CASES IN INVESTMENT MANAGEMENT
©William N. Goetzmann, Yale School of Managment, 1995These cases in investment management are created to teach analytical and quantitive skills. They are designed for use with spreadsheet data, and/or Ibbotson Inc. EnCorr Optimization software. They also can be used to teach applications of other commercially available investment software programs, including products produced by BARRA, Piper and Morningstar. If you are interested in liscensing the spreadsheet data for classroom use, please contact me. If you wish to use the cases for classroom purposes, please link them rather than copying them. They are prepared solely for educational use, and may not be duplicated or circulated without the permission of the author. All resemblance to acual companies is purely coincidental. If you use them, I would welcome suggestions for improvement, and the identification of errors.
Rivermore College A mean-variance optimization case. Software needs: build you own spreadsheet optimizer or use a commercial package. Data needs: a spreadsheet with time-series' of portfolio returns and asset returns from Ibbotson Associates. Concepts: performance evaluation with historical data, forecasting asset returns, portfolio choice with input uncertainty. Computer skills: development and/or use of a mean-variance optimizer.
Taurus Realty An advanced mean-variance case with real estate assets. Software needs: build you own spreadsheet optimizer or use a commercial package. Suggested reading: Roger Ibbotson and William N. Goetzmann, "The Performance of Real Estate as an Asset Class," Journal of Applied Corporate Finance, June, 1990. Concepts: undewrstanding the limitations of a mean-variance optimizer, the effect of integrality constraints and the problems of sub-set optimization. Computer skills: use of the optimizer and spreadsheet analysis.
El Lobo, Inc. An APT case with optimization. Software needs: a spreadsheet optimizer for which you must determine your own objective function and constraints. BARRA or BIRR software may also be used. Recommended reading: Berry, Michael, Edwin Burmeister and Majorie McElroy, "Sorting Out Risks Using Known APT Factors," Financial Analysts Journal, 1988,v44(2), 29,42. Case uses factor loadings reported in the reading. Concepts: the use of mutli-factor asset pricing factor sensitivities to develop portfolios. The definition of client needs and goals in terms of macro-economic sensitivities. The foundations of advanced asset pricing packages. The foundations of programmed risk arbitrage. Computer skills: linear and/or non-linear optimization.
Fast Forward Forecasting Long-horizon stock return forecasting using dividend yields. Software needs: a statistical package for regressions and possibly bootstrapping capabilities. Data needs: time-series of annual returns to U.S. asset classes from Ibbotson Associates. Recommended reading, Michael Rozeff, "Dividend Yields are Equity Premiums," Journal of Portfolio Management, 1984-1985, v11(1) 68-75. Concepts: statistical forecasting. Back-testing trading and filter rules for investment decisions. Statistical problems of overlapping data. Computer skills: advanced regression analysis and statistical hypothesis testing. Bootstrapping optional.
Pied Piper AdvisorsA performance evaluation case with timing measures. Software needs: Ibbotson Associates EnCorr database, Piper database are recommended. Data needs: a spreadsheet of fund return data and asset class returns. Mutual fund data could easily be substituted. Concepts: performance evaluation via risk-adjusted returns. Confidence intervals about performance measures. Tests for market timing ability. Computer skills: spreadsheet analysis and graphics skills. Optional: the use of commercial manager perfomance software.
Tuck Family Trust Company A bond portfolio management case. Software needs: a spreadsheet. Data needs: time-series of historical income and total returns to intermediate term U.S. goverment bonds from Ibbotson Associates. Concepts: duration, constructing a yield curve, mortgage-backed securities, bond mathematics, family trusts. Computer skills: spreadsheet analysis.
Leverage Brothers A bootstrapping and simulation case with taxes. Software needs: a spreadsheet with macro facility, or a simulation programs such as @risk. For lotus users I have a lotus 1-2-3 set of macros. Data needs: monthly returns to major asset classes. Optional: income and capital appreciation returns separated, and a history of maximum marginal tax rates. Concepts: investment simulation, stochastic dominance and preferences over distributions, the effect of taxes. Computer skills: advanced simulation development and analysis.
Hermes Investors a portfolio assurance case. software needs: a spreadsheet, with cumulative normal probability function. Data needs: current S&P 500 volatilty and current t-bill rate. Concepts: binomial model and Black-Scholes. Computer skills: development of a binomial option pricing program and/or theuse of a commercial option valuation tool
Oilshaft, Inc. Hedging by rolling over futures. Software needs: spreadsheet with simulation capability. Data needs: futures and spot prices of contracts from Knight-Ridder Financial Corporation, or a yearbook of futures' prices. Recommended reading: Franklin Edwards and Michael Canter, "The Collapse of Metallgesellschaft: Unhedgeable Risks, Poor Hedging Strategy or Just Bad Luck," Journal of Applied Corporate Finance 8(1) Spring, 1995, and Christopher L. Culp and Merton Miller, "Metallgesellschaft and the Economics of Synthetic Storage," Journal of Applied Corporate Finance, 7(4), Winter, 1994. Concepts: futures markets, corporate hedging needs, Net Present Value, the matching assets and liabilities. Computer skills: spreadsheet analysis, extracting of futures data from databases, and understanding it.