Georgia Institute of Technology
College of Management

MGT 7061
Empirical Finance
Spring 2009

Instructor: Prof. Suzanne S. Lee

Office # 410
Email: suzanne.lee@mgt.gatech.edu
Tel: 404-894-4963
Fax: 404-894-6030
Office Hour: Tuesday after class

Syllabus (Tentative, Subject to Change)

Course Description

This Ph.D-level seminar course introduces students to various topics and methods in empirical research in
Finance. Students who master the course will acquire familiarity with a set of research topics and related
econometrics and financial database, through reading journal papers and understanding empirical
methodologies. The goal of this course is to learn how to become an “independent” empirical finance
researcher by developing a critical perspective on the literature and identifying research issues. No class
notes will be distributed. Students should be able to organize and develop research ideas on their own. This
course is meant to be difficult and demanding and requires extensive reading. Average students are
expected to spend 25+ hours per week outside of class. It is open to Ph.D. students in Finance and related
areas. The course is supported by T-square at http://t-square.gatech.edu.

Course Prerequisites

Students must have taken courses on advanced graduate-level probability and statistics, basic graduate-
level economics (micro, macro or both) and econometrics, investments at the graduate level (e.g. MGT
6078 or 6080), and derivative securities at the graduate level (e.g. MGT 6081): otherwise, my approval is
required via email to take the course. The course involves statistical / computational analysis. I presume
that students are familiar with programming with one of statistical packages such as SAS, S-Plus, Stata,
Matlab (recommended), Fortran, or C (++).

Class Meeting and Format

We meet once a week on Tuesday 3-6pm in Room 436. I will assign readings and who will present in the
upcoming weeks. You are expected to read much of the material before the class. The class will not follow
a lecture format, but a series of student presentations on papers and discussions.

Requirements and Grading

The course requirements are submission of summary reports of papers to be covered in every class,
professional presentations, class participations, “do-it-yourself” homework, final exam and a term paper
related to topics discussed in class. Your course grade will be determined by the following scheme. There
will be no differentiation in grading for Ph.D. students in Finance and other areas or master’s students to be
fair for everyone in class, assuming students meet the course prerequisites.

Summary reports 20%
Professional paper presentation 20%
Class participation (discussion) 20%
“Do-it-yourself” homework 20%
Final Exam 20%
Term paper 20%
Attendance 20%

Total 140%

References

There is no specific required textbook, but following books are references and some include papers to be
discussed.

The Econometrics of Financial Markets, by John Campbell, Andrew Lo and Craig MacKinlay, Princeton
University Press (strongly recommended)
Econometric Analysis, by William Green, Prentice Hall
Time Series Analysis, by James Hamilton, Princeton University Press
Analysis of Financial Times Series, by Ruey Tsay, Wiley Series in Probability and Statistics
Handbook of Financial Econometrics, edited by Yacine Ait-Sahalia and Lars Hansen, Elsevier Science

Detailed reading list of published papers and working papers to be discussed is attached. Students are
responsible for collecting all these reading articles through Georgia Institute of Technology library or
online search.

Paper Presentation and Summary Reports

On a rotational basis, students will be assigned to present and discuss papers in class. A professional
presentation is desired. Each presentation should cover the motivation of the paper, why one should care
about the topic, empirical methods used, contribution of the paper to the literature, critical evaluation and
possible extension of the paper. Non-presenting students are also expected to read and actively participate
in the class seminar. All students are required to submit a one-page summary report on each paper to be
presented before every class starts.

Homework Assignments and Exams

Homework assignments will be given and should be reported. They involve data analysis and simulation.
Much of the data can be access through the WRDS database. Details of login account for the system will
be discussed in class. You will take final exams in class on the last day of the class. No make-up exams
will be provided. There is no exception to this rule to be fair to all students. A score of zero will be
assigned for each exam or homework that is missed.

Term Paper

Each student is required to write and submit a 15-20-page term paper on a topic approved by the instructor.
It is due on the last day of the class. Every student is expected to start thinking of the topic earlier in the
semester and submit a one-page proposal for approval before the spring break. The paper should include
introduction, model description, data description, empirical method, results and conclusion.

