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Poslední úprava: doc. PhDr. Jozef Baruník, Ph.D. (18.09.2023)
The objective of the course is to introduce advanced methods for financial data. We will cover two main topics using machine learning including neural networks, recurrent networks, distributional networks and time varying parameter methods. Students will be able to use the modern financial econometric tools after passing this course. |
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Poslední úprava: PhDr. Petr Bednařík, Ph.D. (06.06.2020)
1. Beran, J. (1994): Statistics for Long - Memory Processes. New York, Chapman and Hall. 2. Percival, D. B., Walden, A. T. (2000), Wavelet Methods for Time series Analysis. Cambridge University Press. 3. Ramsey, J. B. (2002), Wavelets in economics and finance: Past and future. Studies in Nonlinear Dynamics & Econometrics, 3, 1. 4. Samorodinsky, G. (2006) Long Range Dependence, In Foundations and Trends in Stochastic Systems, Vol. 1, No. 3 163–257. 5. Aguiar-Conraria, L., Martins, M. M., & Soares, M. J. (2012). The yield curve and the macro- economy across time and frequencies. Journal of Economic Dynamics and Control. 6. Gencay, R., & Signori, D. (2015). Multi-scale tests for serial correlation. Journal of Econometrics, 184(1), 62-80. 7. + Lecture notes
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Poslední úprava: Mgr. Michaela Čuprová (07.06.2020)
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