We focus on usefulness of machine learning techniques in economics and finance. At its core, one may perceive machine learning as a general statistical analysis that economists can use to capture complex relationships that are hidden when using simple linear methods. The ability of machine learning techniques to find relationships in data seems well-suited for financial applications. In a paper [1], we evaluate the economic gains of using deep learning methods for the construction of optimal portfolios.
The classical asset pricing frameworks is critical for asset valuation, they are all dominated by the expected utility models. Recently, many researchers find this idealization to be overly restrictive feeling that the expected utility model should be generalized. Collecting more and more data, and witnessing the shift in the behaviour of agents, new theoretical approaches need to be developed.
Consumers, firms, and countries are creating ever intensifying linkages in a world economy. Monitoring these intimate network connections between many economic variables is central for risk measurement and management, central bankers, and policy makers.
Rozhovory o stáži Otevřené vědy, vedené Janem Schierem, najdete na stránkách Otevřené vědy (volně přístupný) a Havlíčkobrodského Deníku (paywall). Studenti Jiří Wolker z
The Nonlinear Meeting 2021 is the 6th of a series of annual workshops focusing on nonlinear analysis and differential problems. This edition's common thread will cover theoretical topics on reaction-diffusion equations and dynamical systems with possible applications to biology or physics.
10.2. 2021 odešel náš dlouholetý a stálý zahraniční kolega Jaroslav Kautský. Ač zaměstnanec Flinders Univeristy v Adelaide, South Australia, v UTIA měl svůj stůl a své místo. Spoluautor mnoha publikací, ochotný rádce a glosátor světa okolo. V roce 2013 byly jeho zásluhy oceněny Akademií věd ČR Medailí Bernarda Bolzana za zásluhy v matematických vědách. Bude nám moc chybět.
Sergej Čelikovský was born 21 of January, 1961. He received his MSc. degree in Applied Mathematics from Optimal Control Department, Moscow State University in 1984 and his Ph.D. degree in Technical Cybernetics from the Czechoslovak Academy of Sciences in 1988. He was visiting researcher at University of Twente, Enschede 1996, Department of Mechanical and Automation Engineering, at Chinese University of Hong Kong 1998 and at CINVESTAV del I.P.N., Mexico 1998-2000. He has been Associate Member of the Centre for Chaos and Complex Networks, City University of Hong Kong since 2003.
Ve čtvrtek 26.11. 2020 středoškoláci - stážisté programu Otevřená věda - představili výsledky své práce na konferenci Otevřené vědy a jejich úsilí posoudila odborná porota. V kategorii I. vědní oblast - Neživá příroda se na 1. místě umístil tým vedený Dr. Ing. Janem Schierem z oddělení Zpracování obrazové informace - Marie Šimůnková a Jiří Wolker.
Ing. Stepan Papacek, Ph.D. received the scientific title "Associate Professor of Computer and Applied Mathematics" from the Rector of the Technical University of Ostrava (VŠB - TU Ostrava), prof. RNDr. Václav Snášel, CSc. on October 20, 2020.
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