Reading List

1. Campbell, J., A. Lo and C. MacKinlay, 1997, "Chapter 1: Introduction" in The Econometrics of
Financial Markets. Focus on Sections 1.1 to 1.4 (read alone in the first week after class)
2. Fama, E., 1976, Foundations of Finance. New York: Basic Books. Chapters 1 and 2.
3. Fama, E., 1965, "The Behavior of Stock Prices," Journal of Business 38, 34-105.
4. Campbell, J., A. Lo and C. MacKinlay, 1993, "Chapter 2: Predictability of Asset Returns" in The
Econometrics of Financial Markets.
5. Conrad, J. and G. Kaul, 1988, "Time Variation in Expected Returns," Journal of Busines, 409-426.
6. Lo, A. and C. MacKinlay, 1988, "Stock Market Prices Do Not Follow Random Walks: Evidence from
Simple Specification Test," Review of Financial Studies 1, 41-66.
7. Fama, E. and K. French, 1988, "Dividend Yields and Expected Stock Returns," Journal of Financial
Economics 22, 3-26.
8. Fama, E. and K. French, 1989, "Business Conditions and Expected Returns on Stocks and Bonds,"
Journal of Financial Economics 25, 23-50.
9. Keim, D. and R. Stambaugh, 1986, "Predicting Returns in the Stock and Bond Markets," Journal of
Financial Economics 17, 357-390.
10. Merton, R., 1980, "On Estimating the Expected Return on the Market," Journal of Financial Economics
8, 323-362.
11. Jarque, C. and A. Bera, 1980, “Efficient Tests for Normality, Heteroskedasticity, and Serial
Independence or Regression residuals,” Economic Letters 6, 255-259
11. Autoregressive Conditional Heteroskedasticity With Estimates of the Variance of UK Inflation
Econometrica 50 (1982): 987-1008 (ARCH)
12. Bollerslev, T., 1986, "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and
Rates of Return," Review of Economics and Statistics 69, 542-547. (GARCH: Also in Journal of
Econometrics)
13. Campbell, J., A. Lo and C. MacKinlay, 1993, "Chapter 12: Nonlinearities in Financial Data" in The
Econometrics of Financial Markets. Sections 12.1 and 12.2 only.
14. French, K., Schwert, W. and R. Stambaugh, 1987, "Expected Stock Returns and Volatility," Journal of
Financial Economics 19, 3-30.

15. Hamao Y., R. Masulis and V. Ng, 1990, "Correlations in Price Changes and Volatility Across
International Stock Markets," Review of Financial Studies 3, 281-307.
16. Andersen, T., T. Bollerslev, F. Diebold, and H. Ebens, 2001, “The Distribution of Realized Stock
Return Volatility” Journal of Financial Economics 61, 43-76.
17. Andersen T.G. and T. Bollerslev, 1997, “Heterogeneous Information Arrivals and Return Volatility
Dynamics: Uncovering the Long-Run in High-Frequency Returns,” Journal of Finance 52, 975-1005
18. Karpoff, J., 1987, "The Relation between Price Changes and Trading Volume: A Survey," Journal of
Financial and Quantitative Analysis 22, 109-126.
94. Clark, P.K., 1973, “A Subordinate Stochastic Process Model with Finite Variance for Speculative
Prices,” Econometrica 41, 135-155
19. Gallant, R., Rossi, P. and G. Tauchen, 1992, "Stock Prices and Volume," Review of Financial Studies 5,
199-242.
20. Llorente, G., R. Michaely, G. Saar and J. Wang, 2002, “Dynamic Volume-Return Relation of
Individual Stocks” Review of Financial Studies 15, 1005-1048.
21. Tauchen, G. and M. Pitts, 1983, "The Price Variability-Volume Relationship on Speculative Markets,"
Econometrica 51, 485-505.
22. Andersen, T., 1996, "Return Volatility and Trading Volume: An Information Flow Interpretation of
Stochastic Volatility," Journal of Finance 51, 169-203.
23. Jones, C., G. Kaul and M. Lipson, “Transactions, Volume and Volatility,” Review of Financial Studies
7, 631-651.
24. Campbell, J., Grossman, S. and J. Wang, 1993, "Trading Volume and Serial Correlation," Quarterly
Journal of Economics 108, 905-939.
25. Gervais, S., R. Kaniel and D. Mingelgrin, 2001, “The High Volume Return Premium” Journal of
Finance 56, 877-920.
26. Harris, L., 1987, "Transactions Data Tests of the Mixture of Distributions Hypothesis," Journal of
Financial and Quantitative Analysis 22, 127-141.
27. Lo, A. and J. Wang, 2000, “Trading Volume: Definitions, Data Analysis and Implications of Portfolio
Theory” Review of Financial Studies 13, 257-300.
28. Campbell, J., A. Lo and C. MacKinlay, 1993, "Chapter 5: The Capital Asset Pricing Model" in The
Econometrics of Financial Markets.
29. Fama, E. and K. French, 1992, "The Cross-Section of Expected Stock Returns," Journal of Finance 47,
427-465.
30. M., 1982, "Multivariate Tests of Financial Models: A New Approach," Journal of Financial Economics
10, 3-27.
31. Bollerslev, T., R. Engle and J. Wooldridge, 1988, "A Capital Asset Pricing Model with Time Varying
Covariances," Journal of Political Economy 96, 116-131.
32. Harvey, C., 1989, "Time Varying Conditional Covariances in Tests of Asset Pricing Models," Journal
of Financial Economics 24, 289-317.

