DRE 4011 Empirical Asset Pricing

DRE 4011 Empirical Asset Pricing

Course code: 
DRE 4011
Department: 
Finance
Credits: 
6
Course coordinator: 
Bruno Gerard
Product category: 
PhD
Portfolio: 
PhD Finance courses
Semester: 
2019 Autumn
Active status: 
Active
Teaching language: 
English
Course type: 
One semester
Introduction

This course is intended for PhD students in finance and related fields. The
course is an introduction to empirical research in finance. Topics include tests of asset pricing
models, return predictability in time-series and cross-section, conditional and unconditional tests.
The aim is to familiarize students with essential econometric methods and with important empirical
facts and areas of current research interest.

Learning outcomes - Knowledge
  • To understand the testable implications of asset pricing models
  • To understand the implications of time-varying expected returns on tests of asset pricing models
  • To appreciate the importance of international factors in determining asset returns in the data
  • To know the different potential sources of bias in tests of asset pricing models
Learning outcomes - Skills
  • To formulate empirical tests of asset pricing models using econometric techniques.
  • To construct test  of alternative asset pricing models
  • To be able to differentiate and assess the appropriatedness of cross-sectional, time series, or panel test of AP models
  • To select the appropriate ecometric techinque to address different sources of bias 
General Competence

To be able to:

  • critically review research papers at the forefront of empirical asset pricing, 
  • evaluate their strengths and weaknesses,
  • identify potential extensions, and
  • develop empirical strategies to adress the weaknesses and extensions
Course content

There is no textbook for the course. However students are strongly suggested to have their own copies of:

  1. Campbell, Lo and McKinlay, The Econometrics of Financial Markets, Princeton University Press, 1997.
  2. Cochrane, Asset Pricing (Revised), Princeton University Press, 2005.
  3. Hamilton, Times Series Analysis, Princeton University Press, 1994.
  4. Greene, Econometric Analysis, 6th Edition, Prentice Hall, 2007.

Some of the  topics that will be covered in class, time permitting and some of the readings. The final list of readiings and an updated sylllabus will be provided at the start of the course.

0.  The challenges of empirical work

  • Leamer, E., 1983, "Let's Take the Con Out of Econometrics," American Economic Review 73, pp: 31-43.
  • McCloskey, D., 1985, "The Loss Function has been Mislaid: The Rethoric of Significance Tests," American Economic Review 75, pp: 201-05.
  • Mayer, T., 2000, "Data Mining: A Reconsideration," Journal of Economic Methodology 7, pp: 183-94.
  • Lu, X., White H., 2014, "Robustness Checks and Robustness Tests in Applied Economics," Journal of Econometrics 178, pp: 194-206
  • Cochrane, J., 2011, "Presidential Address: Discount Rates," Journal of Finance 66, pp: 1049-109.

1. The Predictability of Asset Returns

  • Campbell, Lo and MacKinlay (1997) (CLM) Chapter 2
  • Baker, Malcolm and Jeffrey Wurgler, 2006, Investor Sentiment and the Cross-Section of Stock Returns, Journal of Finance, 61, 1645-1680.
  • Boudoukh, Jacob, Roni Michaely, Matthew Richardson and Michael G. Roberts, 2005, On the Im-portance of Measuring Payout Yield: Implications for Empirical Asset Pricing, Journal of Finance,forthcoming.
  • Fama, Eugene F., and Kenneth R. French, 1988, Dividend Yields and Expected Stock Returns, Journal of Financial Economics, 22, 3-27.
  • Fama, Eugene F., and Kenneth R. French, 1989, Business Conditions and Expected Returns on Stocks and Bonds, Journal of Financial Economics, 25, 23-49.
  • Goyal, Amit and Ivo Welch, 2006, A Comprehensive Look at the Empirical Performance of Equity Premium Prediction, Review of Financial Studies, forthcoming.
  • Lettau, Martin and Sydney Ludvigson, 2001, Consumption, AggregateWealth, and Expected Stock Returns, Journal of Finance, 56, 815-849.
  • Lewellen, Jonathan, 2004, Predicting Returns with Financial Ratios, Journal of Financial Eco- nomics 74, 209-235.

2. Present Value Relations

  • CLM Chapter 7.

