Empirical Research  in Accounting and Finance:

Methods and Current Topics

 

MGMT 743   Wednesdays 1:00 – 4:00 Room A60 in Yale School of Management

 

 

Professors:

William N. Goetzmann

Jake Thomas

room:

103A ICF 46 Hillhouse Avenue

210, 55 Hillhouse Avenue

phone:

432-5950

432-5977

E-mail:

william.goetzmann@yale.edu

jacob.thomas@yale.edu

 

Teaching Assistant:  Vivian Wang E-mail: xw63@som.yale.edu

 

Course Description:  This doctoral-level course introduces students to topics and methods of empirical research in Accounting and Finance.   It addresses a set of current research topics in the field through reading and analysis of academic papers and  active empirical analysis. These topics include the risk and return of capital markets, the quantitative study of the equity risk premium,  forecasting markets and security prices with financial and accounting information,  valuation and the analysis of the cost of capital and  required rates of return on investment,  construction of  equity portfolios, performance  evaluation of investment managers.  It is recommended that doctoral students have Financial Economics I  before taking this course.  A strong background in statistics or econometrics is useful.  MBA’s and undergraduates with  statistical and/or econometric skills and an interest in the course should contact one of the instructors.

 

Prerequisites: Financial Economics I, or by permission of instructor. The course is open to Ph.D.’s from all departments, MBA candidates, Law School students and Yale undergraduates.  The assignments will require economic skills and knowledge as well as a willingness to work intensively with financial and accounting data.    The course demands a lot of time and students should plan accordingly.

 

Statistical Packages:  Students should use the statistical or econometric package that they are already familiar with.  If you are starting from scratch, a good package to use is the open sourceware R.  It works on all platforms.  Much of the data for analysis can be accessed through the ICF website and the WRDS system to which the ICF subscribes.  The Ibbotson software system is an important tool and can be accessed only through the SOM Citrix server.  This will require an SOM computer account for non-SOM students.  Please contact SOM student services bout this.

 

Readings:

 

Papers as specified in the syllabus.  Bold papers are expected to be thoroughly read for the class meeting. A useful text for the course is:  Campbell, John Y., Andrew W. Lo  and A. Craig MacKinlay, 1997, The Econometrics of Financial Markets.

 

Assignments :

 

Assignments:  Three of the assignments may be done in a group of three or less. Three assignments may be done individually in place of a research paper.  The three additional assignments or the term paper will be due one week following the last class meeting. For each assignment we expect only one or two pages of  clear explanation of what you did, and a table or two of results, plus one figure to illustrate the salient finding.  Clarity and brevity are appreciated – these are not research papers, although you may find something in the analysis that could lead to a term paper.  Come prepared with your group to discuss the results of your analysis to class with a table or a figure. 

 

 


 

#

Date

Topics

Assignment

Papers

1

1-19

Course overview and introduction to financial and accounting data for research.

·      Visit ICF website, find the WRDS system and acquire a password. Make sure you are approved for use on the SOM network for use of the Ibbotson software via Citrix.

·      Visit http://www.jstor.org/ and download relevant readings.

·      Visit http://www.ssrn.com/ and download relevant readings. (Follow known hyperlinks in the Word file. For others, try google.com)

·      Visit http://www.library.yale.edu/journals/ and download the relevant readings. ( If some readings are not available from the above source.)

·     Ibbotson, Roger G. and  Rex Sinquefield, “Stocks, bonds, bills and inflation,” Journal of Business, 49:1, (Jan,1976), 11-47.

·     Goetzmann, William N., Roger Ibbotson and Liang Peng, “A new historical database for the NYSE 1815 to 1925: performance and predictability,” Journal of Financial Markets, 4 (2001) 1-32.

·     Markowitz, Harry, 1959, Portfolio Selection, Cowles Foundation Monograph.  Scan in preparation for week 2.

2

1-26

The Efficient Market Hypothesis

Assignment: The Efficient Market Hypothesis

 

 

Do dividend yield ratios forecast the stock market?  Choose a market you are interested in from markets around the world and use OLS and or VAR methods to determine if these  variables forecast  returns at the one, three, five and ten year horizons. Test the profitability of a reasonable trading rule designed to exploit this pattern, making sure your analysis is truly out of sample.

 

Data for aggregate series can be found on the Ibbotson Encorr database or Datastream.

