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dc.contributor.authorMagner, Nicolás
dc.contributor.authorLavin, Jaime F.
dc.contributor.authorValle, Mauricio
dc.contributor.authorHardy, Nicolás
dc.identifier.citationMagner, N., Lavin, J. F., Valle, M., & Hardy, N. (2021). The predictive power of stock market’s expectations volatility: A financial synchronization phenomenon. Plos one, 16(5),
dc.description.abstractWe explore the use of implied volatility indices as a tool for estimate changes in the synchronization of stock markets. Specifically, we assess the implied stock market’s volatility indices’ predictive power on synchronizing global equity indices returns. We built the correlation network of 26 stock indices and implemented in-sample and out-of-sample tests to evaluate the predictive power of VIX, VSTOXX, and VXJ implied volatility indices. To measure markets’ synchronization, we use the Minimum Spanning Tree length and the length of the Planar Maximally Filtered Graph. Our results indicate a high predictive power of all the volatility indices, both individually and together, though the VIX predominates over the evaluated options. We find that an increase in the markets’ volatility expectations, captured by the implied volatility indices, is a good Granger predictor of an increase in the synchronization of returns in the following month. Estimating, monitoring, and predicting returns’ synchronization is essential for investment decision-making, especially for diversification strategies and regulating financial
dc.description.sponsorshipUniversidad Adolfo Ibáñez, under the grant Internal Funds for Research 1154-2020 (Business School - Jaime F. Lavin).es
dc.publisherPLoS ONEes
dc.relation.ispartofseriesPLoS ONE;16(5)
dc.rightsAtribución-NoComercial-CompartirIgual 3.0 Chile (CC BY-NC-SA 3.0 CL)
dc.titleThe predictive power of stock market’s expectations volatility: A financial synchronization phenomenones

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Atribución-NoComercial-CompartirIgual 3.0 Chile (CC BY-NC-SA 3.0 CL)
Except where otherwise noted, this item's license is described as Atribución-NoComercial-CompartirIgual 3.0 Chile (CC BY-NC-SA 3.0 CL)