A hidden Markov model to detect regime changes in cryptoasset markets |
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Authors: | Paolo Giudici Iman Abu Hashish |
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Affiliation: | 1. Department of Economics and Management, University of Pavia, Pavia, Italy;2. Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy |
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Abstract: | The objective of this work is to understand the dynamics of cryptocurrency prices. Specifically, how prices switch between different regimes, going from “bull” to “stable” and “bear” times. For this purpose, we propose a hidden Markov model that aims at explaining the evolution of Bitcoin prices through different, unobserved states. The implementation of the proposed model includes a likelihood ratio test that allows to compare models with different states and with different covariance structures. Our empirical findings show that the time movements of Bitcoin prices across different exchange markets are well-described by the proposed model. In particular, a parsimonious model with a diagonal covariance matrix leads to better predictions, compared with a model with a full covariance matrix. |
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Keywords: | Bitcoin exchange markets Bitcoin prices hidden Markov models likelihood ratio tests |
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