 

Is there autocorrelation in individual security returns  on a daily basis?  Choose an individual stock and look at the predictability of returns at the daily level. Report summary statistics and the results of a serial independence and trading rule test of your design.

 

·             Cowles, Alfred 1934, “Can stock market forecasters forecast?” Econometrica, 1 (3), 309-324.

·             Eugene F. Fama, 1965, “The Behavior of Stock-Market Prices”, The Journal of Business, Vol. 38, No. 1. (Jan., 1965), pp. 34-105.

·             Brown, Stephen J., William N. Goetzmann and Alok Kumar, 1998, “The Dow Theory: William Peter Hamilton’s track Record Reconsidered,” Journal of Finance, 53(4) 1311-1333, August.

·             Campbell, Lo and MacKinlay, Chapters 2 and 7.

·             Campbell, John Y. and Robert J.  Shiller, 1988, “The dividend-price ratio and expectations of future dividends and discount factors,” Review of Financial Studies, 1, 195-227.

·             Fama, Eugene and Kenneth French, 1988a, “Dividend yields and expected stock returns,” Journal of Financial Economics, 22, 3-27.

·             Goyal, Amit  and Ivo Welch, 1999, Predicting the Equity Premium,” SSRN

3

2-2

Individual security return behavior and volatility

Assignment:  Individual Security Behavior

 

Construct a matrix of monthly  NYSE stock returns for the last ten  years from CRSP data. Calculate the means, standard deviations, CAPM betas, FF factor betas, R-squares and factor-loading  t-statistics for this dataset. Calculate the cross-sectional first, second, third and fourth moments of the residuals of  this data, and plot them  in time-series.’

·              Shiller, Robert, J. "The Volatility of Stock Market Prices," Science (January 2, 1987), 235: 33-37.

·             Lettau, Martin and John Y. Campbell,  1999, “Dispersion and volatility in stock returns: an empirical investigation,” NBER working paper.

·             Morck, Randall, Bernard Yeung and Wayne Yu, 1999, “The information content of stock markets: why do emerging markets have synchronous stock price movements?” Journal of Financial Economics, 58(1-2): 215-260.

·              Artyom Durnev, Randall Morck, Bernard Yeung and Paul Zarowin, 2001, “Does Greater Firm-specific Return Variation Mean More or Less Informed Stock Pricing?“ Journal of Accounting Research, 41(5): 797-836.

·             Goyal, Amit and Pedro Santa-Clara, 2001, “Ideosyncratic Risk Matters,” Journal of Finance, 58(3): 975-1007.

4

2-9

Systematic risk and asset pricing

Assignment: Factor Models

 

Using CRSP NYSE/AMEX decile portfolio returns, and pre-specified or latent factors of your own choosing to design a Fama-MacBeth / Roll and Ross study to determine whether the evidence for positive factor premia in recent years is persuasive.

·             Fama, Eugene and Kenneth French, 1992, “The cross-section of expected stock returns,” Journal of Finance, 47(2) 427-465.

·             Fama, Eugene and Kenneth French, 1996,” The CAPM is wanted dead or alive,” Journal of Finance, 51 (5)  1947-1958.

·             Fama, Eugene and Kenneth French, 1993, “Common risk Factors in the Returns on Stocks and Bonds,” Journal of Financial Economics, 33(1) 3-56.

·             Roll, Richard and Stephen A. Ross, 1980, “An empirical investigation of the  arbitrage pricing theory,” Journal of Finance, 35, 1073-1103.

·             Chen, Nai-fu, Richard Roll and Stephen A. Ross, 1986, “Economic Forces and the Stock Market,” Journal of Business, 59, 383-403.

·             Fama, Eugene, and J. MacBeth, 1973, “Risk, Return and Equilibrium: Empirical Tests,” Journal of Political Economy, 81(3), 607-636.

·             Campbell, Lo and MacKinlay, Chapters 5 and 6

·             Mamaysky, Harry, 2001, “On the joint pricing of stocks and bonds: theory and evidence,” ICF Working Paper.

·             Lamont, Owen, 2000, “Economic Tracking Portfolios,” Journal of Econometrics, 105(1): 161-184 .

·             Brown, Stephen J.,  William N. Goetzmann and  Mark Grinblatt,  1998, “Positive Portfolio Factors,” ICF SSRN working paper.

