Volatility of Cryptocurrencies

Branimir Cvitko Cicvarić ()
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Branimir Cvitko Cicvarić: Addiko Bank d.d.

Notitia - journal for economic, business and social issues, 2020, vol. 1, issue 6, 13-23

Abstract: Many models have been developed to model, estimate and forecast financial time series volatility, amongst which are the most popular autoregressive conditional heteroscedasticity (ARCH) model introduced by Engle (1982) and generalized autoregressive conditional heteroscedasticity (GARCH) model introduced by Bollerslev (1986). The aim of this paper is to determine which type of ARCH/GARCH models can fit the best following cryptocurrencies: Ethereum, Neo, Ripple, Litecoin, Dash, Zcash and Dogecoin. It is found that the EGARCH model is the best fitted model for Ethereum, Zcash and Neo, PARCH model is the best fitted model for Ripple, while for Litecoin, Dash and Dogecoin it depends on the selected distribution and information criterion.

Keywords: cryptocurrency returns; heteroscedasticity; ARCH/GARCH models (search for similar items in EconPapers)
JEL-codes: C3 C53 G11 G17 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:noa:journl:y:2020:i:6:p:13-23

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