Publication detail

Vacha L., Barunik J.: What does the wavelet analysis tell us about the Central European stock markets behavior during the crisis?

Author(s): doc. PhDr. Jozef Baruník Ph.D.,
Mgr. Lukáš Vácha Ph.D.,
Type: Article in collection
Year: 2009
Number: 0
Published in: Mathematical Methods in Economics Proceedings
Publishing place:
Keywords: wavelet analysis, multiresolution analysis, Central European stock markets, financial crisis
JEL codes:
Suggested Citation:
Grants: GAUK 46108: New Nonlinear Capital Markets Theories: Fractal, Bifurcational and Behavioral Approach
Abstract: In the proposed paper we would like to test for the different reactions of the stock markets to current financial crisis. We will focus on the Central European stock markets, namely Czech, Polish, Hungarian and compare them to German and U.S. benchmark stock markets.
Main method used for the analysis is the wavelet variance decomposition. Wavelet variance (or energy) decomposes a variance of stochastic process on scale basis and hence is important tool for analysing financial time series. The wavelet variance is a suitable alternative to the power spectrum analysis based on the Fourier transform. Such scale decomposition help us to track the different energies on the tested stock markets and their evolution in time.
The wavelet analysis of the tested stock markets shows different energies on scales during current financial crisis. Results indicate that each of the tested stock markets reacted differently to the current financial crisis. More important, Central European stock markets seem to have strongly different behaviour during the crisis. This may be in contradiction to common regional and liquidity similarities, which would indicate more common behaviour.


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