An Application of Autoregressive Extreme Value Theory to Cryptocurrencies

Chun Kwong Koo, Artur Semeyutin, Chi Keung Marco Lau, Jian Fu

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


We study the tails' behavior of four major Cryptocurrencies (Bitcoin, Litecoin, Ethereum and Ripple) by employing the Autoregressive Fŕechet model for conditional maxima. Using five-minute-high-frequency data, we report time-evolving tails as well as provide a straightforward measure of tails asymmetry for positive and negative intra-day returns. We find that only Bitcoin has a notable more massive tail for positive returns asymmetry while the remaining three Cryptocurrencies have a general tendency towards more massive negative intra-day tails. All considered Cryptocurrencies depict lighter tails as the market matures.

Original languageEnglish
JournalSingapore Economic Review
Publication statusAccepted/In press - 2020
Externally publishedYes


  • Cryptocurrencies
  • bitcoin
  • extreme value theory
  • the expected shortfall
  • time-varying tails


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