Value-at-Risk (VaR) is an important instrument for risk assessment of financial time series. This estimation can be performed in different ways. One possibility is modelling with the aid of GARCH-models and copula functions, which is a very flexible approach. Within this bachelor's thesis the Copula-GARCH method is compared with classic VaR-estimation methods based on the stocks ATX and DAX.
Bachelor's Thesis are written in the course Seminar aus Statistik.
- The formal supervision is held by the lectorer of the seminar.
- The content-related supervisian can be performed by any member of IFAS with a doctoral degree.
Members of the IFAS with Phd. supervise Bachelor and Master theses in Statistics , preferably in the following areas and serve as examiners for the Master’s examination:
Modelling of High-Dimensional Data, Approximative Inference, Biostatistics and Modelling of Genomic Data
Computational Statistics, Cluster Analysis, Mixture Distributions
Experimental Design, Econometrics, Spatial Statistics
Risk Management, Experimental Design, Pension Systems
Time-Series Analysis, Analysis of Longitudinal Data, Survival Analysis, Bayes-Statistics, Generalized Linear Models
(Generalized) Linear Models, Factor Analysis
The collection of completed Bachelor's thesis can be found here:
Two Bachelor's Thesis graded as "very good" can be found here (in German)
Magdalena Leitner: Portfolio-VaR-Schätzung mittels bedingter Compula-GARCH Methode
(Portfolio-VaR-Estimation using a conditional Compula-GARCH Method
Daniel Dober: Distanz- und modellbasiertes Clustern eines phänotypischen Datensatzes
(Distance- and modelbased clustern of a phenotypic data set)
This bachelor's thesis conducts a cluster analysis of a phenotypic data set in order to detect class structures with the aid of "unsupervised learning". Therefore, the results of a distance-based cluster analysis, which is generally used for these problems, are compared with those of a model-based cluster analysis. The resulting class structure was used to identify genes having significant effects on the maturity of barley plants.