Mutual volatility transmission between assets and trading places

IF 0.6 Q4 STATISTICS & PROBABILITY
Andreas Masuhr, Mark Trede
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引用次数: 0

Abstract

Abstract This article proposes a framework to model the mutual volatility transmission between multiple assets and multiple trading places in different time zones. The model is estimated using a dataset containing daily returns of three stock indices – the MSCI Japan, the EuroStoxx 50, and the S&P 500 – each traded at three major trading places: the stock exchanges in Tokyo, London, and New York. Strong volatility transmission effects can be observed between New York and Tokyo, whereas current volatility in New York mostly depends on past volatility in New York. For the assets in consideration, spillovers are strong across trading zones, but weak across assets, suggesting a close connection between market places but only a loose volatility link between international stock indices. Volatility impulse response functions indicate a long-lasting and comparably large response of volatility in Tokyo, whereas they suggest a quicker volatility decay in London and New York.
资产与交易场所之间的相互波动传导
摘要本文提出了一个框架来模拟不同时区多个资产和多个交易场所之间的相互波动传导。该模型使用包含三个股票指数(MSCI Japan、EuroStoxx 50和s&p 500)日收益的数据集进行估算,这三个指数分别在三个主要交易场所交易:东京、伦敦和纽约的证券交易所。在纽约和东京之间可以观察到强烈的波动传导效应,而纽约当前的波动主要取决于纽约过去的波动。就所考虑的资产而言,各贸易区之间的溢出效应很强,但各资产之间的溢出效应较弱,这表明各市场之间存在密切联系,但国际股指之间只有松散的波动联系。波动率脉冲响应函数表明东京波动率的响应时间较长且相对较大,而它们表明伦敦和纽约的波动率衰减更快。
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来源期刊
Dependence Modeling
Dependence Modeling STATISTICS & PROBABILITY-
CiteScore
1.00
自引率
0.00%
发文量
18
审稿时长
12 weeks
期刊介绍: The journal Dependence Modeling aims at providing a medium for exchanging results and ideas in the area of multivariate dependence modeling. It is an open access fully peer-reviewed journal providing the readers with free, instant, and permanent access to all content worldwide. Dependence Modeling is listed by Web of Science (Emerging Sources Citation Index), Scopus, MathSciNet and Zentralblatt Math. The journal presents different types of articles: -"Research Articles" on fundamental theoretical aspects, as well as on significant applications in science, engineering, economics, finance, insurance and other fields. -"Review Articles" which present the existing literature on the specific topic from new perspectives. -"Interview articles" limited to two papers per year, covering interviews with milestone personalities in the field of Dependence Modeling. The journal topics include (but are not limited to):  -Copula methods -Multivariate distributions -Estimation and goodness-of-fit tests -Measures of association -Quantitative risk management -Risk measures and stochastic orders -Time series -Environmental sciences -Computational methods and software -Extreme-value theory -Limit laws -Mass Transportations
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