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

IEEE Open Journal of the Computer Society Pub Date : 2024-02-27 DOI:10.1109/OJCS.2024.3370603

Yongrong Huang;Huiqing Wang;Zhide Chen;Chen Feng;Kexin Zhu;Xu Yang;Wencheng Yang

{"title":"Evaluating Cryptocurrency Market Risk on the Blockchain: An Empirical Study Using the ARMA-GARCH-VaR Model","authors":"Yongrong Huang;Huiqing Wang;Zhide Chen;Chen Feng;Kexin Zhu;Xu Yang;Wencheng Yang","doi":"10.1109/OJCS.2024.3370603","DOIUrl":null,"url":null,"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.","PeriodicalId":13205,"journal":{"name":"IEEE Open Journal of the Computer Society","volume":"5 ","pages":"83-94"},"PeriodicalIF":0.0000,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10449426","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Open Journal of the Computer Society","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10449426/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

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.

查看原文本刊更多论文

评估区块链上的加密货币市场风险：使用 ARMA-GARCH-VaR 模型的实证研究

加密货币是区块链技术生态系统中的一种新型数字资产，最近在投资界引起了极大的关注。尽管加密货币越来越受欢迎，但由于其固有的波动性和不稳定性，有必要对其进行全面的风险评估。本研究利用自回归移动平均（ARMA）模型结合广义自回归条件异方差（GARCH）模型，分析了三种主要加密货币--比特币（BTC）、以太坊（ETH）和 Binance Coin（BNB）--在 2017 年 1 月 1 日至 2022 年 10 月 29 日期间的波动性。数据集包括每日收盘价，提供了市场波动的全面视图。我们的分析表明，这些加密货币的风险价值（VaR）曲线显示出显著的波动性，涵盖了广泛的回报范围。整体风险状况相对较高，其中 ETH 的风险最高，其次是 BTC 和 BNB。事实证明，ARMA-GARCH-VaR 模型可以有效量化和评估与加密货币相关的市场风险，为投资者和政策制定者驾驭数字资产的复杂局面提供有价值的见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IEEE Open Journal of the Computer Society

CiteScore

12.60

自引率

0.00%

发文量