University of Technology Sydney

25861 Empirical Asset Pricing

Warning: The information on this page is indicative. The subject outline for a particular session, location and mode of offering is the authoritative source of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.

Subject handbook information prior to 2024 is available in the Archives.

UTS: Business: Finance
Credit points: 6 cp

Subject level:


Result type: Grade and marks

There are course requisites for this subject. See access conditions.


The goal of this subject is to establish perspectives, approaches, tools and methods of independent thinking, analysis, and problem solving and their application to essential asset pricing topics. Topics include utility theory, portfolio theory, arbitrage pricing, equilibrium pricing, security prices' informational efficiency, and performance measurement.

For more information, contact your PhD supervisor.

Subject learning objectives (SLOs)

Upon successful completion of this subject students should be able to:
1. Understand fundamental probability concepts used in econometric analysis;
2. Describe key classical econometric assumptions and the effects of the violations of those assumptions;
3. Describe the principles of least squares analysis and the properties of least squares estimators;
4. Understand properties of variables observed in financial markets, such as stock prices and interest rates.
5. Combine finance theory and econometrics tools to design research on financial markets, in particular, developing, estimating and analysing least square regressions to study relations among financial variables;
6. Collect, interpret, and organize financial data;
7. Write programming codes for statistics/mathematics software, such as Matlab;
8. Interpret and analyse key statistics and diagnostics generated by the software;
9. Explain verbally and in writing implications of empirical results for finance theory; and
10. Collaborate with other students to study issues in financial markets using econometrics tools.

Teaching and learning strategies

The course focuses on learning fundamental principles of least squares analysis, the most commonly used methodology in econometrics. Understanding the concepts and developing econometrics intuition are very important to apply the knowledge to empirical research on financial markets. The course also covers the probability theory to help students build a rigorous foundation for learning econometrics. The course will deal with many examples of how least square analysis is used to study interesting issues in financial markets.

Lectures and lecture slides cover the main material. Students are required to attend the lectures. Lecture slides are based on the textbook and the recommended readings. Lecture slides will be posted on Blackboard. Students are encouraged to print out lecture slides and take notes on them in class. At the end of each lecture, students will solve quizzes (not graded) and discuss the answers.

Bi-weekly homework assignments are designed to help students understand the concepts and develop econometrics intuition. Reviews of lecture slides and the textbook are critical for solving the questions. Students are encouraged to discuss with one another for the assignments. The assignments will also be helpful to prepare for the final exam.

Students will conduct empirical research on financial markets in groups. Group members are expected to discuss potential topics for their projects. All members are also expected to contribute to the final report equally through the following activities: design empirical research, gather data, conduct least squares analyses, interpret the results, and discuss implications of the results. Therefore, rigorous understanding of the course materials and good teamwork are critical for successful projects.

There will be at least two lab sessions for learning Matlab. Matlab is a mathematics software, which is widely used in finance and economics and requires good knowledge of econometrics. Students are required to use the software to solve some of the assignment questions and conduct empirical analysis for the group project. Students need to study all materials covered in class for the final exam.


Assessment task 1: Class participation (Individual)*

Weight: 5%

*Note: Late submission of the assessment task will not be marked and awarded a mark of zero.

Assessment task 2: Practical issues presentation (Individual)*

Weight: 10%

*Note: Late submission of the assessment task will not be marked and awarded a mark of zero.

Assessment task 3: Paper presentation (Individual)*

Weight: 25%

*Note: Late submission of the assessment task will not be marked and awarded a mark of zero.

Assessment task 4: Critique report (Individual)

Weight: 30%

Assessment task 5: Team Project (Group)

Weight: 30%

Required texts

  • A Guide to Econometrics, Peter Kennedy, 6th Edition, 2008, Wiley-Blackwell
  • Introduction to Econometrics, Stock and Watson, 2nd Edition

Recommended texts

  • The Econometrics of Financial Markets, Campbell, Lo, and MacKinlay, 1996
  • Introductory Econometrics: a modern approach, Wooldridge, 3rd edition