Modeling cryptocurrencies volatility using GARCH models: a comparison based on Normal and Student's T-Error distribution

Shazia Salamat (), Niu Lixia (), Sobia Naseem (), Muhammad Mohsin (), Muhammad Zia-ur-Rehman () and Sajjad Ahmad Baig ()
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Shazia Salamat: Liaoning Technical University, China
Niu Lixia: Liaoning Technical University, China
Sobia Naseem: Liaoning Technical University, China
Muhammad Mohsin: Liaoning Technical University, China
Muhammad Zia-ur-Rehman: National Textile University, Pakistan
Sajjad Ahmad Baig: National Textile University, Pakistan

Entrepreneurship and Sustainability Issues, 2020, vol. 7, issue 3, 1580-1596

Abstract: This study measures the volatility of cryptocurrency by utilizing the symmetric (GARCH 1,1) and asymmetric (EGARCH, TGARCH, PGARCH) model of GARCH family using a daily database designated in different digital monetary standards. The results for an explicit set of currencies for entire period provide evidence of volatile nature of cryptocurrency and in most of the cases, the PGARCH is a better-fitted model with student’s t distribution. The findings show positive shocks heavily affected conditional volatility as a contrast with negative stuns. Those additional analyses can be provided further support their findings and worthwhile information for economic thespians who are engrossed in adding cryptocurrency to their equity portfolios or are snooping about the capabilities of cryptocurrency as a financial asset.

Keywords: cryptocurrency; GARCH models; normal distribution; student's T distribution (search for similar items in EconPapers)
JEL-codes: B26 C01 C19 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:ssi:jouesi:v:7:y:2020:i:3:p:1580-1596

DOI: 10.9770/jesi.2020.7.3(11)

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