Time Series Analysis

This course will cover practical time series forecasting techniques and consists of two parts. The first part focuses on the Box-Jenkins approach (ARIMA), including identification (selection) of the appropriate model, estimation of its parameters, and diagnostic checking of model adequacy. The second part of the course is on nonlinear models for time series, with emphasis on conditional volatility and ARCH models. By the end of the course, you will be able to apply these techniques to actual data, primarily financial and economic time series. 

Enrollment in this course is restricted to students who have officially declared the IFEP concentration, as reflected in their Stellic profile. If space allows, enrollment may be extended to additional students at a later date.