Preliminary communication

https://doi.org/10.32676/n.6.1.2

Volatility of Cryptocurrencies

Branimir Cvitko Cicvarić orcid.org/0000-0002-2519-4097 ; Addiko Bank d.d.

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

Hrčak ID:

247232

URI

https://hrcak.srce.hr/247232

Publication date:

30.12.2020.

Article data in other languages: croatian

Visits: 1.999 *