CSC 425 Time Series Analysis and Forecasting
Summary
The course will discuss methods for the analysis of financial time series. Students will learn about statistical methods for the analysis of financial data and the forecasting of future values, and will gain experience in modeling financial data.
The course will place great emphasis on application and empirical data analysis. The course will start reviewing basic concepts of linear time series analysis, such as stationarity and autocorrelation functions, and will present autoregressive and moving average models, and their generalizations. The second part will be focused on modeling conditional heteroschedasticity and market volatility using the ARCH and GARCH models. Alternative models for financial market volatility will be discussed. The course will also cover non-linear models, and non-parametric tests to address the non-linearity problem in financial time series.
Students will learn the statistical package SAS and use several SAS procedures for the analysis and modeling of time series.
Texts
Required Text
Analysis of Financial Time Series, 2nd ed., by Ruey S. Tsay. John Wiley & Sons (2005), ISBN: 0-471-69074-0.
Optional Text SAS for forecasting time series, 2nd ed., by John C. Brocklebank and David A. Dickey. SAS Institute Inc. & John Wiley & Sons (2005). ISBN: 0-471-39566-8
Grading
Grades will be posted on the DL web page http://dlweb.cs.depaul.edu.
The final grade has the following components:
Homework and Programming assignments (40%). Weekly assignments are due by midnight on Tuesdays. Assignments submitted after three days from the due date will not be accepted. Notice that a 10% point penalty will be applied for each overdue day.
Group project. (30%) There will be a group project due near the end of the quarter (due date to be arranged). Details will be provided later in class.
Final (30%). Tuesday November 21st, 2006 in class at 5:45-8:00 pm.
Students receiving more than 90% of possible points are guaranteed at least an A-, more than 80% at least a B-, more than 70% at least a C-, and more than 60% at least a D.
Prerequisites
CSC423 or consent of instructor.
Review of some statistical concepts: exploratory data analysis, correlation and regression analysis. Introduction to financial time series and their properties, distribution of returns. Introduction to SAS.
Linear Time series analysis and its applications. Manipulation and visualization in SAS.
Autoregressive and Moving Average models. The Box-Jenkins approach.
The ARMA models. Estimation and identification of correct ARMA model.
Discussion on model adequacy, including goodness of fit, residual analysis, forecasting accuracy and outlier detection.
Regression models with time series errors.
Conditional heteroschedastic models. Characteristics of volatility and ARCH effects
The GARCH model, Integrated GARCH, GARCH-M and E-GARCH models to analyze market volatility
Non linear models and their applications. Non-linearity tests.
Discussion on multivariate time series analysis – or other optional topics depending on the students’ interests.
This syllabus is subject to change as necessary during the quarter. If a change occurs, it will be thoroughly addressed during class, posted under Announcements in D2L and sent via email.
Evaluations are a way for students to provide valuable feedback regarding their instructor and the course. Detailed feedback will enable the instructor to continuously tailor teaching methods and course
content to meet the learning goals of the course and the academic needs of the students. They are a requirement of the course and are key to continue to provide you with the highest quality of teaching. The
evaluations are anonymous; the instructor and administration do not track who entered what responses. A program is used to check if the student completed the evaluations, but the evaluation is completely
separate from the student’s identity. Since 100% participation is our goal, students are sent periodic reminders over three weeks. Students do not receive reminders once they complete the evaluation.
Students complete the evaluation online in CampusConnect.
This course will be subject to the university's academic integrity policy. More information can be found at http://academicintegrity.depaul.edu/ If you
have any questions be sure to consult with your professor.
All students are expected to abide by the University's Academic Integrity Policy which prohibits cheating and other misconduct in student coursework. Publicly sharing or posting online any prior or current materials from this course (including exam questions or answers), is considered to be providing unauthorized assistance prohibited by the policy. Both students who share/post and students who access or use such materials are considered to be cheating under the Policy and will be subject to sanctions for violations of Academic Integrity.
All students are required to manage their class schedules each term in accordance with the deadlines for enrolling and withdrawing as indicated in the University Academic Calendar. Information on enrollment, withdrawal, grading and incompletes can be found at http://www.cdm.depaul.edu/Current%20Students/Pages/PoliciesandProcedures.aspx.
Students who feel they may need an accommodation based on the impact of a disability should contact the instructor privately to discuss their specific needs. All discussions will remain confidential.
To ensure that you receive the most appropriate accommodation based on your needs, contact the instructor as early as possible in the quarter (preferably within the first week of class), and make sure that
you have contacted the Center for Students with Disabilities (CSD) at:
Lewis Center 1420, 25 East Jackson Blvd.
Phone number: (312)362-8002
Fax: (312)362-6544
TTY: (773)325.7296