Beyond GARCH in cryptocurrency volatility modelling: superiority of range-based estimators

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F25%3A00599014" target="_blank" >RIV/67985556:_____/25:00599014 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11230/25:10514038

Výsledek na webu

<a href="https://www.tandfonline.com/doi/full/10.1080/13504851.2024.2363295" target="_blank" >https://www.tandfonline.com/doi/full/10.1080/13504851.2024.2363295</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/13504851.2024.2363295" target="_blank" >10.1080/13504851.2024.2363295</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Beyond GARCH in cryptocurrency volatility modelling: superiority of range-based estimators

Popis výsledku v původním jazyce

Cryptoassets are extremely volatile with possible volatility jumps and infrastructure noise, making the estimation of true volatility process challenging. When the high-frequency data are not available, the true volatility needs to be estimated to be further studied or forecasted. The GARCH-family models have become a norm in the field. Here, we examine the performance of 6 GARCH-type specifications with 4 distributional assumptions and compare them with 4 non-parametric range-based models built on the daily ‘candles’. Our study focuses on five popular cryptocurrencies (Bitcoin, Ethereum, BNB, XRP, and Dogecoin) between 1 July 2019 and 30 September 2022, utilizing Binance 5-minute data for realized measures as the high-frequency estimators of the true volatility process. The results reveal that the Garman-Klass estimator clearly outperforms the GARCH-family models in all studied settings, and the other range-based estimators remain competitive with the GARCH-family models. These results are crucial for studies on volatility in cryptoassets where using the GARCH-type models is a standard. When the high-frequency data are not available, the range-based estimators, and the Garman-Klass estimator in particular, should be preferred as proxies for the true volatility process over the GARCH-type models, be it in the in-sample, more qualitative studies, or the forecasting, out-of-sample exercises.

Název v anglickém jazyce

Beyond GARCH in cryptocurrency volatility modelling: superiority of range-based estimators

Popis výsledku anglicky

Cryptoassets are extremely volatile with possible volatility jumps and infrastructure noise, making the estimation of true volatility process challenging. When the high-frequency data are not available, the true volatility needs to be estimated to be further studied or forecasted. The GARCH-family models have become a norm in the field. Here, we examine the performance of 6 GARCH-type specifications with 4 distributional assumptions and compare them with 4 non-parametric range-based models built on the daily ‘candles’. Our study focuses on five popular cryptocurrencies (Bitcoin, Ethereum, BNB, XRP, and Dogecoin) between 1 July 2019 and 30 September 2022, utilizing Binance 5-minute data for realized measures as the high-frequency estimators of the true volatility process. The results reveal that the Garman-Klass estimator clearly outperforms the GARCH-family models in all studied settings, and the other range-based estimators remain competitive with the GARCH-family models. These results are crucial for studies on volatility in cryptoassets where using the GARCH-type models is a standard. When the high-frequency data are not available, the range-based estimators, and the Garman-Klass estimator in particular, should be preferred as proxies for the true volatility process over the GARCH-type models, be it in the in-sample, more qualitative studies, or the forecasting, out-of-sample exercises.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50206 - Finance

Projekt

<a href="/cs/project/GA23-06606S" target="_blank" >GA23-06606S: Do hlubin decentralizovaných financí: Tržní mikrostruktura, behaviorální a psychologické vzorce</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

Applied Economics Letters

ISSN

1350-4851

e-ISSN

1466-4291

Svazek periodika

32

Číslo periodika v rámci svazku

21

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

8

Strana od-do

3113-3120

Kód UT WoS článku

001250706200001

EID výsledku v databázi Scopus

2-s2.0-85196257573