MEASURING VALUE AT RISK USING GARCH MODEL - EVIDENCE FROM THE CRYPTOCURRENCY MARKET

Reference: Obeng, C., (2021). Measuring Value at Risk using GARCH model - evidence from the cryptocurrency market. International Journal of Entrepreneurial Knowledge, 9(2), 63-84. doi: 10.37335/ijek.v9i2.133

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DOI:

https://doi.org/10.37335/ijek.v9i2.133

Abstract

There is a growing interest in the activities of the crypto market by various stakeholders. These stakeholders generally include investors, entrepreneurs, governments, fund managers, climate activists, institutional managers, employees with surplus funds, and crypto miners. This study aims to investigate the accuracy of the GARCH models for measuring and estimating Value-at-risk (VaR) using the Cryptocurrency index for future investment and managerial decision making. Because of this, the present study uses the top 30 Cryptocurrencies index in terms of Market capitalization excluding stable coins to determine the best GARCH models. Many entrepreneurs, institutional managers, fund managers, and other stakeholders have recently included cryptocurrency in their investment portfolio because of the increase in transactions and high returns growth in the global financial market with its associated high returns and volatility. Information communication technology has paved the way for such activities in the global markets. The daily data frequency was applied because of the availability of the data. The empirical analysis has been carried out for the period from January 2017 to December 2020 for a total of 1461observation. The returns volatility is estimated using SGARCH and EGARCH models. The findings evidenced that, using both normal distribution and Student t distribution, EGARCH provides a better measure and estimate than SGARCH concerning high persistence and volatility. Against this background, the present study also examined Backtesting to estimate Value at Risk. Interestingly, the findings of the available study would provide industry players, practitioners, entrepreneurs, and investors the maximum edge on how to use or measure such variables against others to make investment decisions. Also, the findings would subsequently contribute more insight into academia on the study area.

Author Biography

Cosmos Obeng, Tomas Bata University in Zlin

Cosmos Obeng

Ph.D. Candidate, Tomas Bata University in Zlín, Faculty of Management and Economics, Mostní 5139, 76001, Zlín, Czech Republic

Email: obeng@utb.cz

Area of interest: Digital finance, Digital Contract, Financial risk management

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Published

2021-12-22