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Postgraduate Course: Empirical Asset Pricing (CMSE11509)

Course Outline
SchoolBusiness School CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate)
Course typeSandwich AvailabilityAvailable to all students
SCQF Credits20 ECTS Credits10
SummaryThis course covers a range of empirical studies of financial markets. The primary emphasis is on the asset pricing literature. The topics in this area include time-series return predictability, cross-sectional market anomalies, tests of single- and multi-factor risk-return models, consumption-based asset pricing. Other related areas, such as fund performance evaluation will be discussed as well.

The course covers several methodological aspects in empirical asset pricing such as the concept of stochastic discount factor (SDF), GMM-based estimation of parameters of asset pricing models, and modern mean-variance efficiency bounds. Most of asset pricing tests will be performed in both unconditional and conditional settings.
Course description The course is anticipated to run over the the summer period following the following outline:

- Introduction session
- Generalized Method of Moments
- Hansen-Jagannathan Bounds and Distance
- Time-Series Dynamics of Asset Returns
- Tests of CAPM
- Cross-Sectional Return Anomalies
- Tests of APT
- Tests of Consumption CAPMs, session 1
- Tests of Consumption CAPMs, session 2
- Fund Performance Evaluation
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements Students joining should have successfully completed Introductory Financial Economics and Econometrics courses. Those from other quantitative backgrounds could be considered following discussion and approval by the course organiser.
Information for Visiting Students
High Demand Course? Yes
Course Delivery Information
Academic year 2020/21, Available to all students (SV1) Quota:  None
Course Start Flexible
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 20, Dissertation/Project Supervision Hours 30, Summative Assessment Hours 15, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 131 )
Assessment (Further Info) Written Exam 0 %, Coursework 75 %, Practical Exam 25 %
Additional Information (Assessment) This course is comprised of three assessment components:
1. An individual report worth 30% of the overall course mark
2. An individual presentation worth 25% of the overall course mark
3. Group homework worth 45% of the overall course mark

Further information of each of these components is listed below:
1. Report: Within 48 hours students will have to write a referee report on an assigned empirical finance paper.
2. Presentation: Students will choose a topic from the reading list and prepare a one-hour presentation. At least one week before their presentation, they should meet with the course organiser to go over the preliminary outline of their talk. At that time, they should be at least 50% prepared for the task. The meeting time should be set with the course organiser in advance.
3. Homework: Three group assignments covering various topics of the course will be required.
Feedback Detailed feedback will be provided to students following all three different forms of assessment.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Understand and critically evaluate empirical asset pricing studies in finance.
  2. Develop methodological skills that you could efficiently use in their own research.
Reading List
Cochrane, J., 2005, Asset Pricing, Princeton University Press.
Ferson, W., 2019, Empirical Asset Pricing: Models and Methods, MIT Press

The papers marked with * are mandatory for reading, while those with ** also require a short written review. In addition, students will be required to use some statistical software package for their assignments and other potential empirical work. They can choose any application package they feel more comfortable with, but the most useful ones for this class are those that have good matrix-based computing capabilities, such as Matlab. They should make their software available by the end of the second week of classes.

1. Introduction
JC, Chapter 1
WF, Chapters 1, 3

2. Generalized Method of Moments
JC, Chapter 10-11
WF, Chapters 15-19
Hansen, L., 1982, Large sample properties of generalized method of moments estimators, Econometrica 50, 1029-1054.

3. Hansen-Jagannathan Bounds and Distance
JC, Chapter 5.6
WF, Chapter 10
Hansen, L., and R. Jagannathan, 1991, Implications of security market data for models of dynamic economies, Journal of Political Economy 99, 225-262.
Hansen, L., and R. Jagannathan, 1997, Assessing specific errors in stochastic discount factor models, Journal of Finance 52, 557-590.

4. Time-Series Dynamics of Asset Returns
JC, Chapter 20.1
WF, Chapter 32

Auto-correlation, Mean Reversion, Momentum, Volatility:
* Cohen, L., and A. Frazzini, 2008, Economic links and predictable returns, Journal of Finance 63, 1977-2011.
Daniel, K., and T. Moskowitz, 2016, Momentum crashes, Journal of Financial Economics 122, 221-247.
** Fama, E. and K. French, 1988, Permanent and temporary components of stock prices, Journal of Political Economy 96, 246-273.
Jegadeesh, N., and S. Titman, 1993, Returns to buying winners and selling losers: Implications for stock market efficiency, Journal of Finance 48, 65-91.
Keloharju, M., J. Linnainmaa, and P. Nyberg, 2016, Return seasonalities, Journal of Finance 71, 1557-1590.
Lo, A., and C. MacKinlay, 1990, When are contrarian profits due to stock market overreaction? Review of Financial Studies 3, 175-205.
Keim, D., 1983, Size-related anomalies and stock return seasonality: Further empirical evidence, Journal of Financial Economics 12, 13-32.
McQueen, G., M. Pinegar, and S. Thorley, 1996, Delayed reaction to good news and the cross-autocorrelation of portfolio returns, Journal of Finance 51, 889-919.
* Shiller, R., 1981, Do stock prices move too much to be justified by subsequent changes in dividends?, American Economic Review 71, 421-436.

