Katsiampa (2017) shows that, among different GARCH models, the optimal conditional heteroskedasticity model regarding the goodness-of-fit to Bitcoin price data is the AR-Component GARCH (AR-CGARCH) model. However, in that paper the author does not take into account for statistical proprieties of Bitcoin’s return distribution, and even showing both skewness and non-normality of the data, we consider a standardized normal distribution for all studied GARCH models. This paper represents an improvement of the previous literature about GARCH model for Bitcoin. In particular, this paper examines different distributional assumptions about innovations distribution for some GARCH models, showing that it is possible to obtain better estimates through the AR(1)-APARCH(1,1) model assuming that innovations follow a t-student distribution.

Alternative distribution based GARCH models for Bitcoin volatility estimation / Mattera, R.; Giacalone, M.. - In: THE EMPIRICAL ECONOMICS LETTERS. - ISSN 1681-8997. - 17:11(2018), pp. 1-9.

Alternative distribution based GARCH models for Bitcoin volatility estimation

Mattera R.
;
Giacalone M.
2018

Abstract

Katsiampa (2017) shows that, among different GARCH models, the optimal conditional heteroskedasticity model regarding the goodness-of-fit to Bitcoin price data is the AR-Component GARCH (AR-CGARCH) model. However, in that paper the author does not take into account for statistical proprieties of Bitcoin’s return distribution, and even showing both skewness and non-normality of the data, we consider a standardized normal distribution for all studied GARCH models. This paper represents an improvement of the previous literature about GARCH model for Bitcoin. In particular, this paper examines different distributional assumptions about innovations distribution for some GARCH models, showing that it is possible to obtain better estimates through the AR(1)-APARCH(1,1) model assuming that innovations follow a t-student distribution.
2018
Alternative distribution based GARCH models for Bitcoin volatility estimation / Mattera, R.; Giacalone, M.. - In: THE EMPIRICAL ECONOMICS LETTERS. - ISSN 1681-8997. - 17:11(2018), pp. 1-9.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/736943
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