Given a text T, and several options, according to the question posed in the text T to choose the most appropriate option from the options as the answer, please directly output the most appropriate option, do not need to output the explanation.

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 Corp. stock has tended to rise following increases in retail energy prices. Golub believes the association between the two variables is negative, but he does not know the strength of the association.Golub directs his assistant, Jill Batten, to study the relationships between (1) Stellar monthly common stock returns and the previous month’s percentage change in the US Consumer Price Index for Energy (CPIENG) and (2) Stellar monthly common stock returns and the previous month’s percentage 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 248 months. All the data are in decimal form, where 0.01 indicates a 1% 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 1Descriptive Statistics |
| Stellar Common | Lagged Monthly |
| Stock Monthly | Change |
| Return | CPI ENG | PP ICEM |
| Mean | 0.0123 | 0.0023 | 0.0042 |
| Standard deviation | 0.0717 | 0.0160 | 0.0534 |
| Covariance， Stellar vs.CPI ENG | -0.00017 |
| Covariance， Stellar vs.PP ICEM | -0.00048 |
| Covariance， CPI ENG vs.PP ICEM | 0.00044 |
| Correlation， Stellar vs.CPI ENG | -0.1452 |



| Exhibit 2Regression Analysis with CPI ENG |
| R2 | 0.0211 |
| Standard error of the estimate | 0.0710 |
| Observations | 248 |



| Regression Statistics |
| Coefficients | Standard Error | t-Statistic |
| Intercept | 0.0138 | 0.0046 | 3.0275 |
| CPI ENG(%) | -0.6486 | 0.2818 | -2.3014 |


Critical t-valuesOne-sided, left side: -1.651One-sided, right side: +1.651Two-sided: ±1.967
Which of the following best describes Batten’s regression?
Option A:Time-series regression.
Option B:Cross-sectional regression.
Option C:Time-series and cross-sectional regression.

Answer: A