Back to Search
Start Over
Volatility Dynamics of Cryptocurrencies' Returns: An Econometric Study.
- Source :
- IUP Journal of Applied Finance; Jan2020, Vol. 26 Issue 1, p5-30, 26p
- Publication Year :
- 2020
-
Abstract
- The dicey regulatory environment surrounding the cryptocurrency sector has raised the concern of investors and potential investors to study the volatility dynamics of cryptocurrencies' returns in the present scenario. The present treatise is an attempt to study the volatility dynamics of most traded cryptocurrencies, viz., Bitcoin, Bitcoin Cash, EOS, Ethereum, Litecoin, Stellar, Tether and XRP. The daily closing prices for the period of July 2017 to March 2019 were considered. The data of cryptocurrencies was initially studied for stationarity with the help of Ng-Perron test and Augmented Dickey-Fuller (ADF) test. The data was further studied for ARCH effect with the help of Ljung-Box Q-test and Engle's ARCH test. The results confirmed that all cryptocurrencies' return series are stationary and ARCH effect is present in all series. GARCH family models (GARCH, EGARCH, TARCH and PARCH) were applied to study the volatility dynamics. The results confirm the presence of highly persistent volatility and asymmetry in Bitcoin, Bitcoin Cash, EOS, Ethereum, Litecoin, Stellar, Tether and XRP return series. The diagnostic checking as per Akaike Information Criterion, Schwarz Information Criterion and Hannan-Quinn Information Criterion confirmed that PARCH model is the best fitted model for these series, except EOS. EGARCH is the best fitted model for EOS. These findings may help in reducing the investors' dilemma with regard to taking investment decision in the cryptocurrency sector. [ABSTRACT FROM AUTHOR]
- Subjects :
- CRYPTOCURRENCIES
AKAIKE information criterion
GARCH model
BITCOIN
Subjects
Details
- Language :
- English
- ISSN :
- 09725105
- Volume :
- 26
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- IUP Journal of Applied Finance
- Publication Type :
- Academic Journal
- Accession number :
- 142016760