Reading 12- LOS a (Part 2): Q1- 5 factors, security, following, determine, companies

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1.Dave Turner is a security analyst who is using regression analysis to determine how well two factors explain returns for common stocks. The independent variables are the natural logarithm of the number of analysts following the companies, Ln(no. of analysts), and the natural logarithm of the market value of the companies, Ln(market value). The regression output generated from a statistical program is given in the following tables. Each p-value corresponds to a two-tail test.

Turner plans to use the result in the analysis of two investments. WLK Corp. has twelve analysts following it and a market capitalization of $2.33 billion. NGR Corp. has two analysts following it and a market capitalization of $47 million.

Table 1: Regression Output

Variable	Coefficient	Standard Error of the Coefficient	t-statistic	p-value
Intercept	0.043	0.01159	3.71	< 0.001
Ln(No. of Analysts)	-0.027	0.00466	-5.80	< 0.001
Ln(Market Value)	0.006	0.00271	2.21	0.028

Table 2: ANOVA

	Degrees of Freedom	Sum of Squares	Mean Square
Regression	2	0.103	0.051
Residual	194	0.559	0.003
Total	196	0.662

In a one-sided test and a 1 percent level of significance, which of the coefficients are significantly different from zero?

A)   The coefficient on ln(no. of Analysts) only.

B)   The intercept and the coefficient on ln(market value) only.

C)   All the coefficients.

D)   The intercept and the coefficient on ln(no. of analysts) only.

2.The 95 percent confidence interval of the expected return of WLK Corp. is closest to:

A)   0.0 to 0.21.

B)   -0.03 to 0.31.

C)   0.03 to 0.24

D)   0.05 to 0.25.

3.If the number of analysts on NGR Corp. were to double to 4, the change in the forecast of NGR would be closest to?

A)   -0.035.

B)   -0.012.

C)   -0.019.

D)   -0.055.

4.Based on a R-squared calculated from the information in Table 2, the analyst should conclude that the number of analysts and ln(market value) of the firm explain:

A)   15.6% of the variation in returns.

B)   84.4% of the variation in returns.

C)   18.4% of the variation in returns.

D)   14.7% of the variation in returns.

5.What is the F-statistic from the regression? And, what can be concluded from its value at a 1 percent level of significance?

A)   F = 1.97, fail to reject a hypothesis that both of the slope coefficients are equal to zero.

B)   F = 5.80, reject a hypothesis that both of the slope coefficients are equal to zero.

C)   F = 17.00, reject a hypothesis that both of the slope coefficients are equal to zero.

D)   F = 33.65, reject a hypothesis that all three coefficients are equal to zero.