Work

Comovement of Central European stock markets using wavelet coherence: Evidence from high-frequency data

Year: 2011

Type: conference-paper

Abstract: In this paper, we contribute to the literature on international stock market comovement. The novelty of our approach lies in usage of wavelet tools to high-frequency financial market data, which allows us to understand the relationship between stock market returns in a different way. Major part of economic time series analysis is done in time or frequency domain separately. Wavelet analysis can combine these two fundamental approaches, so we can work in time-frequency domain. Using wavelet power spectra and wavelet coherence, we have uncovered interesting dynamics of cross-correlations between Central European and Western European stock markets using high-frequency data. Our findings provide possibility of a new approach to financial risk modeling.

Source: ASEP

Authors: Jozef Baruník, Lukáš Vácha, Ladislav Krištoufek

Institution: Czech Academy of Sciences

Language: English

Topic: Financial Risk and Volatility Modeling

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: green

Funder: Grantová Agentura České Republiky

Awards: Analysis of the Heterogeneous Agents Models in Finance, New Approaches to Monitoring and Forecasting Financial Markets

OpenAlex ID: W1545279469