Return Predictability with Information Variables:
** Ang, A., and G. Bekaert, 2007, Stock return predictability: Is it there?, Review of Financial Studies 20, 651-707.
Campbell, J. and M. Yogo, 2006, Efficient tests of stock return predictability, Journal of Financial Economics 81, 27-60.
Fama, E., and G. Schwert, 1977, Asset returns and inflation, Journal of Financial Economics 5, 115-146.
Fama, E., and K. French, 1988, Dividend yields and expected stock returns, Journal of Financial Economics 22, 3-25.
* Fama, E., and K. French, 1989, Business conditions and expected returns on stocks and bonds, Journal of Financial Economics 25, 23-49.
* Ferson, W., S. Sarkissian, and T. Simin, 2003, Spurious regressions in financial economics?, Journal of Finance 58, 1393-1413.
Goyal, A., and I. Welch, 2008, A comprehensive look at the empirical performance of equity premium prediction, Review of Financial Studies 21, 1455-1508.
Torous, W., R. Valkanov, and S. Yan, 2005, On predicting stock returns with nearly integrated explanatory variables, Journal of Business 77, 937-966.

5. Tests of CAPM
JC, Chapter 9.1
WF, Chapter 20.2

Ang, A., J. Chen, and Y. Xing, 2006, Downside risk, Review of Financial Studies 19, 1191-1239.
** Campbell, J. and T. Vuolteenaho, 2004, Good beta, bad beta, American Economic Review 94, 1249-1275.
Fama, E., and J. MacBeth, 1973, Risk, return, and equilibrium: Empirical tests, Journal of Political Economy 91, 607-636.
* Roll, R., 1977, A critique of the asset pricing theory┐s tests, Journal of Financial Economics 4, 129-176.
Savor, J., and M. Wilson, 2014, Asset Pricing: A tale of two days, Journal of Financial Economics 113, 171-201.
Shanken, J., 1985, Multivariate tests of the zero-beta CAPM, Journal of Financial Economics 14, 327-348.

* Harvey, C., 1989, Time varying conditional covariances in tests of asset pricing models, Journal of Financial Economics 24, 289-317.
Harvey, C., 1991, The world price of covariance risk, Journal of Finance 46, 111-157.
* Lewellen, J., and S. Nagel, 2006, The Conditional CAPM does not explain asset-pricing anomalies, Journal of Financial Economics 82, 289-314.
Nagel, S., and K. Singleton, 2011, Estimation and evaluation of conditional asset pricing models, Journal of Finance 66, 873-909.

6. Cross-Sectional Return Anomalies
JC, Chapter 12.2, 20.2
WF, Chapters 33-34

** Daniel, K., and S. Titman, 1997, Evidence on the characteristics of cross sectional variation in stock returns, Journal of Finance 52, 1-33.
Fama, E., and K. French, 1993, Common risk factors in the returns on stocks and bonds. Journal of Financial Economics 33, 3-56.
* Fama, E., and K. French, 2015, A five-factor asset pricing model, Journal of Financial Economics 116, 1-22. ┐
Ferson, W., S. Sarkissian, and T. Simin, 1999, The alpha factor asset pricing model: A parable, Journal of Financial Markets 2, 49-68.
Harvey, C., Y. Liu, and H. Zhu, 2016, ┐and the cross-section of expected returns, Review of Financial Studies 29, 5-68.
Hou, K., C. Xue, and L. Zhang, 2015, Digesting anomalies: An investment approach, Review of Financial Studies 28, 650-705.
Lewellen, J., S. Nagel, and J. Shanken, 2010, A skeptical appraisal of asset pricing tests Journal of Financial Economics 96, 175-194.

7. Tests of APT
JC, Chapter 9.4
WF, Chapters 12, 14

Asness, C., T. Moskowitz, and L. Pedersen, 2013, Value and momentum everywhere, Journal of Finance 68, 929-985.
* Chan, L., J. Karceski, and J. Lakonishok, 1998, The risk and return from factors, Journal of Financial and Quantitative Analysis 33, 159-187.
Chen, N., 1983, Some empirical tests of arbitrage pricing, Journal of Finance 38, 1393-1414.
* Chen, N., R. Roll, and S. Ross, 1986, Economic forces and the stock market: Testing the APT and alternative asset pricing theories, Journal of Business 59, 383-403.