33. Chan, K.C., N. Chen and D. Hsieh, 1985, "An Exploratory Investigation of the Firm Size Effect,"
Journal of Financial Economics 14, 451-471.
34. Chen, N., 1983, "Some Empirical Tests of Arbitrage Pricing," Journal of Finance 38, 1393-1414.
35. Chen, N., Roll, R. and S. Ross, 1986, "Economic Forces and the Stock Market: Testing the APT and
Alternative Asset Pricing Theories," Journal of Business 59, 383-403.
36. Roll, R. and S. Ross, 1980, "An Empirical Investigation of the Arbitrage Pricing Theory," Journal of
Finance 35, 1073-1103.
37. Campbell, J., A. Lo and C. MacKinlay, 1993, "Chapter 6: Multifactor Pricing Models" in The
Econometrics of Financial Markets.
38. Chen, N., 1983, "Some Empirical Tests of Arbitrage Pricing," Journal of Finance 38, 1393-1414.
39. Chen, N., Roll, R. and S. Ross, 1986, "Economic Forces and the Stock Market: Testing the APT and
Alternative Asset Pricing Theories," Journal of Business 59, 383-403.
40. Roll, R. and S. Ross, 1980, "An Empirical Investigation of the Arbitrage Pricing Theory," Journal of
Finance 35, 1073-1103.
41. Goyal, A., and P. Santa-Clara, 2003, “Idiosyncratic Risk Matters!” Journal of Finance 58, 975-1008.
41. Campbell, J., A. Lo and C. MacKinlay, 1993, "Chapter 8: Intertemporal Equilibrium Models" in The
Econometrics of Financial Markets.
42. Fama, E., 1976, Foundations of Finance. New York: Basic Books. Chapter 5.
43. Fama, E., 1970, "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of
Finance 25, 383-417.
44. Fama, E., 1991, "Efficient Capital Markets: II," Journal of Finance 46, 1575-1617.
45. Campbell, J., A. Lo and C. MacKinlay, 1993, "Chapter 7: Present Value Relations" in The
Econometrics of Financial Markets.
46. Campbell, J. and R. Shiller, 1987, "Co-integration and Tests of Present Value Models," Journal of
Political Economy 95, 1062-1088.
47. Campbell, J., A. Lo and C. MacKinlay, "Chapter 3: Market Microstructure" in The Econometrics of
Financial Markets.
48. O’Hara, M., 2003, “Presidential Address: Liquidity and Price Discovery,” Journal of Finance 58, 13351354.
49. Acharya, V., and L. Pedersen, 2005, “Asset Pricing with Liquidity Risk,” Journal of Financial
Economics 77(2), 375-410.
50. Amihud, Y. and H. Mendelson, 1987, "Trading Mechanisms and Stock Returns: An Empirical
Investigation," Journal of Finance 42, 533-553.
51. Chordia, R., R. Roll, A. Subrahmanyam, 2000, “Commonality in liquidity” Journal of Financial
Economics 56, 3-27.

