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

被引:0
|
作者
Huang, Yongrong [1 ]
Wang, Huiqing [1 ]
Chen, Zhide [1 ]
Feng, Chen [2 ]
Zhu, Kexin [3 ]
Yang, Xu [4 ]
Yang, Wencheng [5 ]
机构
[1] Fujian Normal Univ, Sch Comp & Cyberspace Secur, Fuzhou 350117, Peoples R China
[2] Fuzhou Polytech, Dept Informat Engn, Fuzhou 350108, Peoples R China
[3] Natl Sun Yat sen Univ, Dept Comp Sci & Engn, Kaohsiung 80424, Taiwan
[4] Minjiang Univ, Coll Comp & Data Sci, Fuzhou 350108, Peoples R China
[5] Univ Southern Queensland, Sch Math Phys & Comp, Toowoomba, Qld 4350, Australia
基金
中国国家自然科学基金;
关键词
GARCH; VaR; market risk; cryptocurrency; data analysis;
D O I
10.1109/OJCS.2024.3370603
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:83 / 94
页数:12
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