|
|
Choice of the risk-aversion coefficient in optimization
Janásková, Eliška ; Kopa, Miloš (advisor) ; Lachout, Petr (referee)
Cílem této práce je studovat chování portfolia slo¾eného z daných akcií pro rùzné parametry averze k riziku. Nejprve popí¹eme, jaké vlastnosti by mìla splòovat vhodná míra rizika a poté uká¾eme, které z nich tyto vlastnosti opravdu splòují. Pøedstavíme Markowitzùv model a Mean-CVaR model, které slou¾í k optimalizaci portfolia. Z historických dat poté pomocí Mean-CVaR modelu urèíme pro dané akcie jejich zastoupení v optimálním portfoliu v závislosti na parametru averze k riziku a podíváme se, jak by si toto portfolio vedlo v následujících obdob ích. Na základì tìchto výpoètù budeme diskutovat výbìr vhodného parametru. Powered by TCPDF (www.tcpdf.org)
|
|
|
Evolutionary games and their applications to economic conflicts
Kuzmiak, Maroš ; Kopa, Miloš (advisor) ; Lachout, Petr (referee)
At the beginning of my Master's thesis we define basic terms such as payoff, strategy, best reply and Nash equilibrium. Furthermore, we introduce the population perspective, in which during a random meeting of a pair of players, these players interact according to their strategies and they receive payoffs. We define the criterion of evolutionary stability, which shows a link between payoffs in the game and strategy spreading among population. The most common description of this evolution is based on the replicator equations. We analyze their basic properties and examine the relationship between the stationary points of this system and the concepts of Nash equilibrium and evolutionary stability. In the following practical part, we apply the introduced theory to model the Cournot duopoly. Its aim is to analyze the model characteristics in terms of evolutionary stability and to determine the duopolist's behavior in the long run.
|
|
|
Stochastic optimization model of effective hydro energy usage
Janíková, Veronika ; Lachout, Petr (advisor) ; Kopa, Miloš (referee)
This thesis deals with the stochastic optimization problem of hydro reservoir manage- ment. External inflows and market electricity price are both considered as random inputs to the model, which is designed as joint chance constrained programming. The main goal of the optimization problem is to maximize the profit from hydro energy usage together with minimizing the cost of used water. The random component is modelled by suitable stochastic processes based on historical data and then approximated via scenarios. Sea- sonal deterministic model is another model that is presented in this thesis. This model helps appraise water stored in every each reservoir's compartment. The estimates of water values are based on dual variables. Finally, in the practical part the hydro reservoir ma- nagement problem is applied to the real hydro valley located on the Vltava river. This part also deals with an option of increasing the number of pumping stations in this particular hydro valley.
|
|
|
Importance Sampling methods in solving optimization problems
Zavřel, Lukáš ; Kozmík, Václav (advisor) ; Kopa, Miloš (referee)
Present work deals with the portfolio selection problem using mean-risk models where analysed risk measures include variance, VaR and CVaR. The main goal is to approximate solution of optimization problems using simulation techniques like Monte Carlo and Importance Sampling. For both simulation techniques we present a numerical study of their variance and efficiency with respect to optimal solution. For normal distribution with particular expected value and variance the values of parameters for sampling using Importance Sampling method are empirically deduced and they are consequently used for solving a practical problem of choice of optimal portfolio from ten stocks, when their weekly historical prices are available. All optimization problems are solved in Wolfram Mathematica program. Powered by TCPDF (www.tcpdf.org)
|
|
|
Monte Carlo methods in finance
Veselý, Václav ; Hurt, Jan (advisor) ; Kopa, Miloš (referee)
Monte Carlo simulation methods are very universal tool, which is applicable in many different cases. Major part of this work is devoted to variance reduction techniques and other improvements of Monte Carlo estimate. Practical examples of financial derivative pricing will be shown. 1
|
|
|
Spatial econometrics
