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Exploring the predictability of cryptocurrencies via Bayesian hidden Markov models
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Koki, Constandina, Leonardos, Stefanos and Piliouras, Georgios (2022) Exploring the predictability of cryptocurrencies via Bayesian hidden Markov models. Research in International Business and Finance, 59 . 101554. doi:10.1016/j.ribaf.2021.101554 ISSN 0275-5319.
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Official URL: http://dx.doi.org/10.1016/j.ribaf.2021.101554
Abstract
In this paper, we consider a variety of multi-state hidden Markov models for predicting and explaining the Bitcoin, Ether and Ripple returns in the presence of state (regime) dynamics. In addition, we examine the effects of several financial, economic and cryptocurrency specific predictors on the cryptocurrency return series. Our results indicate that the non-homogeneous hidden Markov (NHHM) model with four states has the best one-step-ahead forecasting performance among all competing models for all three series. The dominance of the predictive densities over the single regime random walk model relies on the fact that the states capture alternating periods with distinct return characteristics. In particular, the four state NHHM model distinguishes bull, bear and calm regimes for the Bitcoin series, and periods with different profit and risk magnitudes for the Ether and Ripple series. Also, conditionally on the hidden states, it identifies predictors with different linear and non-linear effects on the cryptocurrency returns. These empirical findings provide important benefits for portfolio management and policy implementation.
Item Type: | Journal Article | ||||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Mathematics | ||||||||
Journal or Publication Title: | Research in International Business and Finance | ||||||||
Publisher: | Elsevier Inc. | ||||||||
ISSN: | 0275-5319 | ||||||||
Official Date: | January 2022 | ||||||||
Dates: |
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Volume: | 59 | ||||||||
Article Number: | 101554 | ||||||||
DOI: | 10.1016/j.ribaf.2021.101554 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||
Description: | Free access |
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