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首页> 外文期刊>European Journal of Management and Business Economics >Bitcoin and CEE stock markets: fresh evidence from using the DECO-GARCH model and quantile on quantile regression
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Bitcoin and CEE stock markets: fresh evidence from using the DECO-GARCH model and quantile on quantile regression

机译：比特币和CEE股票市场：新的证据来自使用Deco-Garch模型和分位数在分数回归

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Purpose This study examines the inter-linkages between Bitcoin prices and CEE stock markets (Hungary, the Czech Republic, Poland, Romania and Croatia). Design/methodology/approach The dynamic contemporaneous nexus has been analyzed using both the multivariate DECO-GARCH model proposed by Engle and Kelly (2012) and quantile on quantile (QQ) methodology proposed by Sim and Zhou (2015). Our study is implemented using the daily data spanning from 6 September 2012 to 12 August 2019. Findings First, the findings show that the average return equicorrelation across Bitcoin prices and CEE stock indices are positive, even though it is found to be time-varying over the research period shown. Second, the Bitcoin-CEE stock market association has positive signs for most pairs of quantiles of both variables and represents a rather similar pattern for the cases of Poland, the Czech Republic and Croatia. However, a weaker and primarily negative connectedness is found for Hungary and Romania, respectively. Furthermore, the interconnectedness between the co-movements in the Bitcoin market and stock returns changes significantly across quantiles of both variables within each nation, indicating that the Bitcoin-stock market relationship is dependent on both the cycle of the stock market and the nature of Bitcoin price shocks. Practical implications The evidence documented in this study has significant implications for divergent economic agents, including global investors, risk managers and policymakers, who would benefit from a comprehensive knowledge of the Bitcoin-stock market relationship to build efficient risk-hedging models and to conduct appropriate policy reactions to information spillover effects in different time horizons. Originality/value This paper is the first study employing both the multivariate DECO-GARCH model and QQ methodology to shed light on the nexus between Bitcoin prices and the stock markets in CEE countries. The DECO model uses more information to compute dynamic correlations between each pair of returns than standard dynamic conditional correlation (DCC) models, declining the estimation noise of the correlations. Besides, QQ approach allows us to capture some nuanced features of the Bitcoin-stock market relationship and explore the interdependence in its entirely. Therefore, the main contribution of this article to the related literature in this field is significant.
机译：目的本研究审查了比特币价格和CEE股市之间的联系方式（匈牙利，捷克共和国，波兰，罗马尼亚和克罗地亚）。设计/方法/方法使用SIM和周（2015年）提出的ZHALE和KELLY（2012）提出的多元化装饰GARCH模型和分位数（QQ）方法中的多变量解毒GARCH模型进行了分析了动态的同期Nexus。我们的研究是使用2012年9月6日至2019年8月12日的日常数据实施的。调查结果表明，比特币价格和CEE股票指数的平均返回等式是积极的，即使发现它被发现是时变的研究期显示。其次，比特币 - CEE股票市场关联对于两个变量的大多数成对数量具有积极的迹象，并且代表了波兰，捷克共和国和克罗地亚案件的相当类似的模式。然而，分别为匈牙利和罗马尼亚发现了较弱和主要的负关联。此外，比特币市场和股票的共同运动之间的相互连接在每个国家内的两个变量的量级中变化显着变化，表明比特币 - 股票市场关系取决于股票市场的周期和比特币的性质价格冲击。实际含义本研究中记录的证据对不同的经济特点具有重大影响，包括全球投资者，风险管理人员和政策制定者，他们将受益于比特币 - 股票市场关系的全面知识，以建立有效的风险套期保值模型和适当的行为对信息溢出效应在不同时间视野中的政策反应。原创性/价值本文是第一次采用多元化加入模型和QQ方法在比特币价格与CEE国家的股票市场之间的闪光。 DeCo模型使用更多信息来计算每对返回之间的动态相关性，而不是标准动态条件相关性（DCC）模型，拒绝相关性的估计噪声。此外，QQ方法使我们能够捕捉比特币股票市场关系的一些细节特征，并探讨其完全相互依存。因此，本文对该领域的相关文献的主要贡献显着。

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