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.

Elena Vasileva recently joined EnergyInvest as a junior portfolio analyst. Vasileva’s supervisor asks her to evaluate a potential investment opportunity in Amtex, a multinational oil and gas corporation based in the United States. Vasileva’s supervisor suggests using regression analysis to examine the relation between Amtex shares and returns on crude oil.Vasileva notes the following assumptions of regression analysis:Assumption 1: The error term is uncorrelated across observations.Assumption 2: The variance of the error term is the same for all observations.Assumption 3: The dependent variable is normally distributed.Vasileva runs a regression of Amtex share returns on crude oil returns using the monthly data she collected. Selected data used in the regression are presented in Exhibit 1, and selected regression output is presented in Exhibit 2. She uses a 1% level of significance in all her tests.
| Exhibit 1Selected Data for Crude Oil Returns and Am texShare Returns |
| Oil Return(X) | Amtex Return(Y) | Cross-Product(x；-X)；-7) | PredictedAmtex Return | RegressionResidualx-； | SquaredResidual |
| Month 1 | -0.032000 | 0.033145 | -0.000388 | 0.002011 | -0.031134 |
|  |  | 0.000969 |
| Month 36 | 0.028636 | 0.062334 |  |
| Sum | 0.0026630.085598 | 0.016282 | -0.046053 | 0.0021210.071475 |
| Average | -0.018056 | 0.005293 |


Critical t-values for a 1% level of significance:One-sided, left side: -2.441One-sided, right side: +2.441Two-sided: ±2.728Vasileva expects the crude oil return next month, Month 37, to be -0.01. She computes the standard error of the forecast to be 0.0469.
Based on Exhibit 1, the standard error of the estimate is closest to:
Option A:0.04456.
Option B:0.04585.
Option C:0.05018.

Answer: B