Howard Golub, CFA, is preparing to write a research report

Howard Golub, CFA, is preparing to write a research report on Stellar Energy Corp. common stock. One of the world’s largest companies, Stellar is in the business of refining and marketing oil. As part of his analysis, Golub wants to evaluate the sensitivity of the stock’s returns to various economic factors. For example, a client recently asked Golub whether the price of Stellar Energy stock has tended to rise following increases in retail energy prices. Golub believes the association between the two variables to be negative, but he does not know the strength of the association.
Golub directs his assistant, Jill Batten, to study the relationships between Stellar monthly common stock returns versus the previous month’s percent change in the US Consumer
Price Index for Energy (CPIENG), and Stellar monthly common stock returns versus the previous month’s percent change in the US Producer Price Index for Crude Energy Materials (PPICEM). Golub wants Batten to run both a correlation and a linear regression analysis. In response, Batten compiles the summary statistics shown in Exhibit 1 for the 248 months between January 1980 and August 2000. All of the data are in decimal form, where 0.01 indicates a 1 percent return. Batten also runs a regression analysis using Stellar monthly returns as the dependent variable and the monthly change in CPIENG as the independent variable. Exhibit 2 displays the results of this regression model.

EXHIBIT 2 Regression Analysis with CPIENG

Regression Statistics

Multiple R………………………….0.1452

R-squared………………………….0.0211

Standard error of the estimate……..0.0710

Observations………………………248

Batten wants to determine whether the sample correlation between the Stellar and CPIENG variables (ˆ’0.1452) is statistically significant. The critical value for the test statistic at the 0.05 level of significance is approximately 1.96. Batten should conclude that the statistical relationship between Stellar and CPIENG is:

A. significant, because the calculated test statistic has a lower absolute value than the critical value for the test statistic

B. significant, because the calculated test statistic has a higher absolute value than the critical value for the test statistic

C. not significant, because the calculated test statistic has a higher absolute value than the critical value for the test statistic

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