Nonlinear dynamics in cryptocurrency markets: a recurrence quantification analysis approach

This paper introduces Recurrence Quantification Analysis (RQA) as a robust, interpretable framework to evaluate the dynamic behavior of cryptocurrency markets. Using optimized recurrence plot thresholds, we assess the long-term market behavior of 100 cryptocurrencies. Results show that RQA can effectively distinguish periods of stability and instability, identify structural differences between assets, and capture hidden non-linearities that may affect market efficiency. We validate the generalizability of our method by applying it to FinTech-related indices, suggesting that RQA has potential applications beyond cryptocurrencies. These insights are relevant to investors, who require tools for navigating volatility, and regulators seeking to monitor systemic risk.