Volatility modelling and VAR: The case of Bitcoin, ether and ripple

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F20%3A82476" target="_blank" >RIV/60460709:41110/20:82476 - isvavai.cz</a>

Výsledek na webu

<a href="https://content.sciendo.com/view/journals/danb/11/3/article-p253.xml?language=en" target="_blank" >https://content.sciendo.com/view/journals/danb/11/3/article-p253.xml?language=en</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2478/danb-2020-0015" target="_blank" >10.2478/danb-2020-0015</a>

Jazyk výsledku

čeština

Název v původním jazyce

Volatility modelling and VAR: The case of Bitcoin, ether and ripple

Popis výsledku v původním jazyce

Since Bitcoin introduction in 2008, the cryptocurrency market has grown into hundreds-of-billion-dollar market. The cryptocurrency market is well known as very volatile, mainly for the fact that the cryptocurrencies have not the price to fall back upon and that anybody can join the trading (no license or approval is required). Since empirical literature suggests that GARCH-type models dominate as VaR estimators the overall objective of this paper is to perform comprehensive volatility and VaR estimation for three major digital assets and conclude which method gives the best results in terms of risk management. The methods we used are parametric (GARCH and EWMA model), non-parametric (historical VaR) and Monte Carlo simulation (given by Geometric Brownian Motion). We conclude that the best method for value-at-risk estimation for cryptocurrencies is the Monte Carlo simulation due to the heavy diffusion (stochastic) process and robustness of the results.

Název v anglickém jazyce

Volatility modelling and VAR: The case of Bitcoin, ether and ripple

Popis výsledku anglicky

Since Bitcoin introduction in 2008, the cryptocurrency market has grown into hundreds-of-billion-dollar market. The cryptocurrency market is well known as very volatile, mainly for the fact that the cryptocurrencies have not the price to fall back upon and that anybody can join the trading (no license or approval is required). Since empirical literature suggests that GARCH-type models dominate as VaR estimators the overall objective of this paper is to perform comprehensive volatility and VaR estimation for three major digital assets and conclude which method gives the best results in terms of risk management. The methods we used are parametric (GARCH and EWMA model), non-parametric (historical VaR) and Monte Carlo simulation (given by Geometric Brownian Motion). We conclude that the best method for value-at-risk estimation for cryptocurrencies is the Monte Carlo simulation due to the heavy diffusion (stochastic) process and robustness of the results.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

50202 - Applied Economics, Econometrics

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Danube: Law and Economics Review

ISSN

1804-8285

e-ISSN

1804-8285

Svazek periodika

11

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

17

Strana od-do

253-269

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85095680453