Business 41910: Time Series Analysis for Forecasting and Model Building

Autumn Quarter of 2008

Instructor: Ruey S. Tsay

Office: HPC 455
Tel:      773-702-6750
Fax:     773-702-0458
e-mail: ruey.tsay@ChicagoGSB.edu

Class: Thursday 8:30 am -- 11:30 am, starting September 25.
(No class in the Thanksgiving week.)

Office hour: (a) Wednesday, 11:00 am -- 12:00 noon.
                   (b) By appointment
You may e-mail me questions. E-mail is the easiest way
to make contact with me. I try to check the e-mail at least
once a day.

Teaching Assistant:
Mr. Paco Vazquez-Grande. Email: vazquez-grande@chicagogsb.edu

Text:  No textbook is used

Some reference books:
(a) Time Series Analysis: Forecasting and Control. Box, Jenkins and Reinsel (2008), 4rd Ed. Wiley   [First 9 chapters]
(b) Analysis of Financial Time Series, 2nd Edition, Tsay (2005), Wiley.
      [Chapters 2, 11, and 12]
(c) A Course in Time Series Analysis: Pena, Tiao and Tsay (2001), Wiley
(d) Time Series Analysis by State Space Methods: Durbin and Koopman (2001),
      Oxford University Press.
(e) Time Series Analysis: Hamilton (1994), Princeton University Press.
(f) Additional books are given in the course syllabus.
Some reference articles will also be given.

Course Syllabus.

Grading: Midterm 30% + Final Exam 40% + Homework 30%
where scores of each component are normalized to be out of 100.
No late homework assigments are accepted.

Lecture:

Week 1: Introduction, difference equations and linear models: lec1-08.pdf
lec2-08.pdf
data sets used: dexuseu.txt, gdp.txt, m2ns.txt, payems.txt, ppiaco.txt, unrate.txt

Week 2: Unit-root, ARIMA models, seasonal models, and aggregation:
lec3-08.pdf, lec4-08.pdf, and lec5-08.pdf

Week 3: Forecasting and model building: lec6-08.pdf, lec7-08.pdf
Week 4: Model specification and Estimation: lec8-08.pdf , lec9-08.pdf
Data set used: airpml.txt  
Week 5:   lec10-08.pdf
Week 6: Unit root and unit-root test: lec11-08.pdf data: vix08.txt
Week 7: State-Space Models and Kalman Filter: lec12-08.pdf
Week 8: MCMC Methods and Their Applications: lec13-08.pdf
Week 9: Conditional Heteroscedasticity: lec14-08.pdf
Week 10:  Duration Models: lec15-08.pdf (Note the time & room changes:
December 3, 1:30 pm to 4:30 pm at C24.)

Computing:
(1) R and SCA will be used for most analyses in class. SCA is available on
      all GSB machines. For R, the recent version 2.6  or higher is recommended.
(2) S-Plus is also used mainly for Kalman filtering.
(3) Students may use other packages, e.g., SAS, SPSS, MATLAB, 
      to answer hw questions.

Some commands for  SCA and R:
SCA-commands,  R-commands   

R code for EACF: eacfR.txt
R code for out-of-sample forecast: r-backtest.txt
R code for out-of-sample forecast error transform: r-foreden.txt

Homework Assignment:
Week 1: HW1  (due in one week; before the lecture). Solution.
Week 2: HW2 (due on October 9 before class). Solution.
Week 3: HW3 (due on October 16 before class). Data sets used:
bjsera.txt, dat4a.txt, dat4b.txt, dat4c.txt, dat4d.txt, dat4e.txt Solution
Week 4: HW4 (due on October 23 before class).
Week 7: HW5 (due on November 13 before class). Data sets:
m-ppiaco08.txt, w-m2.txt, ginterv.txt, m-cpiausl.txt
Week 8: HW6 (due on November 20 before class). Solution

Midterm: Week 6, October 30, 9:30 am - 11:30 am (Lecture before the test)  
Open books and notes. Solutions: exam08s

Final Exam: December 11, 8:00 am to 11:00 am

Zip: