Extreme tail network analysis of cryptocurrencies and trading strategies

Syed Jawad Hussain Shahzad, Elie Bouri, Tanveer Ahmad and Muhammad Abubakr Naeem
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Syed Jawad Hussain Shahzad: Groupe Sup de Co Montpellier (GSCM) - Montpellier Business School, MRM - Montpellier Research in Management - UPVM - Université Paul-Valéry - Montpellier 3 - UPVD - Université de Perpignan Via Domitia - Groupe Sup de Co Montpellier (GSCM) - Montpellier Business School - UM - Université de Montpellier, SUSU - South Ural State University
Elie Bouri: LAU - Lebanese American University
Tanveer Ahmad: KUST - Kohat University of Science and Technology
Muhammad Abubakr Naeem: UCD - University College Dublin [Dublin]

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Abstract: We examine the median- and tail-based return interdependence among cryptocurrencies under both normal and extreme market conditions. Using daily data and combining the LASSO technique with quantile regression within a framework of network analysis, the main results show the following: Interdependence is higher at tails than at medians, especially the right tail. Bitcoin is not the leading risk transmitter or receiver, but this role is taken by smaller cryptocurrencies. The volatilities of market, size, and momentum drive return connectedness and clustering coefficients under both normal and extreme market conditions. Finally, profitable trading strategies are constructed and evaluated.

Keywords: Bitcoin; Cryptocurrencies; Tail network of spillovers; Quantile; LASSO; Trading strategies (search for similar items in EconPapers)
Date: 2022-01
Note: View the original document on HAL open archive server: https://hal.science/hal-05086285v1
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Published in Finance Research Letters, 2022, 44, pp.102106. ⟨10.1016/j.frl.2021.102106⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05086285

DOI: 10.1016/j.frl.2021.102106

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