Risk Modeling in Insurance

Aims of the course

no description

Course syllabus

Stochastic processes: Morkov chains in discrete and continuous time, Poisson process, Brownian motion, Markov processes, martingales.

Stochastic modelling: loss distributions, aggregate loss distributions, models of risk, risk process, credibility theory, reinsurance, stochastic reserving methods.

Risk management in insurance industry. Measuring and modelling of risk: VaR, simulation. Measuring, modelling and managing credit risk.

Difference equations, univariate time series models, vector autoregression, cointegrated vector autoregression. Simultaneous equations regressions model.

Course director(s)