Mutual volatility transmission between assets and trading places

Masuhr Andreas and Trede Mark ()
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Masuhr Andreas: Department of Economics, Institute for Econometrics, University of Münster, Münster, Germany
Trede Mark: Department of Economics, Institute for Econometrics, University of Münster, Münster, Germany

Dependence Modeling, 2023, vol. 11, issue 1, 15

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.

Keywords: international volatility spillovers; copula-GARCH models; intra-day; volatility impulse responses (search for similar items in EconPapers)
JEL-codes: C32 C51 F37 G11 G15 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:demode:v:11:y:2023:i:1:p:15:n:1005

DOI: 10.1515/demo-2022-0155

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