DRE 4011 Empirical Asset Pricing
APPLIES TO ACADEMIC YEAR 2014/2015
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DRE 4011 Empirical Asset Pricing
Responsible for the course
Bruno Gerard, Charlotte Østergaard
Department
Department of Financial Economics
Term
According to study plan
ECTS Credits
6
Language of instruction
English
Introduction
Please note that this course will be revised before it is offered again.
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. This course will provide 6 ECTS credits.
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..
Learning outcome
Learning Outcomes:
To understand the testable implications of asset pricing models
To formulate empirical tests of asset pricing models using econometric techniques
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 be able to test amongst alternative asset pricing models
To understand small sample bias in tests of asset pricing models
Prerequisites
Admission to 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 admission to a PhD programme when signing up for a course with the doctoral administration. Other candidates may be allowed to sit in on courses by approval of the courseleader. Sitting in on courses does not permit registration for courses, handing in exams or gaining credits for the course. Course certificates or conformation letters will not be issued for sitting in on courses
Compulsory reading
Recommended reading
Course outline
Syllabus: Below lists the topics that will be covered in class, time permitting. Reading is provided
below.
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. Consumption CAPM
CLM Chapter 8
Computer-based tools
Learning process and workload
Workload (6 ECTS)
Lectures 30 hours
Specified learning activities (including reading) 130 hours
Total 160 hours
Examination
Your course grade will be based on the following activities and weights:
Paper presentations, summaries and discussion and class participation (40%).
Research proposal (30%)
72 hours take home exam (Referee report) (30%)
The course will be graded on the ECTS scale, A to F
Examination code(s)
DRE 40111 accounts for 100% of the grade in DRE 4011
Examination support materials
BI-approved exam calculator only
BI-approved exam calculator: TEXAS INSTRUMENTS BA II PlusTM.
Instruction manuals can only be used at examinations where “all exam aids” are allowed. In cases where a BI-approved calculator is allowed, only one – 1- such calculator can be brought to the examination premises. In addition one simple calculator can be brought.
Re-sit examination
Re-takes are only possible at the next time a course will be held. When the course evaluation has a separate exam code for each part of the evaluation it is possible to retake parts of the evaluation. Otherwise, the whole course must be re-evaluated when a student wants to retake an exam.
Additional information
Honour Code
Academic honesty and trust are important to all of us as individuals, and represent values that are encouraged and promoted by the honour code system. This is a most significant university tradition. Students are responsible for familiarizing themselves with the ideals of the honour code system, to which the faculty are also deeply committed.
Any violation of the honour code will be dealt with in accordance with BI’s procedures for cheating. These issues are a serious matter to everyone associated with the programs at BI and are at the heart of the honor code and academic integrity. If you have any questions about your responsibilities under the honour code, please ask.