## Info

With a riskless rate of 6%, estimate the expected return on Emerson Electric.

i6. The following equation is reproduced from the study by Fama and French of returns between i963 and i990.

where MV is the market value of equity in hundreds of millions of dollar and BV is the book value of equity in hundreds of millions of dollars. The return is a monthly return.

a. Estimate the expected annual return on Lucent Technologies. The market value of equity is $ 240 billion, and the book value of equity is $ i3.5 billion.

b. Lucent Technologies has a beta of i.55. If the riskless rate is 6%, and the risk premium for the market portfolio is 5.5%, estimate the expected return.

c. Why are the expected returns different under the two approaches?

### Live Case Study Stockholder Analysis

Objective: To find out who the average and marginal investors in the company are. This is relevant because risk and return models in finance assume that the marginal investor is well diversified.

Key Questions:

• Who is the average investor in this stock? (Individual or pension fund, taxable or tax-exempt, small or large, domestic or foreign)

• Who is the marginal investor in this stock?

Framework for Analysis

1. Who holds stock in this company?

• How many stockholders does the company have?

• What percent of the stock is held by institutional investors?

• Does the company have listings in foreign markets? (If you can, estimate the percent of the stock held by non-domestic investors)

2. Insider Holdings

• Who are the insiders in this company? (Besides the managers and directors, anyone with more than 5% is treated as an insider)

• What role do the insiders play in running the company?

• What percent of the stock is held by insiders in the company?

• What percent of the stock is held by employees overall? (Include the holdings by employee pension plans)

• Have insiders been buying or selling stock in this company in the most recent year?

### Getting Information on Stockholder Composition

Information about insider and institutional ownership of firms is widely available since both groups have to file with the SEC. These SIC filings are used to develop rankings of the largest holders of stock in firms. Insider activity (buying and selling) is also recorded by the SEC, though the information is not available until a few weeks after the filing.

Online sources of information:

http: / / www.stern.nyu.edu/~adamodar/cfin2E/ proj ect/data. htm

Appendix on Statistics: Means, Variances, Covariances and Regressions

Large amounts of data are often compressed into more easily assimilated summaries, which provide the user with a sense of the content, without overwhelming him or her with too many numbers. There a number of ways in which data can be presented. One approach breaks the numbers down into individual values (or ranges of values) and provides probabilities for each range. This is called a "distribution". Another approach is to estimate "summary statistics" for the data. For a data series, Xx, X2, X3, X„, where n is the number of observations in the series, the most widely used summary statistics are as follows -

• the mean which is the average of all of the observations in the data series j =n ! *

• the median, which is the mid-point of the series; half the data in the series is higher than the median and half is lower

• the variance, which is a measure of the spread in the distribution around the mean, and is calculated by first summing up the squared deviations from the mean, and then dividing by either the number of observations (if the data represents the entire population) or by this number, reduced by one (if the data represents a sample)

When there are two series of data, there are a number of statistical measures that can be used to capture how the two series move together over time. The two most widely used are the correlation and the covariance. For two data series, X (Xx, X2,.) and Y(Y,Y... ), the covariance provides a non-standardized measure of the degree to which they move together, and is estimated by taking the product of the deviations from the mean for each variable in each period.

The sign on the covariance indicates the type of relationship that the two variables have. A positive sign indicates that they move together and a negative that they move in opposite directions. While the covariance increases with the strength of the relationship, it is still relatively difficult to draw judgements on the strength of the relationship between two variables by looking at the covariance, since it is not standardized.

The correlation is the standardized measure of the relationship between two variables. It can be computed from the covariance -

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