财务管理基础 13版 _pp05b.ppt

5b.* Van Horne and Wachowicz, Fundamentals of Financial Management, 13th edition. ? Pearson Education Limited 2009. Created by Gregory Kuhlemeyer. Chapter 5 – Support Risk and Return Remember? Determining the Expected Return/Standard Deviation Stock BW Ri Pi (Ri)(Pi) –0.15 0.10 –0.015 –0.03 0.20 –0.006 0.09 0.40 0.036 0.21 0.20 0.042 0.33 0.10 0.033 Sum 1.00 0.090 The expected return, R, for Stock BW is 0.09 or 9% Discrete Distribution: Expected Return and Variance Calculation As you can see we have recreated the discrete distribution here in Excel. The probabilities must sum to 1 or 100% and when we multiply the individual expected returns in each state by the associated probability we generate the contribution that state has to the overall expected return. We then use the expected return to generate the variance of .00703 or a standard deviation of 8.38% (0.0838) associated with the 9.00% return. Refer to ‘VW13E-05b.xlsx’ on tab ‘Discrete’. We can also graph as above. You may chance the probabilities and possible returns to view impact. Remember? Distribution Discussions So how do we create graphs that represent something akin to a normal distribution that is continuous? In file ‘VW13E-05b.xlsx’ on tab ‘Standard Normal’ we can create our own distributions with our own defined means and standard deviations! Discrete Distribution: Expected Return and Variance Calculation We can recreate our own distributions using Excel. While the process can be used for many different simulations and analysis techniques, we will focus on the creation of the distribution graph for an individual firm. Assume a stock has an expected mean return of 10% and a standard deviation of 30%. Together, we can create a standard normal distribution as above. Note that we f(x) creates the data for a normal distribution graph and F(x) creates