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We employ a wavelet approach and conduct a time-frequency analysis of dynamic correlations between pairs of key traded assets (gold, oil, and stocks) covering the period from 1987 to 2012. The analysis is performed on both intra-day and daily data. We show that heterogeneity in correlations...
Persistent link: https://www.econbiz.de/10010407524
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...
Persistent link: https://www.econbiz.de/10009229363
We employ a wavelet approach and conduct a time-frequency analysis of dynamic correlations between pairs of key traded assets (gold, oil, and stocks) covering the period from 1987 to 2012. The analysis is performed on both intra-day and daily data. We show that heterogeneity in correlations...
Persistent link: https://www.econbiz.de/10010515402
Persistent link: https://www.econbiz.de/10003442715
Persistent link: https://www.econbiz.de/10011625108
Persistent link: https://www.econbiz.de/10012219710
In the paper we test for the different reactions of stock markets to the current financial crisis. We focus on Central European stock markets, namely the Czech, Polish and Hungarian ones, and compare them to the German and U.S. benchmark stock markets. Using wavelet analysis, we decompose a time...
Persistent link: https://www.econbiz.de/10003891213
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Persistent link: https://www.econbiz.de/10011446589
This paper proposes an enhanced approach to modeling and forecasting volatility using high frequency data. Using a forecasting model based on Realized GARCH with multiple time-frequency decomposed realized volatility measures, we study the influence of different timescales on volatility...
Persistent link: https://www.econbiz.de/10011412440