Institute of Information Theory and Automation

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Department of Econometrics

Publications ÚTIA: 

Department of Econometrics focuses on understanding and modelling important economic and financial problems like decision making of agents, asset pricing, understating interaction between agents, or recently understanding the economic impacts of pandemics. We offer solutions to these problems with the help of mathematical models as well as statistical methodologies. More recently, we utilize modern machine learning methods for decision-making problems and analyze high-dimensional data sets (big data). We particularly focus on understanding economic and financial problems, focusing on estimation of real-world data.

In our department, we cover topics such as Machine Learning/Statistical Learning, Dynamic networks and financial decision making, Dynamic quantile asset pricing models, Measurement of dependence between cyclical economic variables, High-frequency data analysis, Agent based models, Stochastic optimization and Macroeconomics.

Working Papers:

Selected Papers:


Organized conferences and workshops:

  • Haindorf workshop 2022, 2020, 2019, 2018, 2017, 2016. The series of joint workshops with Humboldt University organized in January are focused on networking activities of research groups of prof. Barunik and prof.Hardle and training PhD students in statistical techniques. We have enjoyed hosting several respected scholars who joined the workshops including Victor Chernozhukov (MIT), Oliver Linton (Cambridge), Bryan Graham (UC Berkeley), Qiwei Yao (LSE), Holger Dette (Bochum) and many visiting international scholars.
  • STAT of ML 2021, 2020, 2019, Prague. Economterics Department in cooperation with Humboldt-Universität zu Berlin and Faculty of Mathematics and Physics, Charles University in Prague organized a STAT of ML (Statistics of Machine Learning) conference held October 7-8, 2021.  
  • 2015 – 2020 Research Seminar Series – Jointly with Institute of Economic Studies we organize occasional small workshops for PhD students with invited international speakers, i.e. Eddie Gerba (LSE), Mattia Bevilaqua (LSE), Todorova (Bocconi).
  • FinMaP – Financial Distortions & Macroeconomic Performance 2015 Prague: 2nd general workshop of the consortium organized by Institute of Information Theory and Automation.
  • FinMaP – Financial Distortions & Macroeconomic Performance 2015 Mannheim: 3rd general workshop of the consortium co-organized by Institute of Information Theory and Automation.
  • 2015 Econophysics Colloquium: The 2015 annual meeting of international researchers that brings together interdisciplinary research as physicists, economists and practitioners to discuss statistical methods, quantitative measures, modelling, simulations, and computational issues was co-organized in Prague by Institute of Information Theory and Automation and Charles University.
2021-12-16 17:08

Department detail

Doc. PhDr. Jozef Baruník Ph.D.
PhDr. Jaromír Baxa Ph.D.
PhDr. František Čech Ph.D.
Mgr. Luboš Hanus
Mgr. Martin Hronec
Mgr. Lukáš Janásek
RNDr. Vlasta Kaňková CSc.
Prof. Ing. Evžen Kočenda Ph.D. DSc.
Prof. PhDr. Ladislav Krištoufek Ph.D.
Mgr. Dušan Križan
PhDr. Jiří Kukačka Ph.D.
Mgr. Josef Kurka
Prof. RNDr. Radko Mesiar DrSc.
Mgr. Lenka Nechvátalová
Mgr. Matěj Nevrla
Jan Šíla MSc.
Ing. Karel Sladký CSc.
RNDr. Martin Šmíd Ph.D.
Mgr. Ing. Martin Štěpánek Ph.D.
Mgr. Lukáš Vácha Ph.D.
Prof. Ing. Miloslav Vošvrda CSc.
Duration: 2019 - 2023
The recent availability of large digital finance datasets brings new challenges to quantitative finance. Many of the classical financial econometric or optimization models become inappropriate or intractable when applied to digital finance data.
Duration: 2019 - 2021
The goal of this Project is to study arbitrage opportunities on limit order markets with boundedly rational agents.
Duration: 2018 - 2020
Multi-objective stochastic programming problems correspond to economic situations in which economic process is simultaneously influenced by a random environment and a decision parameter selected with respect to multi-objective optimization problem depending on the probability measure.
Duration: 2017 - 2019
The project focuses on utilization of multifractal framework in finance and financial economics. Specifically, we focus on three main branches of research. First, we examine how occurrence of financial extreme events translates into multifractal properties of the time series. For this purpose, we utilize the cusp catastrophe theory and the log-periodic power-law model.
Duration: 2016 - 2018
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.
Duration: 2016 - 2018
The aim of this project is to model optimal dynamic behaviour of a risk-averse European carbon-emitting steel producer, to design and implement an algorithm solving the corresponding multi-stage optimisation problem and apply the model to a real-life steel company. A linear combination of mean profit and conditional value at risk will serve as a decision criterion; decision variables will includ