Evaluating Cryptocurrency Market Risk on the Blockchain: An Empirical Study Using the ARMA-GARCH-VaR Model

Article

Huang, Yongrong, Wang, Huiqing, Chen, Zhide, Feng, Chen, Zhu, Kexin, Yang, Xu and Yang, Wencheng. 2024. "Evaluating Cryptocurrency Market Risk on the Blockchain: An Empirical Study Using the ARMA-GARCH-VaR Model." IEEE Open Journal of the Computer Society. 5, pp. 83-94. https://doi.org/10.1109/OJCS.2024.3370603
Article Title

Evaluating Cryptocurrency Market Risk on the Blockchain: An Empirical Study Using the ARMA-GARCH-VaR Model

Article CategoryArticle
AuthorsHuang, Yongrong, Wang, Huiqing, Chen, Zhide, Feng, Chen, Zhu, Kexin, Yang, Xu and Yang, Wencheng
Journal TitleIEEE Open Journal of the Computer Society
Journal Citation5, pp. 83-94
Number of Pages12
Year2024
PublisherIEEE (Institute of Electrical and Electronics Engineers)
Place of PublicationUnited States
ISSN2644-1268
2644-125X
Digital Object Identifier (DOI)https://doi.org/10.1109/OJCS.2024.3370603
Web Address (URL)https://ieeexplore.ieee.org/abstract/document/10449426
Abstract

Cryptocurrency, a novel digital asset within the blockchain technology ecosystem, has recently garnered significant attention in the investment world. Despite its growing popularity, the inherent volatility and instability of cryptocurrency investments necessitate a thorough risk evaluation. This study utilizes the Autoregressive Moving Average (ARMA) model combined with the Generalized Autoregressive Conditionally Heteroscedastic (GARCH) model to analyze the volatility of three major cryptocurrencies—Bitcoin (BTC), Ethereum (ETH), and Binance Coin (BNB)—over a period from January 1, 2017, to October 29, 2022. The dataset comprises daily closing prices, offering a comprehensive view of the market's fluctuations. Our analysis revealed that the value-at-risk (VaR) curves for these cryptocurrencies demonstrate significant volatility, encompassing a broad spectrum of returns. The overall risk profile is relatively high, with ETH exhibiting the highest risk, followed by BTC and BNB. The ARMA-GARCH-VaR model has proven effective in quantifying and assessing the market risks associated with cryptocurrencies, providing valuable insights for investors and policymakers in navigating the complex landscape of digital assets.

KeywordsGARCH; VaR; market risk; cryptocurrency; data analysis
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020460403. Data security and protection
Byline AffiliationsFujian Normal University, China
Fuzhou Polytechnic, China
National Sun Yat-Sen University, Taiwan
Minjiang University, China
School of Mathematics, Physics and Computing
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