1993. "The impact of exchange rate volatility on international trade: Reduced form estimates using the GARCH-in-mean model," Journal of International Money and Finance, Elsevier, vol. 12(3), pages 298-318, June.
    8. Baljinder Kaur & Sood Kiran & Simon Grima & Ramona Rupeika-Apoga, 2021. "Digital Banking in Northern India: The Risks on Customer Satisfaction," Risks, MDPI, vol. 9(11), pages 1-18, November.
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    Cited by:

    1. Eman Ismail & Yasser Tawfik Halim & Mohamed Samy EL-Deeb, 2023. "Corporate reputation and shareholder investment: a study of Egypt's tourism listed companies," Future Business Journal, Springer, vol. 9(1), pages 1-15, December.
    2. Ziyao Wang & Yufei Xia & Yating Fu & Ying Liu, 2023. "Volatility Spillover Dynamics and Determinants between FinTech and Traditional Financial Industry: Evidence from China," Mathematics, MDPI, vol. 11(19), pages 1-23, September.
    3. Sun Meng & Yan Chen, 2023. "Market Volatility Spillover, Network Diffusion, and Financial Systemic Risk Management: Financial Modeling and Empirical Study," Mathematics, MDPI, vol. 11(6), pages 1-16, March.

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