Measuring conditional correlation between financial markets' inefficiency

IF 3.2 Q1 BUSINESS, FINANCE Quantitative Finance and Economics Pub Date : 2023-01-01 DOI:10.3934/qfe.2023025
Fabrizio Di Sciorio, Raffaele Mattera, Juan Evangelista Trinidad Segovia
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引用次数: 0

Abstract

Assuming that stock prices follow a multi-fractional Brownian motion, we estimated a time-varying Hurst exponent ($ h_t $). The Hurst value can be considered a relative volatility measure and has been recently used to estimate market inefficiency. Therefore, the Hurst exponent offers a level of comparison between theoretical and empirical market efficiency. Starting from this point of view, we adopted a multivariate conditional heteroskedastic approach for modeling inefficiency dynamics in various financial markets during the 2007 financial crisis, the COVID-19 pandemic and the Russo-Ukranian war. To empirically validate the analysis, we compared different stock markets in terms of conditional and unconditional correlations of dynamic inefficiency and investigated the predicted power of inefficiency measures through the Granger causality test.

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衡量金融市场无效率之间的条件相关性
< >< >假设股票价格遵循多分数布朗运动,我们估计了一个时变Hurst指数($ h_t $)。赫斯特值可以被认为是一个相对波动的度量,最近被用来估计市场的无效率。因此,赫斯特指数提供了理论和实证市场效率之间的比较水平。从这一观点出发,我们采用多元条件异方差方法对2007年金融危机、2019冠状病毒病大流行和俄罗斯-乌克兰战争期间各种金融市场的低效率动态进行了建模。为了实证验证这一分析,我们比较了不同股票市场动态无效率的条件相关性和无条件相关性,并通过格兰杰因果检验考察了无效率措施的预测能力。
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来源期刊
CiteScore
0.30
自引率
1.90%
发文量
14
审稿时长
12 weeks
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