This course introduces the mathematical and statistical foundations necessary for the study of time dependent sets, more commonly referred to as time series. The estimation of model parameters and the application of the models to forecasting constitute the main themes of the course. Specific topics include smoothing techniques, stationary and non-stationary stochastic processes, the study of autocorrelation, the standard autoregressive integrated moving average (ARIMA) models and time-varying heteroscedasticity models. This course prepares students for the Statistics for Risk Modeling (SRM) Exam offered by the Society of Actuaries and is one of the three courses participating in the University-Earned Credit (UEC) program with credit for the SRM exam

Prerequiisite: STAT4250 3 Credits