Ang, A., and D. Kristensen, 2012, Testing conditional factor models, Journal of Financial Economics 106, 132-156.
** Ferson, W., and C. 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 returns, Journal of Finance 51, 3-54.
Ludvigson, S., and S. Ng, 2007, The empirical risk-return relation: A factor analysis approach, Journal of Financial Economics 83, 171-222.

8. Tests of Consumption CAPMs
JC, Chapters 2, 21
WF, Chapters 5, 13, 31

Complete Markets, Time Separable CCAPMs:
Hansen, L., and K. Singleton, 1983, Stochastic consumption, risk aversion, and the temporal behavior of asset returns, Journal of Political Economy 91, 249-265.
* Kocherlakota, N., 1996, The equity premium: It's still a puzzle, Journal of Economics Literature 34, 42-71.
* 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.
Julliard, C., and J. Parker, 2005, Consumption risk and the cross-section of expected returns, Journal of Political Economy 113, 185-222.

Long-Run CCAPMs
** Bansal, R. and A. Yaron, 2004, Risks for the long run: A potential resolution of asset pricing puzzles, Journal of Finance 59, 1481-1509.
Bansal, R., R. Dittmar, and C. Lundblad, 2005, Consumption, dividends, and the cross-section of equity returns, Journal of Finance 60, 1639-1672.
Hansen, L., J. Heaton, and N. Li, 2008, Consumption strikes back? Measuring long-run risk, Journal of Political Economy 91, 249-265.
Ferson, W., S. Nallareddy, and B. Xie, 2013, The out-of-sample performance of long-run risk models, Journal of Financial Economics 107, 537-556.

CCAPMs with Habit Persistence:
Boldrin, M., L. Christiano, and J. Fisher, 2001, Habit persistence, asset returns, and the business cycle, American Economic Review 91, 149-166.
** Campbell J. and J. Cochrane, 1999, By force of habit: A consumption-based explanation of aggregate stock market behavior, Journal of Political Economy 107, 205-251.
* Ferson, W. and G. Constantinides, 1991, Habit persistence and durability in aggregate consumption: Empirical tests, Journal of Financial Economics 29, 199-240.
Santos, T. and P. Veronesi, 2010, Habit formation, the cross section of stock returns and the cash-flow risk puzzle, Journal of Financial Economics 98, 385-413.

Incomplete Markets CCAPMs:
* Brav, A., G. Constantinides, and C. Geczy, 2002, Asset pricing with heterogeneous consumers and limited participation: Empirical evidence, Journal of Political Economy 110, 793-824.
Storesletten K., C. Telmer, and A. Yaron, 2004, Cyclical dynamics in idiosyncratic labor market risk, Journal of Political Economy 112, 695-717.
* Sarkissian, S., 2003, Incomplete consumption risk sharing and currency risk premiums, Review of Financial Studies 16, 983-1005.
Telmer, C., 1993, Asset-pricing puzzles and incomplete markets, Journal of Finance 48, 1803-32.

9. Fund Performance Evaluation
WF, Chapters 25-26

Amihud, Y., and R. Goyenko, 2013, Mutual fund┐s R2 as a predictor of performance, Review of Financial Studies 26, 667-695.
Carhart, M., 1997, On persistence in mutual fund performance, Journal of Finance 52, 57-82.
Chen, J., H. Hong, M. Huang, and J. Kubik 2004, Does fund size erode mutual fund performance? The role of liquidity and organization, American Economic Review 94, 1276-1302.
* Cremers, M., and A. Petajisto, 2009, How active is your fund manager? A new measure that predicts performance, Review of Financial Studies 22, 3329-3365.
* Daniel, K., M. Grinblatt, S. Titman, and R. Wermers, 1997, Measuring mutual fund performance with characteristic-based benchmarks, Journal of Finance 52, 1035-1058.
Kacperczyk, M., C. Sialm, and L. Zheng, 2008, Unobserved actions of mutual funds, Review of Financial Studies 21, 2379-2416.

Barras, L., O. Scaillet, and R. Wermers, 2010, False discoveries in mutual fund Performance: measuring luck in estimated alphas, Journal of Finance 65, 179-216.
** Ferson, W., and R. Schadt, 1996, Measuring fund strategy and performance in changing economic conditions, Journal of Finance 51, 425-461.
* Christopherson, J., W. Ferson, and D. Glassman, 1998, Conditioning manager alphas on economic information: another look at the persistence of performance, Review of Financial Studies 11, 111-142.
Christoffersen, S., and S. Sarkissian, 2009, City size and fund performance, Journal of Financial Economics 92, 252-275.
Additional Information
Graduate Attributes and Skills 1. Understand and critically evaluate empirical studies in finance.
2. Develop methodological skills that you could efficiently use in your own research.
KeywordsFinance,Asset Pricing,CAPM,Fund Performance,SDF
Course organiserProf Sergei Sarkissian
Course secretaryMiss Sophi Brunton
Tel: (0131 6)51 5011
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