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National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Combining multivariate volatility forecasts in portfolio optimization
 Šípka, Stanislav ; Hendrych, Radek (advisor) ; Hudecová, Šárka (referee)
The selection of the best-performing model is always a challenge when solving financial-economic problems. The final model might prove to be suboptimal even after a short time if the economic climate changes suddenly. This thesis aims to construct a final model capable of estimating large-scale covariance matrices via the utilization of time-varying weights. A set of multivariate GARCH mod- els to be used as an input in the final combined estimate is used to introduce a weighting scheme based on the metrics of risk-adjusted return of the individ- ual model portfolios. As large-scale modeling often faces problems connected with the underlying dimensionality, the composite likelihood approach to model parameter estimation is proposed as a solution and compared to the standard maximum likelihood and its SVD modification. The resulting weighted covari- ance matrix prediction is used to construct optimal portfolios and their properties are compared in an empirical study. The thesis is concluded by noting the real-life limitation and possible improvements of the defined investing methodology. 1
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Optimization problems with decision-dependent uncertainty
 Šípka, Stanislav ; Branda, Martin (advisor) ; Lachout, Petr (referee)
In practical optimization problems, uncertainty in parameter values is often present. This uncertainty needs to be taken in account when taking real-life de- cisions. Such issues, where the parameters of the problem lie in the sets with a given shape, can be solved by a type of linear optimization called robust linear optimization. Special cases of these robust optimization are problems, where the sets depend on decisions. In this thesis we will focus on these special problems. The main aim of this thesis is to reformulate the classical form of the problems, leading to formulations which can be solved by standard computational software. We will then use these formulations in numerical study, focusing on behavior of robust shortest path in graphs. 1
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