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Volatility of Cryptocurrencies

Author

Listed:
  • Branimir Cvitko Cicvarić

    (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.

Suggested Citation

  • Branimir Cvitko Cicvarić, 2020. "Volatility of Cryptocurrencies," Notitia - journal for economic, business and social issues, Notitia Ltd., vol. 1(6), pages 13-23, December.
    • Handle: RePEc:noa:journl:y:2020:i:6:p:13-23
    as

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    File URL: http://www.notitia.hr/RePEc/noa/journl/02_2020.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    cryptocurrency returns; heteroscedasticity; ARCH/GARCH models;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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