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Correlations and Turbulence of the European Markets

Laurentiu Andrei (), Petre Brezeanu, Sorin-Marius Dinu, Tiberiu Diaconescu and Constantin Anghelache
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Sorin-Marius Dinu: Institute for Economic Forecasting, Romanian Academy
Constantin Anghelache: University of Economic Studies, Bucharest, Romania

Journal for Economic Forecasting, 2019, issue 1, 88-100

Abstract: This paper uses stock market data to compute the turbulence index at the European level. We also compute the dynamic matrix of correlations for all pairs of country indices in our sample. Running regressions of the turbulence index on dynamic correlations we attempt to identify the extent to which some particular pairs of correlations may influence the turbulence index more than others, on average. We can therefore infer that portfolios that contain the pairs of indices with the highest explanatory power will have higher exposure to systemic risk when compared with compares that do not contain the respective pairs.

Keywords: turbulence; dynamic correlations; MIDAS regression (search for similar items in EconPapers)
JEL-codes: G12 G15 (search for similar items in EconPapers)
Date: 2019
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Handle: RePEc:rjr:romjef:v::y:2019:i:1:p:88-100