3. The Cross-section of Expected Stock Returns

(a) Testing Methodologies: Time-series, cross-section and ML.
(b) Single and Multifactor Models
(c) Explaining Size and Book-to-Market
(d) Conditional Models
(e) Portfolio Formation

  • CLM Chapters 5 and 6
  • Campbell. J.Y., and T. Vuolteenaho, 2004, Bad Beta, Good Beta, AER 94, 1249-1275
  • Daniel and Titman, Testing factor model explanations of market anomalies, Working Paper.
  • Fama and French, 1992, The cross-section of expected stock returns, Journal of Finance 47, 427-465.
  • Fama, E. and J.D. MacBeth, 1973, Risk, return and equilibrium: empirical tests, Journal of Political Economy 81, 607-636.
  • Fama, E. and K. French, 1993, Common risk factors in the returns on stocks and bonds, Journal of Financial Economics 33, 1975-1999.
  • Ferson and Harvey, 1991, The variation of economic risk premiums, Journal of Political Economy 99, 385-415.
  • Jagannathan R., and Z. Wang, 1996, The conditional CAPM and the cross-section of expected stock returns, Journal of Finance 51, 3-53.
  • Lettau and Ludvigson, 2001, Resurrecting the (C)CAPM: A cross-sectional test when risk premia are time-varying, Journal of Political Economy 109, 1238-1287.
  • Lewellen, J., S. Nagel and J. Shanken, 2006, A skeptical appraisal of asset-pricing tests, working paper, Dartmouth University.
  • Li, Vassalou, and Xing, Sector investment growth rates and the cross section of equity returns, Journal of Business
  • Liew, J., and M. Vassalou, 2000, Can book-to-market, size and momentum be risk factors that predict economic growth, Journal of Financial Economics, 221-245.
  • McElroy, M.B, E. Burmeister, and K.D. Wall, 1985, Two estimators for the APT model when factors are measured, Economic Letters 19, 271-275.
  • Chen, Roll and Ross, 1986, Economic forces and the stock market, Journal of Business 59, 383-403.
  • Xing, Interpreting the value e¤ect through the q-theory: An empirical investigation, Forthcoming RFS

4.Testing the Consumption and Production CAPMs

  • CLM Chapter 8
  • Mehra, R. and E. Prescott, 1985, "The Equity Premium Puzzle," Journal of Monetary Economics 15, 145-161.
  • Breeden, D., Gibbons, M. and R. Litzenberger, 1989, "Empirical Tests of the Consumption Oriented CAPM," Journal of Finance 44, 231-262.
  • Cochrane, J., 1991, "Production-based Asset Pricing and the Link between Stock Returns and Economic Fluctuations," Journal of Finance 46, 207-234.
  • Lettau, M., and S. Ludvigson, 2001, "Resurrecting the (C)CAPM: A Cross- Sectional Test When Risk Premia are Time-Varying," Journal of Political Economy 109, 1238-1287.
  • Jagannathan, R. and Y. Wang, 2007, "Lazy Investors, Discretionary Consumption, and the Cross-Section of Stock Returns," Journal of Finance 62, 1623-1661.

5. International APM & FX

  • Cochrane, John H., Asset Pricing Ch. 20.1 "Foreign Exchange" p. 389-435.
  • Froot, Kenneth A ., and Richard H . Thaler, 1990, "Foreign Exchange," Journal of Economic Perspectives 4: 179-92.
  • De Santis, Giorgio and Bruno Gerard, 1998, "How big is the premium for currency risk?" Journal of Financial Economics 49, 375-411.
  • Lustig, Hanno, and Adrien Verdelhan, 2007, The cross section of foreign currency risk premia and consumption growth risk. American Economic Review 97, 89-117.
  • Lustig, Hanno, Nikolai L. Roussanov, and Adrien Verdelhan, 2011, "Common Risk Factors in Currency Markets," Review of Financial Studies 24, 3731-3777
  • Hassan, T., 2013, "Country Size, Currency Unions and International Asset Returns,"  Journal of Finance 68:2269-308.
  • Harvey, C., 1991, "The world price of covariance risk", The Journal of Finance 46, 111-57.
  • Campbell, J., de Medeiros, K., Viceira, L., 2010, "Global Currency Hedging," The Journal of Finance  65:87-121.
  • Menkhoff, Lukas, Lucio Sarno, Maik Schmeling, and Andreas Schrimpf, 2012, Carry trades and global foreign exchange volatility, The Journal of Finance 67, 681-718.

