TY - JOUR
T1 - An Application of Autoregressive Extreme Value Theory to Cryptocurrencies
AU - Koo, Chun Kwong
AU - Semeyutin, Artur
AU - Marco Lau, Chi Keung
AU - Fu, Jian
N1 - Publisher Copyright:
© 2020 World Scientific Publishing Company.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Cryptocurrencies
KW - bitcoin
KW - extreme value theory
KW - the expected shortfall
KW - time-varying tails
UR - http://www.scopus.com/inward/record.url?scp=85093114119&partnerID=8YFLogxK
U2 - 10.1142/S0217590820470013
DO - 10.1142/S0217590820470013
M3 - Article
AN - SCOPUS:85093114119
SN - 0217-5908
JO - Singapore Economic Review
JF - Singapore Economic Review
ER -