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An enhanced Multivariate Markov Chain method for modeling cross-market influences on cryptocurrencies
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Resumo(s)
The predictability of the cryptocurrency market is a current and highly researched topic. However, the cross-market influences on the returns of the cryptocurrencies would benefit from different perspectives. This study examines the dynamic interplay between Bitcoin, Ethereum, and traditional financial indices spanning from 2017 to 2023 using the Mixture Transition Distribution and Generalized Multivariate Markov Chain models. The findings indicate the presence of own-state persistence within each cryptocurrency, as well as influence from a diverse set of financial indices. Evidence suggests that different sector indices affect these cryptocurrencies with distinct degrees of influence. Additionally, the results demonstrate cross-currency influence, notably Ethereum’s influence on Bitcoin, suggesting a more interconnected market.
Descrição
Reyna, A., & Damásio, B. (2026). An enhanced Multivariate Markov Chain method for modeling cross-market influences on cryptocurrencies. Decision Analytics Journal, 20, Article 100739. https://doi.org/10.1016/j.dajour.2026.100739
Palavras-chave
Markov chains Mixture Transition Distribution Cryptocurrency Cross-market influence Transition probability Financial analytics Analysis General Decision Sciences Modelling and Simulation Applied Mathematics