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Homework answers / question archive / You estimate a regression of the excess return on Microsoft stock (ermsoft) on a constant, the excess return on the S&P market index (ersandp) and the return on the term spread (rterm)

You estimate a regression of the excess return on Microsoft stock (ermsoft) on a constant, the excess return on the S&P market index (ersandp) and the return on the term spread (rterm)

Economics

You estimate a regression of the excess return on Microsoft stock (ermsoft) on a constant, the excess return on the S&P market index (ersandp) and the return on the term spread (rterm). You run a diagnostic test. EViews provides you with the following output Dependent Variable: ERMSOFT Method: Least Squares Sample: 1986M04 2013M04 Included observations: 325 Variable Coefficient Std. Error t-Statistic Prob. ? ERSANDP RTERM FITTED^2 -1.177958 1.454598 4.005786 0.013618 0.797167 0.174896 2.497635 0.009268 -1.477680 8.316935 1.603832 1.469306 0.1405 0.0000 0.1097 0.1427 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.198864 Mean dependent var 0.191377 S.D. dependent var 12.64684 Akaike info criterion 51341.54 Schwarz criterion -1283.800 Hannan-Quinn criter. 26.56033 Durbin-Watson stat 0.000000 -0.263150 14.06400 7.924923 7.971493 7.943509 2.136191 Which of the following do you conclude? Select one: A. There is no evidence of incorrect functional form at the 5 percent level. B. There is no evidence of autocorrelation at the 5 percent level. C. There is no evidence of heteroskedasticity at the 5 percent level. D. None of these. E. There is no evidence of multicollinearity at the 5 percent level.
Consider the following model yt = 0.3 +0.4€-1 + Et, where &t is a white noise process. The correlation between yand yt-1 for this process is: Select one: A. 0.4 O B. 0.3448 C. None of these. D. 0.12 O E. 1.3333

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Answer:

First we should familiarize ourselves with the rules of statistical significant tests.

  • If t calc > t critic then we reject our null hypothesis
  • If p < 0.05 then we reject our null hypothesis (at 5 percent probability)

So naturally given the question and the data, our dependent variable is ermsoft and independent variables are ersandp and rterm. The null hypothesis would be that ersandp and rterm have no statistical significant impact on ermfost (H0 = 0).

  1. There is negative autocorrelation as the Durbin Watson Test value is >2. Therefore we cancel out option B. The p value is <0.05 and thus the hypothesis seems statistical significant. Since there is no information on the tests of Heteroskedasticity and Multicollinearity, we cannot form conclusions on option C and E and thus cancel them out too. Since the log-likelihood is negative, it implies that the data set may be bad, as our aim should be to minimize negative log-likelihood and maximize positive log-likelihood. Therefore, there can be a case of incorrect functional form, and we have to cancel out option A. Option D is thus the best suited.
  2. I am unable to answer this part with certainty, apologies.

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