Exploring the Predictability of Cryptocurrencies via Bayesian Hidden Markov Models

Constandina Koki
Constandina Koki
Stefanos Leonardos
Stefanos Leonardos
Cited by: 0|Views3

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 result...More

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