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. 2022 Dec 23:1-30.
doi: 10.1007/s42521-022-00072-8. Online ahead of print.

Time-varying higher moments in Bitcoin

Leonardo Ieracitano Vieira  1 , Márcio Poletti Laurini  1
Affiliations

Time-varying higher moments in Bitcoin

Leonardo Ieracitano Vieira et al. Digit Finance. .

Abstract

Cryptocurrencies represent a new and important class of investments but are associated with asymmetric distributions and extreme price changes. We use a modeling structure where higher-order moments (scale, skewness and kurtosis) are time-varying, and additionally we used nontraditional innovations distributions to study the return series of the most important cryptocurrency, Bitcoin. Based on the estimation of a series of Generalized Autoregressive Score (GAS) models, we compare predictive performance using a loss function based on Value at Risk performance.

Keywords: Bitcoin; Generalized autoregressive score; Higher-order moments; Risk management.

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Conflict of interest statement

Conflict of interestThe authors report the absence of any type of conflict of interest.

Figures

Fig. 1
Fig. 1
Figure displays Bitcoin US dollar prices in top panel (a) and daily Log returns in bottom panel (b). Price data was collected from coinmetrics.io
Fig. 2
Fig. 2
Figure displays the posterior probability of jumps for the conditional volatility and mean using the double jump model of (Chaim and Laurini, 2018)
Fig. 3
Fig. 3
Absolute Log returns (black color) and predicted volatility (red). These are the sstd innovations estimation result
Fig. 4
Fig. 4
Figure displays Bitcoin return’s predicted skewness in top panel (a) and daily predicted kurtosis in bottom panel (b)
Fig. 5
Fig. 5
Absolute Log returns (black color) and predicted volatility of garch, sstd, std and ald distributions
See this image and copyright information in PMC

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