23. Chordia, T., R. Roll and A. Subrahmanyam, 2002, “Order Imbalance, Liquidity and Market Returns,”
Journal of Financial Economics 65, 111-130.
52. Cohen, K., Maier, S., Schwartz, R. and D. Whitcomb, 1986, The Microstructure of Securities Markets.
New Jersey: Prentice-Hall.
53. Foster, D. and S. Viswanathan, 1993, "Variations in Trading Volume, Return Volatility and Trading
Costs," Journal of Finance 48, 187-211.
54. Hasbrouck, J., 1988, "Trades, Quotes, Inventories and Information," Journal of Financial Economics 22,
229-252.
55. Hasbrouck, J., 1991, "Measuring the Information Content of Stock Trades," Journal of Finance 46, 176208.
56. Hasbrouck, J. and T. Ho, 1987, "Order Arrival, Quote Behavior, and the Return-Generating Process,"
Journal of Finance 42, 1035-1048.
57. Hasbrouck, J., and D. Seppi, 2001, “Common Factors in Prices, Order Flows and Liquidity,” Journal of
Financial Economics 59, 383-411.
58. Lee, C. and M. Ready, 1991, "Inferring Trade Direction from Intraday Data," Journal of Finance 46,
733-746.
59. Pastor, L. and R. Stambaugh, 2003, “Liquidity Risk and Expected Stock Returns,” Journal of Political
Economy 111, 642-685.
60. Wood, R., McInish, T. and K. Ord, 1985, "An Investigation of Transactions Data for NYSE Stocks,"
Journal of Finance 40, 723-738.
61. George, T., G. Kaul and M. Nimalendran, 1991, "Estimation of the Bid-Ask Spread and its
Components: A New Approach," Review of Financial Studies 4, 623-656.
62. Glosten, L. and L. Harris, 1988, "Estimating the Components of the Bid/Ask Spread," Journal of
Financial Economics 21, 123-142.
63. Harris, L., 1986, “A Transaction Data Study of Weekly and Intradaily Patterns in Stock Returns,”
Journal of Financial Economics 16, 99-117
63. Harris, L., 1991, "Stock Price Clustering and Discreteness," Review of Financial Studies 5, 389-415.
64. Hausman, J., Lo, A. and C. MacKinlay, 1991, "An Ordered Probit Analysis of Transaction Stock
Prices," Journal of Financial Economics 31, 319-379.
65. Roll, R., 1984, "A Simple Implicit Measure of the Effective Bid-Ask Spread in an Efficient Market,"
Journal of Finance 39, 1127-1139.
66. Thompson, R., 1985, "Conditioning the Return-Generating Process on Firm Specific Events: A
Discussion of Event Study Methods," Journal of Financial and Quantitative Analysis 20, 151-168.
67. Fama, E., Fisher, L., Jensen, M. and R. Roll, 1969, "The Adjustment of Stock Prices to New
Information," International Economic Review 10, 1-21.
68. Boehmer, E., Musumeci, J. and A. Poulsen, 1991, "Event-Study Methodology Under Conditions of
Event-Induced Variance," Journal of Financial Economics 30, 253-272.

69. Brown, S. and J. Warner, 1985, "Using Daily Stock Returns: The Case of Event Studies," Journal of
Financial Economics 14, 3-31.
70. Ait-Sahalia, Y., 1996, “Testing Continous-time Models of the Spot Interest Rate,” Review of Financial
Studies, 9, 385-426.
71. Ait-Sahalia, Y., 2004, “Disentangling Diffusion from Jumps,” Journal of Financial Economics, 74, 48772.
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Working paper, Department of Economics, Princeton University
73. Andersen, T.G., 1996, “Return Volatility and Trading Volume: An Information Flow Interpretation of
Stochastic Volatility”, Journal of Finance 51, 169-204
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76. Andersen, T., T. Bollerslev, F. Diebold, and C. Vega, 2003, “Micro Effects Macro Announcements:
Real-time Price Discovery in Foreign Exchange,” American Economic Review, 93, 38-62
77. Andersen, T., T. Bollerslev, P.H. Frederiksen, and M.O. Nielsen, 2006, “Continuous-Time Models,
Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns,” Working Paper,
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78. Andersen, T, L. Benzoni, and J. Lund, 2002, “An Empirical Investigation of Continuous-time Equity
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79. Bakshi, G., C. Cao, and Z. Chen, 1997, “Empirical Performance of Alternative Option Pricing Models”,
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80. Bakshi, G. C. Cao and Z. Chen, 2000, “Pricing and Hedging Long-Term Options”, Journal of
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81. Bakshi, G., N. Kapadia, and D. Madan, 2003, “Stock Return Characteristics, Skew Laws, and the
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91. Carr, P. and L. Wu, 2004, “Time-Changed Levy Processes and Option Pricing,” Journal of Financial
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