Beyond GARCH in cryptocurrency volatility modelling: superiority of range-based estimators
The result's identifiers
Result code in 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>
Alternative codes found
RIV/00216208:11230/25:10514038
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Beyond GARCH in cryptocurrency volatility modelling: superiority of range-based estimators
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50206 - Finance
Result continuities
Project
<a href="/en/project/GA23-06606S" target="_blank" >GA23-06606S: Deep dive into decentralized finance: Market microstructure, and behavioral and psychological patterns</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Applied Economics Letters
ISSN
1350-4851
e-ISSN
1466-4291
Volume of the periodical
32
Issue of the periodical within the volume
21
Country of publishing house
GB - UNITED KINGDOM
Number of pages
8
Pages from-to
3113-3120
UT code for WoS article
001250706200001
EID of the result in the Scopus database
2-s2.0-85196257573