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Continuous wavelet transform and rolling correlation of European stock markets

Aviral Tiwari (), Mihai Ioan Mutascu () and Claudiu Albulescu ()

International Review of Economics & Finance, 2016, vol. 42, issue C, 237-256

Abstract: The purpose of this paper is to assess the level of co-movements, contagion and rolling correlation between the stock markets of the PIIGS and those of the UK and Germany. We thus resort to a novel time–frequency approach, namely the continuous wavelet transform, and we analyze the co-movements of the stock index returns at different frequency-scales. We also test the influence of different macroeconomic factors on stock markets co-movements at different time–frequencies. The wavelet analysis results show that, in the short-run, the correlation level is high only during financial distress episodes, while in the long-run, the co-movements are present for the entire analyzed horizon. In addition, at low-frequency levels, the PIIGS stock markets are more correlated with Germany than with the UK. An opposite result is obtained at high-frequency decomposition levels. We also discover that the stock markets' correlation does not increase after all crisis events and depends on the wavelet decomposition levels.

Keywords: Portfolio risk management; Co-movements; Wavelet transform; Rolling wavelet correlation; European stock markets (search for similar items in EconPapers)
JEL-codes: C3 F3 F4 G1 (search for similar items in EconPapers)
Date: 2016
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