6. Bond Returns Predictability

  • Cochrane, John H., Asset Pricing Ch. 20.1 "Bonds" p. 389-435.
  • Fama, E., 1984, "The Information in the Term Structure," Journal of Financial Economics 13, 509-528.
  • Fama, Eugene F., 1986, "Term Premiums and Default Premiums in Money Markets." Journal of Financial Economics 17, 175-96.
  • Cochrane, John H. and Monika Piazzesi, Bond Risk Premia March 2005, American Economic Review 95:1, 138-160.  
  • Fama, Eugene F. and Robert R. Bliss, 1987, "The Information in Long-Maturity Forward Rates," American Economic Review 77, 680-92.
  • Piazzesi, Monika and Eric Swanson, 2008, "Futures Prices as Risk-Adjusted Forecasts of Monetary Policy," Journal of Monetary Economics 2008, 55, 677-691.
Teaching and learning activities

Reading research papers, presenting and discussing them in class, relating them to each others and to finance theory and econometrics

Software tools
EViews
Matlab
R
Rats
Stata
Additional information

-

Qualifications

Enrollment in a PhD programme is a general requirement for participation in PhD courses at BI Norwegian Business School.
External candidates are kindly asked to attach confirmation of enrollment in a PhD programme when signing up for a course. Other candidates may be allowed to sit in on courses by approval of the course leader. Sitting in on a course does not permit registration for the course, handing in exams or gaining credits for the course. Course certificates or confirmation letters will not be issued for sitting in on courses.

Required prerequisite knowledge

It is assumed that students are familiar with the material in FE I: Introduction to Asset Pricing. Knowledge of a software package such as SAS, RATS etc, or programming skills are required..

Exam categoryWeightInvigilationDurationGroupingComment exam
Exam category:
Activity
Form of assessment:
Presentation
Exam code:
DRE40111
Grading scale:
Point scale
Grading rules:
Internal examiner with external supervisor
Resit:
All components must, as a main rule, be retaken during next scheduled course
20No -Individual
Exam category:
Activity
Form of assessment:
Presentation and discussion
Exam code:
DRE40111
Grading scale:
Point scale
Grading rules:
Internal examiner with external supervisor
Resit:
All components must, as a main rule, be retaken during next scheduled course
20No -Individual
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
DRE40111
Grading scale:
Point scale
Grading rules:
Internal examiner with external supervisor
Resit:
All components must, as a main rule, be retaken during next scheduled course
30No 48 Hour(s)Individual Referee report
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
DRE40111
Grading scale:
Point scale
Grading rules:
Internal examiner with external supervisor
Resit:
All components must, as a main rule, be retaken during next scheduled course
30No3 Month(s)Individual Empirical research Project plan.
Exams:
Exam category:Activity
Form of assessment:Presentation
Weight:20
Invigilation:No
Grouping (size):Individual
Duration: -
Comment:
Exam code:DRE40111
Grading scale:Point scale
Resit:All components must, as a main rule, be retaken during next scheduled course
Exam category:Activity
Form of assessment:Presentation and discussion
Weight:20
Invigilation:No
Grouping (size):Individual
Duration: -
Comment:
Exam code:DRE40111
Grading scale:Point scale
Resit:All components must, as a main rule, be retaken during next scheduled course
Exam category:Submission
Form of assessment:Written submission
Weight:30
Invigilation:No
Grouping (size):Individual
Duration: 48 Hour(s)
Comment: Referee report
Exam code:DRE40111
Grading scale:Point scale
Resit:All components must, as a main rule, be retaken during next scheduled course
Exam category:Submission
Form of assessment:Written submission
Weight:30
Invigilation:No
Grouping (size):Individual
Duration:3 Month(s)
Comment: Empirical research Project plan.
Exam code:DRE40111
Grading scale:Point scale
Resit:All components must, as a main rule, be retaken during next scheduled course
Type of Assessment: 
Continuous assessment
Grading scale: 
ECTS
Total weight: 
100
Workload activityDurationType of durationComment student effort
Group work / Assignments144Hour(s)Specified learning activities (including reading).
Teaching36Hour(s)
Expected student effort:
Workload activity:Group work / Assignments
Duration:144 Hour(s)
Comment:Specified learning activities (including reading).
Workload activity:Teaching
Duration:36 Hour(s)
Comment:
Sum workload: 
180

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.