InvestmentPlanningWeek5_2

# InvestmentPlanningWeek5_2 - FSU Certificate in Financial...

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FSU Certificate in Financial Planning Investment Planning © Florida State University Page 1 Lecture Title: Week 5: Statistical Tools, Performance Evaluation Week 5: Risk and Portfolio Theory – Part 2 Introd uctio n Part 1 of our study of risk and portfolio theory began with the basic building blocks of defining risk and return. We discovered the powers of diversification and negative correlation in greatly reducing unsystematic risk. We moved to the two main measurements of risk used in portfolio theory, standard deviation and beta coefficient. Finally, we studied the capital asset pricing model and arbitrage pricing theory. Theoretically, these theories help us to select a portfolio that provides the highest return for a given amount of risk. In Part 2, we learn more of the statistical tools we use in our constant vigil to protect honest, law abiding returns from the insidious behavior of risk. A few of these you need to be able to use proficiently as tools of the trade; a couple of them only need to be understood conceptually. The material presented in this week's reading takes us to the next logical step. We will learn to more accurately evaluate performance by adjusting returns for the amount of risk taken in achieving those returns. Objectives At the end of this lecture, you will be able to: Use statistical tools and models to compare portfolio performance on the basis of risk and return. Lecture Presentation Let's begin by looking at pages 341-344. There are basically three different ways an average may be expressed and each method has practical applications in the real world.

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FSU Certificate in Financial Planning Investment Planning © Florida State University Page 2 Arithmetic (Simple) Average: All observations are treated equally with the sum of the individual numbers being divided by the number of observations. Example: 3+5+7 = 15; 15/3 = 5. Weighted average: This average considers not only the number of observations but also the weight (% of the total represented) of each observation. In the example above the observations represent stock prices. If there were five shares at \$3, two shares at \$5, and one share at \$7, the weighted average would be figured this way: 5(3) + 2(5) + 1(7) = 32 = 4 total # of shares 8 In the example, we are looking at the weighted average of an ex post (realized) return. You should remember from last week's lecture that we can also look at ex ante (expected) returns using a weighted average in which each outcome is weighted by the probability of the outcome occurring. Geometric Average: You may recall a former USBA Heavyweight Champion named Carl "The Truth" Williams. He undoubtedly was not the greatest boxer of all time, but I challenge anyone to come up with a greater moniker. If averages were boxers we'd have Geometric "The Truth" Average. The computation of investment average returns requires this bad boy be used in order to derive the true return.
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