Národní úložiště šedé literatury Nalezeno 7 záznamů.  Hledání trvalo 0.01 vteřin. 
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.
Waveletová analýza trhů střední evropy během krize
Vácha, Lukáš ; Baruník, Jozef
V článku testujeme rozdílné reakce středoevropských trhů na finanční krizi pomocí waveletové analýzy
Smart Predictors in the Heterogeneous Agent Model
Vácha, Lukáš ; Baruník, Jozef ; Vošvrda, Miloslav
In this paper we extended the original model of heterogeneous agent model by introducting smart traders concept.
Sentiment Patterns in the Heterogeneous Agent Model
Vácha, Lukáš ; Baruník, Jozef ; Vošvrda, Miloslav
In this paper we extended the original model of heterogeneous agent model by introducting smart traders and changes in the agents sentiment to the model.
Wavelet Neural Networks Prediction of Central European Stock Markets
Vácha, Lukáš ; Baruník, Jozef
In this paper we apply neural network with denoising layer method for forecasting of Central European Stock Exchanges, namely Prague, Budapest and Warsaw.

Chcete být upozorněni, pokud se objeví nové záznamy odpovídající tomuto dotazu?
Přihlásit se k odběru RSS.