Abstract
W. Sharpe's (Citation1988, Citation1992) returns-based style analysis provides an excellent opportunity to use a sophisticated portfolio-analysis tool in the classroom to help illustrate important topics in investment and operations research courses. Students can perform classic returns-based style analysis by creating a spreadsheet model and using the Solver add-in in Microsoft Excel. The technique can also be used to supplement classroom units on performance measurement and style drift in investment courses or to illustrate a finance application in an introductory operations research course. An example analysis using a popular mutual fund is provided as well as the accompanying Excel model.
Notes
1. Available for download at: http://corporate.morningstar.com/UK/html/pdf.htm?./documents/MethodologyDocuments/ResearchPapers/Holdings-basedAndReturns-basedStyleModels_PK.pdf
2. There is an extensive literature on window dressing. Influential research includes CitationGrinblatt and Titman (1993), CitationGrinblatt, Titman, and Wermers (1995), and CitationWermers (2002).
3. The nonnegativity constraint on the weights can be relaxed when appropriate. For example, when analyzing a portfolio that uses derivatives, short positions, or leverage.
4. I find it instructive to run an ordinary least squares (OLS) regression with the mutual fund's monthly returns as the dependant variable and the monthly returns of the indices as the independent variables. The OLS results can be contrasted with the RBSA results specifically highlighting the natural interpretation of the RBSA slopes as portfolio weights.
5. You may be wondering about U.S. midcap stocks. They are split between the large and small-cap DJ Wilshire indices. S&P midcap indices use stocks 501 through 1000. The Dow Wilshire large-cap indices contain the 750 largest stocks in the U.S., whereas small-cap indices capture stocks 751 through 2,500 and the microcap has 2,500 through approximately 4,000.
6. Thanks to Jim Davis of Dimensional Fund Advisors for suggesting this set of indices.
7. As of December 31, 2007, DODBX had over $28 billion in assets.
8. See www.dodgeandcox.com.
9. See www.morningstar.com.
10. Please contact the author for the Excel workbook.
11. See Lobosco and Di Bartolomeo (1997) for calculating approximate confidence intervals.
12. A caution is necessary; the style benchmark can only explain about 41% of the variation in Exxon's monthly returns for the past five years ending in December 2007. This highlights the use of RBSA as a tool for analyzing portfolios.
14. Chan, Chen, and Lakonishok (2002) analyze style drift in mutual funds.
15. For example, Brown and Goetzmann (2001) used RBSA in analyzing the performance of hedge funds.