The IUP Journal of Applied Finance
Volatility Dynamics of Cryptocurrencies' Returns: An Econometric Study
Article Details
| Pub. Date | : Jan, 2020 |
|---|---|
| Product Name | : The IUP Journal of Applied Finance |
| Product Type | : Article |
| Product Code | : IJAF10120 |
| Author Name | : Vandana Dangi |
| Availability | : YES |
| Subject/Domain | : Finance |
| Download Format | : PDF Format |
| No. of Pages | : 26 |
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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.
Description
The contemporary scenario in cryptocurrency sector has aroused the need for redevelopment of investment strategy by existing and potential investors. The termination of relationship of all RBI regulated entities with individuals or firms dealing in cryptocurrencies is a big blow to this sector. However, the ecosystem of cryptocurrency has been surviving on two lifelines in terms of peer-to-peer and crypto-to-crypto trading. Investors are in a big dilemma in considering this virtual currency sector as a reliable investment alternative. They need prediction of volatility dynamics in cryptocurrency sector to measure risk exposure in their investment. That is why investors are interested in studies relating to the volatility dynamics in cryptocurrencies. Researchers have given a lot of attention to accurate modeling of the volatility dynamics. The approaches developed by Engle (1982) and Bollerslev (1986) modeled the conditional volatility that had improved the way of capturing the characteristics of financial data. Researchers like Crouhy and Rockinger (1997), Connolly and Stivers (1999 and 2005), Kaur (2004), Pati (2006), Sarangi and Patnaik (2006), Sinha (2006 and 2012), Daal Elton et al. (2007), Hourvouliades (2007), Ninga et al. (2009), Mahmud and Mirza (2011), Xue and Gencay (2012), Lin and Fuerst (2013), and Moussa (2014) had discarded the volatility as a constant and unconditional statistics. These researchers had studied the volatility dynamics in financial markets with the help of various models of GARCH family.
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