An Econometric Study on Volatility Clusters, Dynamic Risk Return Relationship, and Asymmetry in Bitcoin Returns

Q2 Business, Management and Accounting

Business Perspectives and Research Pub Date : 2023-12-20 DOI:10.1177/22785337231208300

Vandana Dangi

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Abstract

The most sought-after cryptocurrency sector is facing dicey environment in India due to stringent ideology of its government that put Indian investors in dilemma in envisaging this sector as a virtuous investment avenue. The investors are very curious for this sector and their curiosity aroused the need for its evaluation in terms of risk-return dynamics in contemporary scenario. The present study is an endeavor to econometrically explore volatility clusters, dynamic risk return relationship, and asymmetry in Bitcoin return series covering the period from August 2010 to February 2022. The results of Augmented Dickey–Fuller test, Ng–Perron tests, Ljung Box Q test, Engle’s ARCH, and White test asserted that the Bitcoin return series is stationary and has apparent volatility clusters in it. The estimates from GARCH-M model confirmed the absence of risk return relationship and the estimates from ARMA-EGARCH model confirmed the presence of asymmetry (leverage effect) in Bitcoin return series. However, the results of ARMA-TARCH model confirmed the absence of asymmetry in the series and further diagnostic checking asserted that ARMA- TARCH model is the best fitted model. These estimations may help the investors in comprehending risk-return dynamics of investment in Bitcoins for framing better hedging strategy in contemporary scenario.

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关于波动性集群、动态风险回报关系和比特币回报不对称的计量经济学研究

在印度，最受追捧的加密货币行业正面临着严峻的环境，原因是印度政府严格的意识形态使印度投资者在将该行业视为良性投资渠道时陷入两难境地。投资者对该行业非常好奇，他们的好奇心促使人们需要对该行业在当代形势下的风险回报动态进行评估。本研究试图从计量经济学角度探讨 2010 年 8 月至 2022 年 2 月期间比特币回报序列中的波动群、动态风险回报关系和不对称问题。Augmented Dickey-Fuller 检验、Ng-Perron 检验、Ljung Box Q 检验、Engle's ARCH 检验和 White 检验的结果表明，比特币收益序列是静态的，并且具有明显的波动集群。GARCH-M 模型的估计值证实比特币收益序列不存在风险收益关系，ARMA-EGARCH 模型的估计值证实比特币收益序列存在非对称性（杠杆效应）。然而，ARMA-TARCH 模型的结果证实比特币收益序列中不存在非对称性，进一步的诊断检查断言 ARMA- TARCH 模型是最佳拟合模型。这些估计可能有助于投资者理解比特币投资的风险收益动态，从而在当前情况下制定更好的对冲策略。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Business Perspectives and Research Business, Management and Accounting-Business and International Management

CiteScore

5.00

自引率

0.00%

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期刊介绍： Business Perspectives and Research (BPR) aims to publish conceptual, empirical and applied research. The empirical research published in BPR focuses on testing, extending and building management theory. The goal is to expand and enhance the understanding of business and management through empirical investigation and theoretical analysis. BPR is also a platform for insightful and theoretically strong conceptual and review papers which would contribute to the body of knowledge. BPR seeks to advance the understanding of for-profit and not-for-profit organizations through empirical and conceptual work. It also publishes critical review of newly released books under Book Review section. The aim is to popularize and encourage discussion on ideas expressed in newly released books connected to management and allied disciplines. BPR also periodically publishes management cases grounded in theory, and communications in the form of research notes or comments from researchers and practitioners on published papers for critiquing and/or extending thinking on the area under consideration. The overarching aim of Business Perspectives and Research is to encourage original/innovative thinking through a scientific approach.