5

2-16

Momentum Investing

Assignment: Momentum Investing

 

Download the momentum and industry factor portfolios from Ken French's web site http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/Data_Library/det_mom_factor.html

 

http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/Data_Library/det_mom_factor.html

 

What are the statistical characteristics, including autocorrelation, of the momentum portfolio?  what is its Sharpe Ratio, CAPM Alpha and Appraisal Ratio?   Does this vary through time?  Does heteroskedasticity matter?  Is there performance persistence in industry portfolios?  I.e. does performance last year predict performance this year, cross-sectionally? You can do this year-by-year as a regression or as a 2 by 2 table. Regress the momentum factor out of the industry portfolios.  Does this change your results in (2)?  Form an industry momentum factor by creating a factor that is  long last year's winning industries and short last year's losing industries. What are its statistical characteristics? what is its Sharpe Ratio, CAPM Alpha and Appraisal Ratio?   Does this vary through time?  Does heteroskedasticity matter? Regress the Fama-French momentum factor on your industry momentum factor and then examine the statistical characteristics of the residual.

·       Jegadeesh, Narasimhan and Sheridan Titman, 1993, “Returns to buing winners and selling losers: implications for stock market efficiency,” Journal of Finance, 48(1) March 65-91.

·       Jegadeesh, Narasimhan and Sheridan Titman,  2001,  “Profitability of momentum strategies: An evaluation of alternative explanations,” Journal of Finance, 56 (2): 699-720.

·       Rouwenhorst, K. Geert,  1998, “International Momentum Strategies,” Journal of Finance, 53(1) 267-283.

·       Moskowitz, Tobias and Mark Grinblatt, 1999, “Do Industries Explain Momentum,” Journal of Finance, 54(4) August, 1249-1290.

·       Chordia, Torun, and Lakshmanan, Shivakumar, 2001, “Momentum, Business Sycle and Time Varying Expected Returns,” Journal of Finance¸ 57(2): 985-1019.

6

2-23

Investment Portfolios and Performance Evaluation

Assignment: Mutual Fund Managers

 

Take a ten-year data base for one sector of the mutual fund universe (available on WRDS or via the ICF network). Divide it into two equal sub-periods.  For each sub-period,  calculate risk-adjusted performance measures for the managers in this sector. Plot the Sharpe ratios, the single factor or multi-factor alphas, the information ratios, and the Henrikkson-Merton timing coefficients.  Also plot the GISW utility measure.

 

Test to see if GISW skill in the first half forecasts GISW skill in the second half. On the H-M coefficients, make appropriate corrections for monthly as opposed to daily observations.

·       Sharpe, William F., 1966, “Mutual fund performance,” Journal of Business, Vol. 39, No. 1, Part 2: Supplement on Security Prices. (Jan.,1966), pp. 119-138.

·       Sharpe, William F. 1992, “Asset Allocation: Management Style and Performance Measurement,” The Journal of Portfolio Management, Winter.

·       Goetzmann, Ingersoll, Spiegel and Welch, 2004, “Sharpening Sharpe Ratios” Working Paper.

·       Barberis, Nick and Andrei Shleifer, 2001, “Style  Investing,” Journal of Financial Economics, 68 (2): 161-199.

 

7

3-2

Market Microstructure

Assignment: Market Microstructure

 

From the TAQ database on WRDS, choose two stocks – a large, liquid stock and a small, illiquid stock you are interested in.  download  3 months of trades for the securities. Take one day and plot the time series of prices for each.  When did it close and when was most trading?  Use the Lee and Ready approach to sign trades and use the Roll method to estimate effective bid-ask spread.

·             Chordia, Tarun, Richard Roll, and Avanidhar Subrahmanyam, 2000, “Commonality in Liquidity,” Journal of Financial Economics, 56, 3-28.

·             Lee, Charles and Mark Ready, 1991, “Infering Trade Direction from Intraday Data,” Journal of Finance, 46 (2) June, 733-746.

·             Dufour, Alfonso and Robert F. Engle, 2000, “Time and the Price Impact of a Trade,” Journal of Finance, 55 (6), 2467-2498.

·             Easley, David, Soeren Hvidkjaer, and Maureen O'Hara, 2000, “Is Information Risk a Determinant of Asset Returns?” Journal of Finance, 57(5), 2185-2221.

·      Spring Break

8

3-23

Determinants of P/E ratios

 

·             Fairfield, P., 1994. P/E, P/B, and the present value of future dividends, Financial Analysts Journal, 50 (4) 23-31.

