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

Mukul Bhatnagar, Ercan Özen, Sanjay Taneja, Simon Grima and Ramona Rupeika-Apoga ()
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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
Ramona Rupeika-Apoga: Faculty of Business, Management and Economics, University of Latvia, LV-1586 Riga, Latvia

Risks, 2022, vol. 10, issue 11, 1-16

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.

Keywords: fintech; risk; return; investments; variance-based Mean-GARCH (GARCH-M) model; dynamic connectedness (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jrisks:v:10:y:2022:i:11:p:209-:d:962407

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