This preview shows pages 1–3. Sign up to view the full content.
This preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
Unformatted text preview: Chapter Four Portfolio Tools Overview Part two of the textbook begins the heavy math. Chapter four, specifically, wastes no time in providing students with immersion in formulae. The topics covered in chapter four accurately reflect the chapters title, Portfolio Tools. Instructors are encouraged to think of this chapter as providing students with the toolbox with which they can later build portfolios. The math will quickly become tedious. Much of what is offered is a review of statistics. It is simply presented in the context of finance. At first students will resist and the instructors often have difficulty getting motivated to teach these topics. It is highly recommended that an entire class be spent on this material. It should be considered an investment. Time invested in honing the statistical skills of students and laying a solid math foundation will make the upcoming chapters much easier. Plenty of homework assignments and practice questions should be used to force the learning process. There is no magic to this chapter. Roll up the sleeves and get started. Learning Objectives After reading this chapter, students should be able to: 1. Compute the covariance and correlation between two returns given historical data. 2. Identify a meanstandard deviation diagram and be familiar with its basic elements. 3. Use means and covariances for individual asset returns to calculate the mean and variance of the returns on a portfolio of N assets. 4. Use covariances between stock returns to compute the covariance between the return of a stock and the return of a portfolio. 5. Understand the implications of the statement that the covariance is a marginal variance for small changes in the composition of a portfolio. 6. Compute the minimum variance portfolio of a set of risky assets and interpret the equations that need to be solved in this computation. Lecture Material 1. Portfolio theory a. Meanvariance optimizers b. Meanvariance analysis c. Asset allocation d. CAPM e. Diversification 25 2. Portfolio weights a. The portfolio weight for stock j 3. The twostock portfolio a. Example 4.1 Computing portfolio weights for a two stockportfolio b. This example allows you to apply the formula listed above....
View
Full
Document
 Spring '08
 Juan

Click to edit the document details