Value-at-Risk and Expected Shortfall for the major digital currencies

TL;DR

This paper assesses the risk measures of major digital currencies using GARCH and Filtered Historical Simulation, revealing their higher risk levels and implications for risk management.

Contribution

It introduces an analysis of Value-at-Risk and Expected Shortfall for digital currencies using advanced econometric models, filling a gap in cryptocurrency risk assessment.

Findings

Digital currencies exhibit higher risk levels than traditional assets.

GARCH and Filtered Historical Simulation effectively capture cryptocurrency risk.

Higher risk necessitates larger buffers and risk capital for digital currencies.

Abstract

Digital currencies and cryptocurrencies have hesitantly started to penetrate the investors, and the next step will be the regulatory risk management framework. We examine the Value-at-Risk and Expected Shortfall properties for the major digital currencies, Bitcoin, Ethereum, Litecoin, and Ripple. The methodology used is GARCH modelling followed by Filtered Historical Simulation. We find that digital currencies are subject to a higher risk, therefore, to higher sufficient buffer and risk capital to cover potential losses.