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
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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Journal Article: Fear connectedness among asset classes (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:ira:wpaper:201703
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