Abstract
PurposeThe purpose of this paper is to describe some optimization exercises which have proved to be very useful for introducing students to Markowitz‐style mean‐varience optimization.Design/methodology/approachThis paper describes two exercises that walk students through the process of gathering security price and dividend data, estimating the parameters of the joint distribution of asset returns, and then using a portfolio optimizer to construct mean‐variance efficient portfolios. It describes the basic methodology, and the more complex formulations of the portfolio optimization problem that are used in practice.Practical implicationsPortfolio selection is typically taught in finance courses as an abstract solution to a system of equations, and does little to connect the portfolio construction process to Exchange Traded Funds, stocks, bonds and other assets that are traded in markets. This study offers a practical approach to teaching portfolio optimization, that starts with gathering market data and shows how a quadratic optimization system is used to construct mean‐variance optimal portfolios.Originality/valueThe exercises in this case study prepare students to construct mean‐variance efficient portfolios for asset allocation with Exchange Traded Funds, and for building stock and bond portfolios, using market data and a portfolio optimizer.
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