Spring Quarter 2008
Business 41202: Analysis of Financial Time Series
Instructor: Ruey S. Tsay
Phone: 773-702-6750
Fax: 773-702-0458 (Please put my name on the cover
page)
HPC: 455
Lecture:
Bus 41202-01: Tuesdays 8:30 am to 11:30 am at C02, Harper Center
Bus 41202-81: Tuesdays 6:00 pm to 9:00 pm at Room 206, Gleacher Center
Teaching Assistant: Mr. David
Matteson
e-mail: matteson@uchicago.edu
(e-mail is the easiest way to contact TA)
Review Sessions:
BS41202-01: Thursdays 11:45 am to 1:15 pm at C03, Harper Center
BS41202-81: Saturdays 12:10 pm to 12:50 pm at Room 206, Gleacher Center
Syllabus of the course.
Course materials
Text: Analysis of Financial Time Series,
2nd Edition
Ruey S. Tsay,
Wiley, 2005.
ISBN:
0-471-69074-0
Data sets:
http://faculty.chicagogsb.edu/ruey.tsay/teaching/fts2/
or additional datasets will be posted for lectures and homework
assignments.
Lecture Notes:
Will be posted here the week before lecture.
Week 1: Lecture & Data sets used: m-ibm2607.txt Norwegianfire.txt
Week 2: Lecture & Data sets used: dgnp82.txt, q-unrate4807.txt
Week 3: Lecture & Data sets used: jnj.txt, q-earn-fdx.txt, power6.txt
d-sp55008.txt
Week 4: Lecture & Data sets used: m-intc7303.txt, vix08.txt
Week 5: Lecture & Data sets used: sp500.txt, m-ibm2697.txt
Additional lecture: out-of-sample forecast
Week 6: Lecture & Midterm
Week 7: Lecture & data sets used: m-ibmln2699.txt, d-geohlc.txt
Week 8: Lecture & data sets used: ibm-ads.dat, ibm-adsx.dat
Week 9: Lecture & data set used: d-ibmln98.dat
Week 10: Lecture & data sets used: q-gdpun.txt, d-vnq.txt, d-iyr.txt
Computing:
The main package used is R, which is free
from R-Project for Statistical Computing.
The most recent version of R is R2.6.2
The following
packages are needed in R:
(fBasics,
fSeries, fUtilities, tseries,
nnet, evir)
[In fact, install the package Rmetrics that contains all fxxxx packages needed.]
In Particular, Dr. Spencer Graves has created a R Companion to the textbook.
The package is called FinTS and can be download from CRAN of R similar to other packages. This is an ongoing project, but it has all data files used in the text and script files to perform most of the analyses in the first few chapters. You can also download the associated document from CRAN.
The class also needs Ox with G@RCH to fit various GARCH models.
[Students may use other packages or programs if they prefer. ]
R and Ox Installation:
Instructions
for download R and G@RCH: G@RCH-info (readme)
1. Download R here. [Click CRAN to select a mirror site.]
2. Download Ox here.
3. Download G@RCH
here.
4. Modified GarchOxModelling file
5. A corrected version of the
garchOxFit function.
(This part is from Prof. K.S. Chan of University of Iowa)
6. A (dated) tutorial of
G@RCH. (document)
Additional R scripts:
1. Forecasts with specified forecast origin: r-fore.txt
2. Recursive out-of-sample forecasts: r-backtest.txt
3. To estimate EGARCH models, use the following two modified files:
(a) GarchOxModelling_w file and (b) garchoxfit_w file [stored in the same directories
as the original ones.]
4. Moving window for volatility calculation: r-mvwindow.txt
5. Yang and Zhang's methof: r-yz.txt
6. Recursive out-of-sample nnet forecasts: r-backnnet.txt
7. Calculate VaR based on EVT: r-evtVaR.txt
8. Compute volatility of a given GARCH11 model: r-garch11v.txt
(including IGARCH(1,1) model for RiskMetrics).
9. Multivariate Ljung-Box statistics: mqstat.txt
10. Co-integration test: coint.txt
Instructions
for running R on PC. R-start
Demonstration: in class
Homework :
Assignment before class: Read Chapter 1 of the textbook.
HW1: hw1-08.pdf, Data sets used: d-aaplsp0007.txt, m-ibmsp7707.txt, m-tb3ms7708.txt
Solution: hw1s-08.pdf
HW2: hw2-08.pdf, Data sets used: m-dec1n10.txt, d-aapl9907.txt, q-unrate4807.txt
Solution: hw2s-08.pdf
HW3: hw3-08.pdf, Data sets used: w-mortg.txt, w-gs3yr0408.txt, m-dec1n10.txt, q-earn-fdx.txt
Solution: hw3s-08.pdf
HW4: hw4-08.pdf, Dara sets used: d-catvw0007.txt, m-ge4007.txt, d-exszus.txt
Solution: hw4s-08.pdf
HW5: hw5-08.pdf, Data sets used: d-ibmohlc0008.txt, m-unrate.txt, d-usuk0107.txt,
Solution: hw5s-08.pdf
Additional HW (self-study only): addhw-08.pdf (data sets available on the book web page).
Solution: hwextras.pdf
HW6: hw6-08.pdf, Data sets used: d-qcom9807.txt, d-mcd9807.txt
Solution: hw6s-08.pdf & R-output used in my solutions: hw6-08-R.txt
Office hour
: (a) Wednesdays 1:30 pm to 2:30 pm
(b) By appointment
(c) E-mail me at any time with questions.
(This is the easiest way to reach me.)
Midterm :
Week 6. Open book and notes!
Date: Campus session: May 6
Evening session: May 6
Lecture to follow after the exam.
Final Exam:
(New) at Exam week
Campus: Tuesday, June 10, 8:00 am to 11:00 am
Evening: Tuesday, June 10, 6:00 pm to 9:00 pm.
Open book and notes.
Grading:
35% midterm + 35% final exam + 30% homework,
where the scores of midterm, final exam and homework
assignments are normalized to be out of 100.
The GSB mandates a maximum class
grade point average of 3.33.
I rank the class based on the final scores using the above grading
formula and pick grade cutoffs so that I can get the highest class
GPA under the constraint.
Additional
Web Sites for data:
(a) Wharton WRDS at http://wrds.wharton.upenn.edu
(b) St Louis Fed at http://research.stlouisfed.org/fred2/
Feedback:
Mid-term: Exam ( including R output) & Solution
Final Exam: Eaxm & Solution
Time: June 10, Tuesday
Campus class 8:00 - 11:00 am
Evening class: 6:30 - 9:30 pm.
Old mid-term tests:
Year 2006: mideterm, ouput, and solutions
Year 2007: midterm, output,
and solutions
Final exam, output, and solutions