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Total Least Squares and Their Asymptotic Properties
Chuchel, Karel ; Pešta, Michal (advisor) ; Antoch, Jaromír (referee)
Tato práce se zabývá metodou úplně nejmenších čtverc·, která slouží pro odhad parametr· v lineárních modelech. V práci je uveden základní popis metody a její asymptotické vlastnosti. Je vysvětleno, jakým zp·sobem lze v konceptu metody využít neparametrický bootstrap pro hledání odhadu. Vlastnosti bootstrap od- had· jsou pak simulovány na pseudo náhodně vygenerovaných datech. Simulace jsou prováděny pro dvourozměrný parametr v r·zných nastaveních základního modelu. Jednotlivé bootstrap odhady jsou v rovině řazeny pomocí Mahalanobis a Tukey statistical depth function. Simulace potvrzují, že bootstrap odhad dává dostatečně dobré výsledky, aby se dal využít pro reálné situace.
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Stochastic claims reserving with double chain ladder
Javůrková, Tereza ; Pešta, Michal (advisor) ; Zichová, Jitka (referee)
This thesis deals with an important problem of insurance which is forecasting outstanding claims liabilities. It describes the Chain-Ladder method, the basic method for forecasting outstanding claims, and then it's extention to Double Chain-Ladder method. It also uses the number of reported claims for a beter estimate. The final forecast is calculated from the IBNR and RBNS reserves which are estimated separetly. Finly we aplly those methods to a real life dataset. The results shows differences betwen those two methods and different ways of programming. 1
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Multivariate Pareto distribution
Novytskyi, Oleksandr ; Mazurová, Lucie (advisor) ; Pešta, Michal (referee)
Title: Multivariate Pareto distribution Author: Oleksandr Novytskyi Department: Department of Probability and Mathematical Statistics (305. 32- KPMS) Supervisor: RNDr. Lucie Mazurová, Ph.D., Department of Probability and Mathematical Statistics (305. 32-KPMS) Abstract: This bachelor thesis focuses on three methods of constructing multiva- riate Pareto distribution, i.e. multivariate distribution, where marginal distributi- ons are univariate Pareto distributions. We provide survival and density functions for these models, which are used for the numerical studies and valuation of insu- rance product, specifically a yearly life annuity paid to each insured in the group, whose remaining life time is given by the multivariate Pareto distribution. Keywords: multivariate distribution, Pareto distribution, survival function, density, life annuity.
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Stochastic approaches to distributions of aggregated claims
Kirešová, Katarína ; Pešta, Michal (advisor) ; Mazurová, Lucie (referee)
Bachelor thesis deals with the calculation of the distribution of an aggregated claim: at first generally and afterward, focusing on life portfolio in an indivi- dual model. Three methods are compared: De Pril recursion, Kornya's method, and Panjer algorithm. We assess assumptions and derive formulae for particular methods. Methods are compared in terms of time complexity and precision of computations. We also deal with the calculation of the expected value and va- riance. Eventually, examples and simulations, which we used to determine the best method of calculation of the distribution of aggregated claim in an arbitrary portfolio, are preceded.
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Micro-level stochastic claims reserving
Rathouský, Marek ; Pešta, Michal (advisor) ; Vitali, Sebastiano (referee)
This thesis covers, in detail, theoretical background of micro-level stochastic model, which includes definition and properties of non-homogeneous Poisson process. This the- ory is then applied to real data generated by MTPL portfolio. Estimates of provisions under micro-level stochastic model are calculated using ordinary Monte Carlo simula- tion method. Results obtained from micro-level stochastic model are compared to Mack Chain-ladder estimates. 1
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Actuarial and Exposure-based Models for Hail Peril
Drobuliak, Matúš ; Pešta, Michal (advisor) ; Hlubinka, Daniel (referee)
Title: Actuarial and Exposure-based Models for Hail Peril Author: Bc. Matúš Drobuliak Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Michal Pešta, Ph.D., Department of Probability and Mathe- matical Statistics Abstract: This thesis covers an introduction to catastrophe modelling and focuses on statistical methods for extreme events. This includes methods of estimating parameters of claim distribution with a focus on probability weighted moments estimation technique. Furthermore, times series modelling, skew t-distribution, and two model clustering techniques are examined as well. This is later utilised in the practical application part of this thesis, which uses real data provided by an insurance company operating in the Czech Republic. Probability distribution fitting of large claims caused by hailstorms and Monte Carlo simulation of future losses are demonstrated later. Keywords: Catastrophe modelling, Hail peril, Probability weighted moments, Extreme events, ARMA-GARCH, Monte Carlo simulation iii
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Counterparty risk in reinsurance
Kohout, Marek ; Cipra, Tomáš (advisor) ; Pešta, Michal (referee)
The main goal of this Bachelor thesis is to present a survey of methods for cal- culating the required capital to cover the default risk of reinsurers in the frame- work of the regulatory system Solvency II in EU. The methods are based on so-called common shock principle which is preferred in the case of portfolios with a smaller number of heterogeneous counterparties (e. g. reinsurers). In difference from (Hendrych and Cipra, 2018) the case with flexible weights of particular reinsurers given by their LGD (loss given default) is considered. One discusses the results of extensive numerical study comparing particular methods. 1
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Claims reserve volatility and bootstrap with aplication on historical data with trend in claims development
Malíková, Kateřina ; Pešta, Michal (advisor) ; Zichová, Jitka (referee)
This thesis deals with the application of stochastic claims reserving methods to given data with some trends in claims development. It describes the chain ladder method and the generalized linear models as its stochastic framework. Some simple functions are suggested for smoothing the origin and development period coefficients from the estimated model. The extrapolation is also considered for estimation of the unobserved tail values. The residual bootstrap is used for the reparameterized model in order to get the predictive distribution of the estimated reserve together with its standard deviation as a measure of volatility. Solvency capital requirement in one year time horizon is also calculated. 1
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Estimations of risk with respect to monthly horizon based on the two-year time series
Myšičková, Ivana ; Houfková, Lucia (advisor) ; Pešta, Michal (referee)
The thesis describes commonly used measures of risk, such as volatility, Value at Risk (VaR) and Expected Shortfall (ES), and is tasked with creating models for measuring market risk. It is concerned with the risk over daily and over monthly horizons and shows the shortcomings of a square-root-of-time approach for converting VaR and ES between horizons. Parametric models, geometric Brownian motion (GBM) and GARCH process, and non-parametric models, historical simulation (HS) and some its possible improvements, are presented. The application of these mentioned models is demonstrated using real data. The accuracy of VaR models is proved through backtesting and the results are discussed. Part of this thesis is also a simulation study, which reveals the precision of VaR and ES estimates.
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Tests for Combination of Correlation Coefficients
Kulíšková, Michaela ; Hudecová, Šárka (advisor) ; Pešta, Michal (referee)
This bachelor thesis is focused on tests for correlation coefficients. Fundamental knowledge about correlation coefficient are reminded as well as tests for correlation coefficient based on estimated correlation coefficient. Then three main methods for combining more correlation coefficients - Fisher`s method, Linear combination test with Z-transformation and Hotelling transformation - are described, simulated and compared. These tests have several assumptions such as that k correlation coefficients are known as well as the range of random samples from which they were calculated plus it is assumed that these correlation coefficients are equal.
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