Forecast value-at-risk for the cryptocurrency market using Markov-switching EGARCH models

Authors

DOI:

https://doi.org/10.12660/rbfin.v18n3.2020.81186

Keywords:

Cryptocurrencies, Volatility, Regime Change, Value-at-Risk.

Abstract

This study aims to understand the volatile behavior of six highly representative cryptocurrencies. To do so, EGARCH and Markov-switching EGARCH models were estimated, combined with different distributions of statistical probability. The predictive capacity of the best models resulting from these combinations were tested by predicting the value-at-risk. The daily returns of the cryptocurrencies clearly show regime changes in their volatility dynamics. In the in-sample analysis, the regime change model confirms the existence of two states: the first characterized by a greater ARCH effect and less affected by asymmetries, while the second reveals a greater effect of the arrival of information, that is, it is more sensitive to asymmetric shocks. In the out-of-sample analysis, the value-at-risk predictions of the regime change model clearly exceed the single-regime model by the extreme quantile of 1%.

Author Biography

Paulo Fernando Marschner, Universidade Federal de Santa Maria

Doutorando em Administração/Finanças pela Universidade Federal de Santa Maria.

Published

09/05/2020