Machine learning, Reinforcement learning in decision making. Wavelet analysis in finance and economics, Volatility, Spillovers.
Selected publications:
Growth cycle synchronization of the Visegrad Four and the European Union (with L. Hanus). Empirical Economics, , 2020, vol 58, pp. 1779-1795. journal link.
Comovement and disintegration of EU sovereign bond markets during the crisis. (with F. Smolik, J. Baxa ). International Review of Economics and Finance, 2019, , vol 64, pp. 541 - 556. journal link.
Do co-jumps impact correlations in currency markets? (with J. Barunik ). Journal of Financial Markets, 2018, vol 37, pp. 97-119. journal link, pdf
Asymmetric volatility connectedness on the forex market (with J. Barunik and E. Kocenda). Journal of International Money and Finance, 2017, vol 77, pp. 39-56. journal link, pdf
Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers (with J. Barunik and E. Kocenda). Journal of Financial Markets, 2016, vol 27, pp. 55-78. journal link, pdf
Modeling and forecasting exchange rate volatility in time-frequency domain (with J. Barunik and T. Krehlik). European Journal of Operational Research, 2016, vol. 251(1), pp. 329-340. journal link, pdf
Volatility spillovers across petroleum markets (with J. Barunik and E. Kocenda). The Energy Journal, 2015, vol. 36(3), pp. 309-329. journal link, pdf
Realized wavelet-based estimation of integrated variance and jumps in the presence of noise (with J.Barunik). Quantitative Finance, 2015, vol. 15(8), pp. 1347-1364. journal link, pdf
Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis (with J. Barunik). Energy Economics, 2012, vol. 34, pp. 241-247. journal link, pdf
The project will develop a new measures of dependence between economic variables, which will allow to study the frequency dependent dznamics of correlations in different quantiles of joint distribution.
The goal of the grant project is the construction and verification of a heterogeneous agent model which will be an extension of the model developed by Brock and Hommes. The new model will include a possibility to change the mood of the investors on the market. This modification will allow changing phases of optimism and pessimism and will enable generation of more realistic financial time series.