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Institute of Information Theory and Automation
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Projects
Dept.: E
Duration: 2024
- 2026
The project will develop a new family of models for identification of tail risks in financial markets from possibly large datasets using deep learning algorithms. Our newly developed methods will allow us to revisit several classical problems in empirical asset pricing. We believe that the results will be of fundamental character and will open number of questions. Specifically, we aim to explore...
Dept.: E
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. Vast quantities of information available in every moment require improvement of the classical methodology, in order to understand correctly the...
Dept.: E
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. Although the previous literature is helpful in uncovering the origins of dependence at one of these dimensions in manz important economic problems, there exists no methodology being able to...
Dept.: E
Duration: 2014
- 2016
The aim of the research project is to analyze financial risk and market co-movements using novel econometric methods and their theoretically grounded modifications. The main focus will be on emerging European markets with respect to global developed markets, as well as important assets from commodities markets. Co-movements between the markets based on different data frequencies may potentially...
Dept.: E
Duration: 2014
- 2016
The ability of financial markets to bear risk is central to economic welfare and stability. Growth and economic wellbeing is inhibited if financial markets are unable to transfer resources efficiently from the suppliers of liquiditz to entrepreneurs. However, this proper functioning of financial markets has been distorted by levels of volatility considerably in excess of those implied by...
Dept.: E
Duration: 2013
- 2015
The project focuses on studying multivariate time-frequency dynamics of financial markets using spectral methods. First target is to formulate new spectral-based realized measure of variance and covariance using wavelets, which will be applied to measure the integrated volatililty and covolatility under the various types of dependent microstructure noise. The newly proposed estimators will also...