Found 15 relevant results in 0.82s where lecturer="Paul Embrechts"
Poisson processes; renewal processes; Markov chains in discrete and in continuous time; some applications.
This course introduces methods from probability theory and statistics that can be used to model financial risks. Topics addressed include loss distributions, risk measures, extreme value theory, multivariate models, copulas, dependence structures, backtesting, and operational risk.
This course yields a mathematical introduction into the theory of extremes. Besides a derivationof the Fisher-Tippett theorem for sample maxima, it is also shown how the theory of point pro-cesses yields a methodological basis for the Peaks Over Threshold method. Some examplesof statistical data analysis for the modelling of extremes will also be discussed.
This course treats the following topics:(1) Basic Monte Carlo simulation: generating pseudo-random numbers from a variety of distributions.(2) Variance reduction techniques.(3) Statistical Methods and Simulation.(4) Simulation of Continuous-Time Models.Examples will mainly come from the realm of finance and insurance.
Probability and Statistics
Wahrscheinlichkeit und Statistik
- Diskrete Wahrscheinlichkeitsräume- Stetige Modelle- Grenzwertsätze- Einführung in die Statistik
This course introduces the basic concepts, techniques and tools of quantitative financial risk management. A main emphasis will be put on the application of these techniques to the regulatory framework of the Basel Committee of Banking Supervision (Basel II) and some aspects of insurance regulation under Solvency 2.
No description available.
Randomness and Risk
Zufall und Risiko
In this course we introduce the concepts of randomness and risk through several examples.
Risk Theory
Risikotheorie
This course gives a first introduction to insurance risk theory. It serves as a basis for later courses on non-life insurance mathematics, risk management (in finance) and reinsurance. Topics included are claim processes, models for claim frequency and severity, ruin theory, modelling of large claims.
The topics treated are:- A historic overview of financial risk management- Basel II (banking) and solvency 2 (insurance)- Risk mapping- Coherent risk measures- Value-at-Risk and beyond- Hedging as a risk management tool- Selected topics on market, credit and operational risk- Modelling extremal events- Some practical examples
Seminar on Financial and Insurance Mathematics: Operational Risk. Modeling Analytics.
Seminar über Finanz- und Versicherungsmathematik: Operational Risk: Modeling Analytics
In this student seminar the main probabilistic and statistical tools in use for the quantitative modeling of operational risk are reviewed. Operational Risk is defined as in the Basel II guidelines. The tools presented are mainly borrowed from acrtuarial science.
Seminar on Insurance and Financial Mathematics
Seminar über Versicherungs- und Finanzmathematik
The goal of this seminar is to present various stochastic methods for claims reserving.These methods enable to set adequate reserves for open claims and todetermine prediction errors of these estimators.
Stochastics (Probability and Statistics)
Stochastik
The following concepts are covered: probabilities, random variables, probability distributions, joint and conditional probabilities and distributions, law of large numbers, central limit theorem, descriptive statistics, statistical inference, parameter estimation, confidence intervals, statistical tests, two-sample tests, linear regression.
The aim of this course is to give a mathematical introduction to the modelling of extremes. Topics treated include: one-dimensional EVT, maximal domain of attraction, Peaks Over Threshold, regular variation (one-dimensional as well as more dimensional), multivariate extremes (componentwise approach), point processes methodology.