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Fear connectedness among asset classes

Julián Andrada-Félixa (), Adrian Fernandez-Perez () and Simon Sosvilla-Rivero ()
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Julián Andrada-Félixa: Department of Quantitative Methods in Economics, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain.
Adrian Fernandez-Perez: , Department of Finance, Auckland University of Technology, Auckland, New Zealand.

No 201703, IREA Working Papers from University of Barcelona, Research Institute of Applied Economics

Abstract: This study investigates the interconnection between five implied volatility indices representative of different financial markets during the period August 1, 2008-September 9, 2015. To this end, we first perform a static and dynamic analysis to measure the total volatility connectedness in the entire period (the system-wide approach) using a framework recently proposed by Diebold and Yilmaz (2014). Second, we make use of a dynamic analysis to evaluate both the net directional connectedness for each market and all net pair-wise directional connectedness. Our results suggest that slightly more than only 38.23%, of the total variance of the forecast errors is explained by shocks across markets, indicating that the remainder 61.77% of the variation is due to idiosyncratic shocks. Furthermore, we find that volatility connectedness varies over time, with a surge during periods of increasing economic and financial instability.

Keywords: Implied volatility indices; Financial market Linkages; Connectedness; Vector Autoregression; Variance Decomposition. JEL classification:C53; E44; F31; G15. (search for similar items in EconPapers)
Date: 2017-02, Revised 2017-02
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