How to measure the liquidity of cryptocurrencies?


Brauneis, Alexander ; Mestel, Roland ; Riordan, Ryan ; Theissen, Erik



DOI: https://doi.org/10.2139/ssrn.3503507
URL: https://papers.ssrn.com/sol3/papers.cfm?abstract_i...
Document Type: Working paper
Year of publication: 2020
The title of a journal, publication series: SSRN Working Paper Series
Place of publication: Rochester, NY
Publication language: English
Institution: Business School > ABWL u. Finanzierung (Theissen 2009-)
Subject: 330 Economics
Keywords (English): cryptocurrencies , liquidity , horse race
Abstract: We use data from cryptocurrency markets to analyze the accuracy of liquidity measures that are calculated from transactions data. We use benchmark measures calculated from high-frequency order book data to evaluate the performance of the transactions-based measures along three dimensions, the time-series correlation with the benchmark measures, the root mean squared and mean absolute error, and the liquidity ranking across three exchanges. The Abdi & Ranaldo (2017) estimator best captures the time series variation in liquidity. It also performs well in the cross-sectional dimension. When it comes to estimating the level of the benchmark measures the Kyle & Obizhaeva (2016) estimator and the Amihud (2002) illiquidity ratio perform best.




Dieser Eintrag ist Teil der Universitätsbibliographie.




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