Tail risk transmission in technology-driven markets

Muhammad Abubakr Naeem, Mohammad Rahim Shahzad, Sitara Karim, Rima Assaf

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

The soaring popularity of blockchain investing and cryptocurrencies has captured the attention of policymakers and investors alike. However, as cryptocurrencies remain the most volatile and high-risk investment options, they have displayed extreme asymmetric patterns over time. Considering these concerns, we conducted a comprehensive analysis of the tail risk transmission of these technology-driven markets using the Conditional autoregressive Value at risk (CAViaR) model, which sheds valuable light on the market's tail characteristics. We combined the CAViaR approach with the time-frequency methods proposed by Diebold and Yilmaz (2012) and Barunik and Krehlik (2018) to further enhance our analysis. Our results revealed a range of asymmetric economic and financial patterns across markets and highlighted the varying exposure of these markets to different circumstances over time. Finally, we investigated the impact of global factors on the tail risk transmission of technology-driven markets both in the long and short term. This study offers a wealth of insights for policymakers, investors, financial market participants, and scholars of digital finance to help navigate these rapidly evolving markets.

Original languageEnglish
Article number100855
JournalGlobal Finance Journal
Volume57
DOIs
Publication statusPublished - Aug 2023

Keywords

  • CAViaR
  • Cryptocurrencies
  • Tail risk transmission
  • Technology-driven markets

ASJC Scopus subject areas

  • Finance
  • Economics and Econometrics

Fingerprint

Dive into the research topics of 'Tail risk transmission in technology-driven markets'. Together they form a unique fingerprint.

Cite this