Methods of nonlinear dynamics and the construction of cryptocurrency crisis phenomena precursors

TL;DR

This paper develops and tests complex systems-based indicators, like recurrence analysis and permutation entropy, to predict critical and crisis phenomena in cryptocurrency markets, demonstrated on Bitcoin's historical crises.

Contribution

It introduces novel dynamic complexity measures as precursors for cryptocurrency crises, validated through empirical analysis of Bitcoin's historical data.

Findings

Indicators effectively predict pre-crisis periods

Recurrence and entropy measures show distinct behavior during crises

Proposed methods outperform traditional indicators

Abstract

This article demonstrates the possibility of constructing indicators of critical and crisis phenomena in the volatile market of cryptocurrency. For this purpose, the methods of the theory of complex systems such as recurrent analysis of dynamic systems and the calculation of permutation entropy are used. It is shown that it is possible to construct dynamic measures of complexity, both recurrent and entropy, which behave in a proper way during actual pre-crisis periods. This fact is used to build predictors of crisis phenomena on the example of the main five crises recorded in the time series of the key cryptocurrency bitcoin, the effectiveness of the proposed indicators-precursors of crises has been identified.