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Time-varying higher moments in Bitcoin
Leonardo Ieracitano Vieira1, Márcio Poletti Laurini1
1Department of Economics, FEARP, University of São Paulo, Av. dos Bandeirantes 3900, Ribeirão Preto, 14040-950 Brazil.
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.
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