Syllabus
Software usage for the following applied methods in finance and insurance: generalized linear models, categorical data analysis, random effects models, panel/longitudinal data analysis, generalized estimating equations, bayes methods, bootstrap, Markov chain Monte Carlo, copulae, extreme observations and large claims analysis (GEV and POT methods).
Annotation
Software (mostly R, but Mathematica as well) in finance and insurance. Modeling financial, economic, and insurance processes.
Practical exercises and problems from finance and insurance, model testing, parameter estimation, prediction in stochastic models and their diagnostics. Computational intensive methods, copulae, and their application in finance and insurance.
Practice with databases. Requirements: Basics of statistical modeling.