8221 - TIME SERIES ANALYSIS OF ECONOMIC-FINANCIAL DATA
MM-LS - AFC-LS - CLAPI-LS - CLEFIN-LS - CLELI-LS - DES-LS - CLG-LS - M-LS - IM-LS - ACME-LS - EMIT-LS
Course taught in English
Go to class group/s: 31
The analysis of dynamic phenomena is extremely important in economic and financial studies. The aim of the course is to provide knowledge of the classical statistical procedures for time series analysis, but also of more modern techniques, based on dynamic linear models (or state-space models). The course intends to provide a solid methodological background and data-analysis skill, with lectures in the computer room and individual and team work. The software will be R, freely available at www.R-project.org. A new user-friendly R-package, dlm, has been developed for this course, for classical and Bayesian analysis of time series by dynamic linear models.
Part I. Classical analysis of univariate time series
Parte II. Dynamic linear models for time series analysis.
There are no mid-term exams. Instead, there are take-home assignments (about every two weeks), and a final individual or team work on the analysis of real data (about 40% of the final grade). Finally. there is a written and oral individual exam (about 60%).
- C. CHATFIELD, The Analysis of Time Series, Chapman & Hall/ CRC, 2004, 6th ed.
- G. PETRIS, S. PETRONE, P. CAMPAGNOLI. Dynamic Linear Models with R, Springer, New York (forthcoming).
Teaching material, lecture notes, data sets, examples, R code etc will be available on the learning space of the course.R is freely available at http://www.cran.r-project.org/