Question: 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
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.
-1.png)
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
-2.png)
Did Batten's regression analyze cross-sectional or time-series data, and what was the expected value of the error term from that regression?
Data Type.............................Expected Value of Error Term
A. Time-series.............................0
B. Time-series.............................ε i
C. Cross-sectional........................0
EXHIBIT 1 Descriptive Statistics Lagged Monthly Change Monthly Return Stellar Common Stock CPIENG PPICEM Mean 0.0042 0.0123 0.0023 Standard Deviation 0.0534 0.0717 0.0160 Covariance, Stellar vs. CPIENG -0.00017 F0.00048 Covariance, Stellar vs. PPICEM Covariance, CPIENG vs. PPICEM 0.00044 Correlation, Stellar vs. CPIENG -0.1452 Coefficients Standard Error -Statistic 0.0138 0.0046 3.0275 Intercept Slope coefficient -0.6486 0.2818 -2.3014
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