·             Ohlson/Juettner, Expected EPS and EPS Growth as Determinants of Value. Forthcoming in Review of Accounting Studies.

9

3-30

Determinants of aggregate market valuations

Assignment: Fed model for other countries

 

Take any country other than the 10 countries examined in Thomas (2005) and plot the forward earnings yields and long bond yields each month. Obtain forward earnings per share, # of shares, and prices from IBES data on wrds, and get long bond yields from Datastream or similar source.

·          Shiller, R.J. 1981. Do stock prices move too much to be justified by subsequent changes in dividends? American Economic Review 71: 421-436.

·           Ritter & Warr, 2002, The decline of inflation and the Bull market of 1982-1999 Journal of Financial and Quantitative Analysis..

·           Asness, C., 2003, Fight the Fed model: the relationship between future returns and stock and bond market yields, Journal of Portfolio Management, Fall:11-24.

·           Campbell, J.Y. and T. Vuolteenaho. 2004Inflation illusion and stock prices, American Economic Review, 94(2): 19-23.  May 2004.

·          Thomas, J.K. 2005, Price equals forward earnings scaled by the risk-free rate: the implications of this remarkable empirical regularity, Working Paper.

 

10

4-6

Equity risk premium

 

·     Mehra R, Prescott EC, 1985; "The equity risk premium - a puzzle" Journal of Monetary Economics, 15 (2)145-161.

·     Brown, Stephen J. William N. Goetzmann and Stephen A. Ross, 1995, “Survival,” Journal of Finance, 50:3 853-873.

·       Graham, John and Campbell Harvey,  2001, “Expectation of equity risk premia, volatility and asymmetry from a  corporate finance perspective,” SSRN working paper.

·     Jorion, Philippe and William N. Goetzmann, 1999, “Global stock markets of the twentieth century,” Journal of Finance, 54(3) (June) 953-980.

·             Claus/Thomas, Equity premia as low as three percent? Evidence from analysts’ earnings forecasts for domestic and international stock markets, Journal of Finance. Vol. 55, No. 5, (October 2001), pp. 1629-66.

·     Fama, Eugene and Kenneth French, 2000, “The Equity Premium, “Journal of Finance. Vol. 57, No. 2, (April 2002).

11

4-13

Estimating firm-specific cost of equity

Assignment: Calculate firm-specific cost of capital

 

Calculate firm-specific cost of capital by replicating either the Gode/Mohanram approach or the Huang, Natarajan and Radhakrishnan approach.

·              Gebhardt, W., C. Lee, and B., Swaminathan, 2001; Toward an implied cost of capital, Journal of Accounting Research: 135-176.

·             Botosan/Plumlee, Estimating Expected Cost of Equity Capital: A Theory-Based Approach, Working paper (University of Utah)

·             Gode/Mohanram, What Affects the Implied Cost of Equity Capital. Working paper (New York University).

·             Easton, P., G., Taylor,, P., Shroff, and T., Sougiannis. 2002. Using forecast of earnings to simultaneously estimate growth and the rate of return on equity investment. Journal of Accounting Research 40: 657-676.

·             Huang R., R. Natarajan and S. Radhakrishnan, 2004 Estimating firm-specific long term growth rate and cost of capital, working paper, UT, Dallas.

12

4-20

Using fundamentals to explain firm-level variation in observed stock prices and returns

Assignment: Do deviations from the Fed model predict future returns?

 

Take each of the countries in the fed model paper by Thomas (2005), other than the US, and plot future 12-month returns for market indices against the difference between earnings yield and long bond yield each month. Excel sheet containing the results in Thomas (2005) will be provided.

 

 

·             Liu/Thomas, Stock returns and accounting earnings, Journal of Accounting Research. 38 (Spring 2000): 71-101.

·             Liu/Nissim/Thomas, Valuation using multiples, Journal of Accounting Research. 40 (1) (March 2002): 135-172.

13

4-27

Using accounting information to identify mispricing

Assignment: Do forecast errors predict future returns?

 

Post earnings announcement drift strategies are normally based on forecast errors using simple forecasts. What if the forecasts errors are calculated as reported quarterly earnings versus  consensus forecasts?

·             Sloan, Do stock prices fully reflect information in accruals and cash flows about future earnings?  The Accounting Review, (1996) 71: 289-315.

·             Bernard/Thomas, Post-earnings-announcement drift: Market inefficiency or CAPM misspecification? Journal of Accounting Research, (Supplement, 1989).