Question #52
Reading: Reading 1 Multiple Regression
PDF File: Reading 1 Multiple Regression.pdf
Page: 23
Status: Unattempted
Correct Answer: B
Question
Alex Wade, CFA, is analyzing the result of a regression analysis comparing the performance of gold stocks versus a broad equity market index. Wade believes that first lag serial correlation may be present and, in order to prove his theory, should use which of the following methods to detect its presence?
Answer Choices:
A. The Breusch-Pagan test
B. The Hansen method
C. The Durbin-Watson statistic. Phillip Lee works for Song Bank as a quantitative analyst. He is currently working on a model to explain the returns (in %) of 20 hedge funds for the past year. He includes three independent variables: Market return = return on a broad-based stock index (in %) Closed = dummy variable (= 1 if the fund is closed to new investors; 0 otherwise) Prior period alpha = fund return for the prior 12 months – return on market (in %) Estimated model: hedge fund return = 3.2 + 0.22 market return + 1.65 closed – 0.11 prior period alpha Lee is concerned about the impact of outliers on the estimated regression model and collects the following information:
Explanation
The Durbin-Watson statistic is the most commonly used method for the detection of serial
correlationat the first lag, although residual plots can also be utilized. For testing of serial
correlation beyond the first lag, we can instead use the Breusch-Godfrey test (but is not
one of the answer choices).
(Module 1.3, LOS 1.i)
Phillip Lee works for Song Bank as a quantitative analyst. He is currently working on a model
to explain the returns (in %) of 20 hedge funds for the past year. He includes three
independent variables:
Market return = return on a broad-based stock index (in %)
Closed = dummy variable (= 1 if the fund is closed to new investors; 0 otherwise)
Prior period alpha = fund return for the prior 12 months – return on market (in %)
Estimated model: hedge fund return = 3.2 + 0.22 market return + 1.65 closed – 0.11 prior
period alpha
Lee is concerned about the impact of outliers on the estimated regression model and
collects the following information:
Observation
1
2
3
4
5
6
7
8
9
10
Cook's D
0.332
0.219
0.115
0.212
0.376
0.232
0.001
0.001
0.233
0.389
Observation
11
12
13
14
15
16
17
18
19
20
Cook's D
0.089
0.112
0.001
0.001
0.219
0.001
0.112
0.044
0.517
0.212
Additionally, Lee wants to estimate the probability of a hedge fund closing to new investors,
and he uses two variables:
Fund size = log of assets under management
Prior period alpha (defined earlier)
Results are shown as follows:
Variable
Coefficient
Intercept
–3.76
Fund size
–2.98
Prior period alpha
–2.99