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Extreme tail network analysis of cryptocurrencies and trading strategies

Author

Listed:
  • 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])

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.

Suggested Citation

  • Syed Jawad Hussain Shahzad & Elie Bouri & Tanveer Ahmad & Muhammad Abubakr Naeem, 2022. "Extreme tail network analysis of cryptocurrencies and trading strategies," Post-Print hal-05086285, HAL.
    • Handle: RePEc:hal:journl:hal-05086285
    DOI: 10.1016/j.frl.2021.102106
    as

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