A Peek into the Unobservable: Hidden States and Bayesian Inference for the Bitcoin and Ether Price Series

TL;DR

This paper applies a novel Hidden Markov model to Bitcoin and Ether prices, revealing unobservable market states and distinct influences on each cryptocurrency, advancing understanding of their complex microstructure.

Contribution

It introduces a Non-Homogeneous Hidden Markov model with blockchain and financial covariates to analyze unobservable market states in cryptocurrencies.

Findings

Identifies two main market states: fundamental and noise trading.

Reveals different key indicators influence Bitcoin and Ether markets.

Shows cryptocurrency markets are influenced by distinct factors despite perceived correlation.

Abstract

Conventional financial models fail to explain the economic and monetary properties of cryptocurrencies due to the latter's dual nature: their usage as financial assets on the one side and their tight connection to the underlying blockchain structure on the other. In an effort to examine both components via a unified approach, we apply a recently developed Non-Homogeneous Hidden Markov (NHHM) model with an extended set of financial and blockchain specific covariates on the Bitcoin (BTC) and Ether (ETH) price data. Based on the observable series, the NHHM model offers a novel perspective on the underlying microstructure of the cryptocurrency market and provides insight on unobservable parameters such as the behavior of investors, traders and miners. The algorithm identifies two alternating periods (hidden states) of inherently different activity -- fundamental versus uninformed or noise traders -- in the Bitcoin ecosystem and unveils differences in both the short/long run dynamics and in the financial characteristics of the two states, such as significant explanatory variables, extreme events and varying series autocorrelation. In a somewhat unexpected result, the Bitcoin and Ether markets are found to be influenced by markedly distinct indicators despite their perceived correlation. The current approach backs earlier findings that cryptocurrencies are unlike any conventional financial asset and makes a first step towards understanding cryptocurrency markets via a more comprehensive lens.