Advanced Theories in Finance
AG930
Course Pack
Reading
A useful textbook is by Wayne Ferson, 2019, Empirical asset pricing: Models and methods, MIT Press.
Cliff Asness at AQR provides a blog discussion that covers issues in linear factor models.
Hall, A.R., 2005, Generalized method of moments, Oxford University Press.
Hansen, B.E., 2021, Probability and statistics for economists, and Econometrics, Princeton University Press.
https://www.ssc.wisc.edu/~bhansen/
Nagel, S., 2021, Machine learning in asset pricing, Princeton University Press.
Review Papers
Fama, E.F., 2015, Cross-section versus time-series tests of asset pricing models, Working Paper, University of Chicago.
Available at ssrn.com.
Good introduction to testing linear factor models.
Individual Papers
Fama, E.F. and K.R. French, 2012, Size, value and momentum in international stock returns, Journal of Financial Economics, 105, 457-472.
Fama, E.F. and K.R. French, 2015, A five-factor asset pricing model, Journal of Financial Economics, 116, 1-22.
Fama, E.F. and K.R. French, 2016, Dissecting anomalies with a five-factor model, Review of Financial Studies, 29, 69-103.
Fama, E.F. and K.R. French, 2018, Choosing factors, Journal of Financial Economics, 128, 234-252.
All of the FF papers are available at ssrn.com.
Kan, R. and G. Zhou, 2017, Modeling non-normality using multivariate t: Implications for asset pricing, China Finance Review International, 7, 2-32.
Available of Raymond Kan’s web site.
http://www-2.rotman.utoronto.ca/~kan/research.htm
MacKinlay, A.C. and M.P. Richardson, 1991, Using generalized method of moments to test mean-variance efficiency, Journal of Finance, 46, 511-527.
Available of JSTOR.
Chou, P. and G. Zhou, 2006, Using bootstrap to test portfolio efficiency, Annals of Economics and Finance, 7, 217-249.
Available at:
http://apps.olin.wustl.edu/faculty/zhou/zpublications.html
Barillas, F. and J. Shanken, 2018, Comparing asset pricing models, Journal of Finance, 73, 715-754.
Available at:
https://onlinelibrary.wiley.com/doi/pdf/10.1111/jofi.12607
Assessment
The assessment for this class is 100% coursework.
The coursework is the completion of the problem set questions. The coursework will be submitted online by Thurs 27th March.
The aim of the problem set is to develop the following skills:
Undertaking empirical research
Evaluating and interpreting evidence
The written part of the report should be a maximum of 6 pages (Times New Roman font size 12, double spaced) but can be shorter. After the report should go all the tables and graphs. All of the answers to calculations must go either in Tables or graphs. Put each graph and table on a separate page. The tables and graphs should be presented in a similar fashion to research papers i.e. have a number, a title, and short explanation of what is in the table. The references go at the end of the report. The references should be double spaced and presented in the same way as a research paper.
When doing the problem sets, the material will be assessed on how well the questions have been addressed as well as the overall presentation. Answer the questions specifically. Do not include literature reviews or extensive discussion of research methods or Matlab code unless the question asks you for that.
Feedback will be provided through the use of an evaluation form. on how well these criteria have been met.
You are welcome to come and see me if you want further feedback of your assessment.
You are going to evaluate the performance of the Fama and French(2015) 5-factor model (FF5), and the alternative five-factor model of Hou, Mo, Xue and Zhang(2020) (HMXZ).
You are to select one group of U.S. test assets (either the 25 or 32 portfolios) from Ken French’s Data Library but not the size/BM portfolios
Problem Set Questions
Include a discussion of your results with respect to each question below.
1. Calculate summary statistics of the test assets and the factors in both the FF5 and HMXZ models.
2. Run the time-series regressions of the excess returns of the test assets on both factor models and report the results.
3. Use the Gibbons et al(1989) test to examine the mean-variance efficiency of both factor models.
4. Repeat the mean-variance efficiency tests using the Kan and Zhou(2017) approach, the GMM tests, and using the bootstrapping approach of Chou and Zhou(2006).
How sensitive are the results to the choice of empirical method?