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Modeling the volatility of cryptocurrencies: an empirical application of stochastic volatility models

This paper compares a number of stochastic volatility (SV) models for modeling and predicting the volatility of the four most capitalized cryptocurrencies (Bitcoin, Ethereum, Ripple, and Litecoin). The standard SV model, models with heavy-tails and moving average innovations, models with jumps, leve...

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Main Authors: Zahid, Mamoona, Iqbal, Farhat
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2020
Online Access:http://journalarticle.ukm.my/15201/1/ARTIKEL%2025.pdf
http://journalarticle.ukm.my/15201/
http://www.ukm.my/jsm/malay_journals/jilid49bil3_2020/KandunganJilid49Bil3_2020.html
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spelling my-ukm.journal.152012020-09-14T03:56:31Z http://journalarticle.ukm.my/15201/ Modeling the volatility of cryptocurrencies: an empirical application of stochastic volatility models Zahid, Mamoona Iqbal, Farhat This paper compares a number of stochastic volatility (SV) models for modeling and predicting the volatility of the four most capitalized cryptocurrencies (Bitcoin, Ethereum, Ripple, and Litecoin). The standard SV model, models with heavy-tails and moving average innovations, models with jumps, leverage effects and volatility in mean were considered. The Bayes factor for model fit was largely in favor of the heavy-tailed SV model. The forecasting performance of this model was also found superior than the other competing models. Overall, the findings of this study suggest using the heavy-tailed stochastic volatility model for modeling and forecasting the volatility of cryptocurrencies. Penerbit Universiti Kebangsaan Malaysia 2020-03 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/15201/1/ARTIKEL%2025.pdf Zahid, Mamoona and Iqbal, Farhat (2020) Modeling the volatility of cryptocurrencies: an empirical application of stochastic volatility models. Sains Malaysiana, 49 (3). pp. 703-712. ISSN 0126-6039 http://www.ukm.my/jsm/malay_journals/jilid49bil3_2020/KandunganJilid49Bil3_2020.html
institution Universiti Kebangsaan Malaysia
building Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
description This paper compares a number of stochastic volatility (SV) models for modeling and predicting the volatility of the four most capitalized cryptocurrencies (Bitcoin, Ethereum, Ripple, and Litecoin). The standard SV model, models with heavy-tails and moving average innovations, models with jumps, leverage effects and volatility in mean were considered. The Bayes factor for model fit was largely in favor of the heavy-tailed SV model. The forecasting performance of this model was also found superior than the other competing models. Overall, the findings of this study suggest using the heavy-tailed stochastic volatility model for modeling and forecasting the volatility of cryptocurrencies.
format Article
author Zahid, Mamoona
Iqbal, Farhat
spellingShingle Zahid, Mamoona
Iqbal, Farhat
Modeling the volatility of cryptocurrencies: an empirical application of stochastic volatility models
author_facet Zahid, Mamoona
Iqbal, Farhat
author_sort Zahid, Mamoona
title Modeling the volatility of cryptocurrencies: an empirical application of stochastic volatility models
title_short Modeling the volatility of cryptocurrencies: an empirical application of stochastic volatility models
title_full Modeling the volatility of cryptocurrencies: an empirical application of stochastic volatility models
title_fullStr Modeling the volatility of cryptocurrencies: an empirical application of stochastic volatility models
title_full_unstemmed Modeling the volatility of cryptocurrencies: an empirical application of stochastic volatility models
title_sort modeling the volatility of cryptocurrencies: an empirical application of stochastic volatility models
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2020
url http://journalarticle.ukm.my/15201/1/ARTIKEL%2025.pdf
http://journalarticle.ukm.my/15201/
http://www.ukm.my/jsm/malay_journals/jilid49bil3_2020/KandunganJilid49Bil3_2020.html
_version_ 1678593695231770624
score 13.211869

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