Risk Modeling in Insurance
course
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)
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