Modeling tail-dependence of crypto assets with Extreme Value Theory – Perspectives of Risk Management in Banks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14220%2F22%3A00127831" target="_blank" >RIV/00216224:14220/22:00127831 - isvavai.cz</a>

Výsledek na webu

<a href="https://virtusinterpress.org/Modeling-tail-dependence-of-crypto-assets-with-extreme-value-theory-Perspectives-of-risk-management-in-banks.html" target="_blank" >https://virtusinterpress.org/Modeling-tail-dependence-of-crypto-assets-with-extreme-value-theory-Perspectives-of-risk-management-in-banks.html</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.22495/rgcv12i4p5" target="_blank" >10.22495/rgcv12i4p5</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Modeling tail-dependence of crypto assets with Extreme Value Theory – Perspectives of Risk Management in Banks

Popis výsledku v původním jazyce

Cryptocurrencies show some properties that differ from typical financial instruments. For example, dynamic volatility, larger price jumps, and other market participants and their associated characteristics can be observed (Pardalos, Kotsireas, Guo, &amp; Knottenbelt, 2020). Especially high tail risk (Sun, Dedahanov, Shin, &amp; Li, 2021; Corbet, Meegan, Larkin, Lucey, &amp; Yarovaya, 2018; Borri, 2019) leads to the question of whether the methods and procedures established in risk management are suitable for measuring the resulting market risks of cryptos appropriately. Therefore, we examine the risk measurement of Bitcoin, Ethereum, and Litecoin. In addition to the classic methods of market risk measurement, historical simulation, and the variance-covariance approach, we also use the extreme value theory to measure risk. Only the extreme value theory with the peaks-over-threshold method delivers satisfactory backtesting results at a confidence level of 99.9%. In the context of our analysis, the highly volatile market phase from January 2021 was crucial. In this, extreme deflections that have never been observed before in the time series have significantly influenced backtesting. Our paper underlines that critical market phases could not be sufficiently observed from the short time series, leading to adequate backtesting results under the standard market risk measurement. At the same time, the strength of the extreme value theory comes into play here and generates a preferable risk measurement.

Název v anglickém jazyce

Modeling tail-dependence of crypto assets with Extreme Value Theory – Perspectives of Risk Management in Banks

Popis výsledku anglicky

Cryptocurrencies show some properties that differ from typical financial instruments. For example, dynamic volatility, larger price jumps, and other market participants and their associated characteristics can be observed (Pardalos, Kotsireas, Guo, &amp; Knottenbelt, 2020). Especially high tail risk (Sun, Dedahanov, Shin, &amp; Li, 2021; Corbet, Meegan, Larkin, Lucey, &amp; Yarovaya, 2018; Borri, 2019) leads to the question of whether the methods and procedures established in risk management are suitable for measuring the resulting market risks of cryptos appropriately. Therefore, we examine the risk measurement of Bitcoin, Ethereum, and Litecoin. In addition to the classic methods of market risk measurement, historical simulation, and the variance-covariance approach, we also use the extreme value theory to measure risk. Only the extreme value theory with the peaks-over-threshold method delivers satisfactory backtesting results at a confidence level of 99.9%. In the context of our analysis, the highly volatile market phase from January 2021 was crucial. In this, extreme deflections that have never been observed before in the time series have significantly influenced backtesting. Our paper underlines that critical market phases could not be sufficiently observed from the short time series, leading to adequate backtesting results under the standard market risk measurement. At the same time, the strength of the extreme value theory comes into play here and generates a preferable risk measurement.

Druh

J_ost - Ostatní články v recenzovaných periodicích

CEP obor

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OECD FORD obor

50206 - Finance

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

Risk Governance and Control: Financial Markets and Institutions

ISSN

2077-429X

e-ISSN

2077-4303

Svazek periodika

12

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

UA - Ukrajina

Počet stran výsledku

11

Strana od-do

67-77

Kód UT WoS článku

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EID výsledku v databázi Scopus

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