 On the topology of cryptocurrency marketsSimon Rudkin, Wanling Rudkin and Paweł Dłotko International Review of Financial Analysis, 2023, vol. 89, issue C Abstract: Cryptocurrency markets are characterised by high volatility, high returns and comparative immaturity relative to equity and commodity markets. Topological Data Analysis (TDA) persistence norms are effective tools for the analysis of noisy dynamical systems like the cryptocurrency markets. We show how information from the shape of daily return data adds additional inference on activity within the cryptocurrency markets. TDA persistence norms embed volatility and connectedness between coins as well as incorporating information from uncertainty indexes, financial market performance and commodity returns. Our TDA measures are robust to noise and are consistent across a raft of alternative coin selections. Further, we exposit how persistence norms peak to forewarn of crashes and stay low as markets face exogenous shocks. We demonstrate the clear advantages of TDA for the study of cryptocurrency markets and develop the next steps for exploiting the potential of TDA for application to cryptocurrency markets. Keywords: Topological data analysis; Persistence norms; Cryptocurrency returns; Volatility; Market efficiency (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:89:y:2023:i:c:s1057521923002752 DOI: 10.1016/j.irfa.2023.102759 Access Statistics for this article International Review of Financial Analysis is currently edited by B.M. Lucey More articles in International Review of Financial Analysis from Elsevier |
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