Nývltová, Veronika ; Pawlas, Zbyněk (advisor) ; Kopa, Miloš (referee)
This thesis is devoted to the models that are suitable for modelling spatial data. For this purpose, random fields with finite index set are used. Based on the neighbourhood relationship a spatial weight matrix is introduced which describes spatial dependencies. A recognition and testing of spatial dependence is mentioned and it is applied for macroeconomic indicators in the Czech Republic. Spatial models originated from generalization of usual time series models are subsequently combined with linear regression models. The parameter estimators are derived for selected models by three different methods. These methods are ordinary least squares, maximum likelihood and method of moments. Theoretical asymptotic results are supplemented by a simulation study that examines the performance of estimators for finite sample size. Finally, a short illustration on real data is demonstrated. Powered by TCPDF (www.tcpdf.org)
|
|
|
Implied volatility modelling of options
Jahn, Daniel ; Kopa, Miloš (advisor) ; Hendrych, Radek (referee)
This text presents an analysis of constrained local polynomial estimation used to extract the implied volatility smile from options data. The optimization constraint derived from the state price density ensures the no arbitrage condition. The analysis contains an evaluation of the role of different parameters, such as the degree of the polynomial, kernel type and bandwidth, on the resulting IV smile. Two main approaches are suggested, one attempting to reflect the problematic case of the out-of-the- money options, the other focusing on producing a smooth state price density and a well-fitting IV smile. Powered by TCPDF (www.tcpdf.org)
|
|
|
Generalized Leontiev models
Hála, Petr ; Kopa, Miloš (advisor) ; Cipra, Tomáš (referee)
"his thesis de-ls with veontiev¡s input -nd output model of the e onomy -nd its potenti-l extensionsF et the eginning of the thesis -si formul-tions -nd h-r- teristi s of the veontiev¡s model -re summ-rized with emph-sis on its solv- ilityF sn the third -nd fourth h-pterD we present the simplest modi( -tions with -ddition-l restri tions or o je tive fun tionF sn the sixth h-pter - dyn-mi model with dis rete time is derivedD -g-in with emph-sis on the formul-tion of the onditions of existen e of solutionF "he l-st h-pter presents - sto h-sti gener-liz-tion of the veontiev¡s model using pro - ilisti onstr-ints -nd the s en-rio -ppro- hF "he thesis is - omp-nied y its own ex-mple of veontiev¡s sto h-sti modelF
|
|
|
Spectral risk measures in portfolio selection problems
Štefánik, Martin ; Kopa, Miloš (advisor) ; Zahradník, Petr (referee)
This thesis examines spectral risk measures. Spectral risk measures, as a subset of coherent risk measures, satisfy all the crucial and reasonable properties that a risk measure should have. A specific characteristic of a spectral risk measure is that it makes it possible for an investor to quantify the risk that arises due to holding a selected group of assets based on his or her personal attitude towards risk. The aim of this bachelor thesis is to discuss the properties of spectral measures of risk and their relations to commonly known measures of risk, but primarily to scrutinize its utilization in the portfolio selection problem. Based on monthly returns of stocks from chosen American stock exchanges we compute the optimal portfolios of stock indices for different risk aversion functions, and consequently we make an analysis of the results. Powered by TCPDF (www.tcpdf.org)
|
|
|
Scenario trees in stochastic programming problems
Malá, Alena ; Kopa, Miloš (advisor) ; Branda, Martin (referee)
This thesis deals with multi-stage stochastic linear programming and its ap- plictions in the portfolio selection problem. It presents several models of invest- ment planning, the emphasis is on the basic model with transaction costs and risk adjusted model for every investment level. Random returns entering the above models are modelled by the scenario trees which are generated using the moment- matching method. The thesis presents the optimal investment strategy for each model. It then examines distance of optimal values of objective functions in de- pendence on the nested distance of these generated trees. All calculations were performed using Mathematica software version 9. 1
|
guest ::
