Question #70

Reading: Reading 1 Multiple Regression

PDF File: Reading 1 Multiple Regression.pdf

Page: 33

Status: Unattempted

Correct Answer: B

Part of Context Group: Q69-70
Shared Context
- Which of the following tests is least likely to be used to detect autocorrelation? A) Durbin-Watson. B) Breusch-Godfrey. C) Breusch-Pagan.
Question
If a regression equation shows that no individual t-tests are significant, but the F-statistic is significant, the regression probably exhibits:
Answer Choices:
A. serial correlation
B. multicollinearity
C. heteroskedasticity. Lynn Carter, CFA, is an analyst in the research department for Smith Brothers in New York. She follows several industries, as well as the top companies in each industry. She provides research materials for both the equity traders for Smith Brothers as well as their retail customers. She routinely performs regression analysis on those companies that she follows to identify any emerging trends that could affect investment decisions. Due to recent layoffs at the company, there has been some consolidation in the research department. Two research analysts have been laid off, and their workload will now be distributed among the remaining four analysts. In addition to her current workload, Carter will now be responsible for providing research on the airline industry. Pinnacle Airlines, a leader in the industry, represents a large holding in Smith Brothers' portfolio. Looking back over past research on Pinnacle, Carter recognizes that the company historically has been a strong performer in what is considered to be a very competitive industry. The stock price over the last 52-week period has outperformed that of other industry leaders, although Pinnacle's net income has remained flat. Carter wonders if the stock price of Pinnacle has become overvalued relative to its peer group in the market, and wants to determine if the timing is right for Smith Brothers to decrease its position in Pinnacle. Carter decides to run a regression analysis, using the monthly returns of Pinnacle stock as the dependent variable and monthly returns of the airlines industry as the independent variable. Analysis of Variance Table (ANOVA) Source df SS Mean Square (SS/df)
Explanation
Common indicators of multicollinearity include: high correlation (>0.7) between independent variables, no individual t-tests are significant but the F-statistic is, and signs on the coefficients that are opposite of what is expected. (Module 1.3, LOS 1.j) Lynn Carter, CFA, is an analyst in the research department for Smith Brothers in New York. She follows several industries, as well as the top companies in each industry. She provides research materials for both the equity traders for Smith Brothers as well as their retail customers. She routinely performs regression analysis on those companies that she follows to identify any emerging trends that could affect investment decisions. Due to recent layoffs at the company, there has been some consolidation in the research department. Two research analysts have been laid off, and their workload will now be distributed among the remaining four analysts. In addition to her current workload, Carter will now be responsible for providing research on the airline industry. Pinnacle Airlines, a leader in the industry, represents a large holding in Smith Brothers' portfolio. Looking back over past research on Pinnacle, Carter recognizes that the company historically has been a strong performer in what is considered to be a very competitive industry. The stock price over the last 52-week period has outperformed that of other industry leaders, although Pinnacle's net income has remained flat. Carter wonders if the stock price of Pinnacle has become overvalued relative to its peer group in the market, and wants to determine if the timing is right for Smith Brothers to decrease its position in Pinnacle. Carter decides to run a regression analysis, using the monthly returns of Pinnacle stock as the dependent variable and monthly returns of the airlines industry as the independent variable. Analysis of Variance Table (ANOVA) Source df (Degrees of Freedom) SS (Sum of Squares) Mean Square (SS/df) Regression 1 3,257 (RSS) 3,257 (MSR) Error 8 298 (SSE) 37.25 (MSE) Total 9 3,555 (SS Total)
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