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Modeling multivariate volatility using wavelet-based realized covariance estimator
Baruník, Jozef ; Vácha, Lukáš
Abstract. Study of the covariation have become one of the most active and successful areas of research in the time series econometrics and economic forecasting during the recent decades. Our work brings complete theory for the realized covariation estimation generalizing current knowledge and bringing the estimation to the time-frequency domain for the first time. The results generalize the popular realized volatility framework by bringing the robustness to noise as well jumps and ability to measure the realized covariance not only in time but also in frequency domain. Noticeable contribution is brought also by the application of the presented theory. Our time-frequency estimators bring not only more efficient estimates, but decomposes the realized covariation into arbitrarily chosen investment horizons. Results thus bring better understanding of the dynamics of dependence between the stock markets.
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Comovement of Central European stock markets using wavelet coherence: Evidence from high-frequency data
Baruník, Jozef ; Vácha, Lukáš ; Krištoufek, Ladislav
In this paper, we contribute to the literature on international stock market comovement and contagion. 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 completely different way. Major part of economic time series analysis is done in time or frequency domain separately. Wavelet analysis can combine these two funda- mental approaches, so we can work in time-frequency domain. Using wavelet coherence, we have found very interesting dynamics of cross-correlations be- tween Central European and Western European stock markets. We analyze the high-frequency (5 minute) and low-frequency (daily) data of Czech (PX), Hungarian (BUX) and Polish (WIG) stock indices with a benchmark of German stock index (DAX) on the period of 2008-2009. Our findings provide possibility of a new approach to financial risk modeling.
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Modelování vkusu na finančních trzích
Vácha, Lukáš ; Vošvrda, Miloslav
Heterogeneous agents model with the stochastic forecasts formation is considered. Fundamentalists rely on their model employing fundamental information basis to forecast the next price period. Chartists determine whether current conditions call for the acquisition of fundamental information in a forward looking manner rather than relying on the past performance. This paper shows an influence of the mood change on the financial market structure. This feature is simulated by changing of the forecast structure trend.
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