Roth- Case Paper

The historical beta comes from historical data. This kind of beta would slope coefficient in a regression, and associated with company's stock returns and market returns. This approach is conceptually straightforward, and complications quickly arise in practice.

Beta is the slope of the characteristic line. As shown in appendix1, we use the monthly historical data from April 2003 to April 2008 to graph SCL. We use S&P 500 as the market because it contains the stocks of 500 Large-Cap corporations and can reflect the market change broadly. As shown in exhibit 1, we can get the SCL: Ri-Rf = - 0.001 + 0.1649(Rm - Rf). So the beta is 0.1649 and the alpha (intercept) is -0.001. From the regression line, we find the R square is only 0.103. It reflects the degree that X variable explains Y variable is 10.3%. That is, Ri-Rf has no close relationship with Rm-Rf. In addition, due to the fact that beta is only 0.1649, it also provides the same result which Ri-Rf and Rm-Rf have no strong positive relationship. It is a good issue to consider why Wal-Mart stock return does not relate with S&P 500 return very well. From exhibit 2, we find the Wal-Mart price did not change very much while S&P 500 price went up. The major reasons may be that S&P 500 includes many high-tech stocks and those stocks performed very well during the period; therefore the volatility is greater than Wal-Mart. Moreover, maybe Wal-Mart has lower weight in S&P 500 so its trend of price change is different from S&P 500. From exhibit2, we also find Wal-Mart had good relationship with S&P 500 before 2004. To examine the situation, we use the data from 1998 to 2003 and find the SCL

After levering the equity beta, the asset beta of the firms are calculated. As mentioned we think that the three discount brokerages (highlighted in green) should be used as comparables for Ameritrade. The average asset beta of the three firms is 1.386. As a comparison the investment services firms have average asset beta of 0.603 and the one internet company (Mecklermedia) for which enough historical data is

In the Fama & French paper, they found that: 1) stocks with high beta did not have consistently higher returns than low-beta stocks; 2)

2. Beta for mercury is calculated by comparison with the companies having similar debt/equity ratio (25%). This beta is used in the calculation of cost of equity afterwards. The equity beta comes out to be 1.12.

A common practice to determine the firm’s beta is to draw from historical data from published sources or compare numbers to competitors. In this case, Heinz can compare to Kraft, Campbell Soup and Del Monte and use professional judgement in determining the stock’s sensitivity to the market. A stock’s beta can be determined using a formula as well.

For the calculation of equity, beta is a necessity because there is no comparison that matches its operational profile. Beta 1.17 ke = (4.58%+1.17) =

CAPM is a model that describes the relationship between risk and expected return, and the formula itself measures the expected return of the portfolio. Mathematically, when beta is higher, meaning the portfolio has more systematic risk (in comparison to the market portfolio), the formula yields a higher expected return for the portfolio (since it is multiplied by the risk premium and is added to the risk free interest rate). This makes sense because the portfolio needs to

For estimation of betas, the above equation was run for the period from Jan, 2003 to Dec, 2006. Based on the estimated betas we have divided the sample of 63 stocks into 10 portfolios each comprising of 6 stocks except portfolio no.1, 5 and 10 having seven stocks each. The first portfolio 1 has the 7 lowest beta stocks and the last portfolio 10 has the 7 highest beta stocks. The rationale for forming portfolios is to reduce measurement error in the betas.

Using CAPM: Risk Free Rate = 6%; Market Risk Premium = 5%; Beta = 1.2

To calculate beta, we took the beta of assets of the company as a while and set that equal to the percentage of equity for each division and multiplied by the beta of equity for each respective division.

For beta, there are mainly two different ways to calculate the value for beta. The first is to calculate it yourself based on historical data. By using this method, you run the risk of using inaccurate data if you choose a period that is too broad or narrow. Conversely, the other way to determine it is to use published sources such as Bloomberg and Standard & Poor’s. Similar to using historical data to determine beta, there are variations in these published sources for the values of beta. As a result, the calculation of the overall cost of capital will vary depending on which source of beta you

Beta: Companies in the same industries usually have different betas, one of the reasons this can happen is the kind of financing or debt equity ratio. The higher the debt equity ratio the higher the beta: this shows why company N has a higher beta compared to company M that has a lower debt equity ratio.

Blunt thought that NYL had a chance to sell a very large volume of immediate annuities through the roughly 500,000 independent and company-based investment advisors in the United States who helped people manage their retirement assets. To do this, he wanted to make a multimillion-dollar investment in people and resources to try to convince these investment advisors to sell NYL’s immediate annuities.

The betas (slope of estimated regression equation) for the individual stocks can be obtained from the regression