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2015
- handle: 10670/1.n4u7c9
- hal: hal-01529755
- doi: 10.1016/j.mulfin.2015.03.001
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info:eu-repo/semantics/altIdentifier/doi/10.1016/j.mulfin.2015.03.001
Mots-clés
G20 Financial crisis Crisis Episodes Detection World Market Volatility Diversification Factor-DCC C - Mathematical and Quantitative Methods/C.C4 - Econometric and Statistical Methods: Special Topics/C.C4.C40 - General E - Macroeconomics and Monetary Economics/E.E6 - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook/E.E6.E60 - General F - International Economics/F.F3 - International Finance/F.F3.F30 - General G - Financial Economics/G.G1 - General Financial Markets/G.G1.G13 - Contingent Pricing • Futures Pricing G - Financial Economics/G.G3 - Corporate Finance and Governance/G.G3.G32 - Financing Policy • Financial Risk and Risk Management • Capital and Ownership Structure • Value of Firms • GoodwillCiter ce document
Julien Chevallier et al., « Geographical Diversification with a World Volatility Index », HAL-SHS : droit et gestion, ID : 10.1016/j.mulfin.2015.03.001
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Résumé
This paper proposes a new ‘World Volatility Index’, coined WVIX, by constructing the first index that approximates the aggregate volatility level of the G20 countries. The empirical analysis makes use of the factor dynamic conditional correlation model – with an automated methodology to detect the number of factors – in order to (i) sum up the information contained in the implied volatility indexes belonging to the US, the UK, the Eurozone, Japan and emerging countries, and (ii) examine the time-varying correlation between them. The results reveal that the WVIX evolves around 22%, but its activity can vary sharply depending on its exposure to various sources of geographical risks (e.g. the latest 2010-11 European debt crisis). Thus constructed as an early warning device, the methodology behind the WVIX can be replicated by market practitioners to datasets that better suit their needs.