Extreme tail network analysis of cryptocurrencies and trading strategies

Syed Jawad Hussain Shahzad, Elie Bouri, Tanveer Ahmad, Muhammad Abubakr Naeem

Research output: Contribution to journalArticlepeer-review

47 Citations (Scopus)

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.

Original languageEnglish
Article number102106
JournalFinance Research Letters
Volume44
DOIs
Publication statusPublished - Jan 2022
Externally publishedYes

Keywords

  • Bitcoin
  • Cryptocurrencies
  • LASSO
  • Quantile
  • Tail network of spillovers
  • Trading strategies

ASJC Scopus subject areas

  • Finance

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