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Econometric

Autor:   •  October 10, 2016  •  Exam  •  1,543 Words (7 Pages)  •  726 Views

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SAMPLE QUESTION

  1. Given below is the ACF and PACF plot of Apple stock returns estimated by a researcher

[pic 1]

[pic 2]

  1. what should be the order of ARIMA model                                                

Though ACF and PACF suggest either AR(11) or AR(24), but based on principle of parsimony one may consider AR(4).

  1. The  researcher estimated AR(p) Models as follows for Apple Stock returns:

AR(1)

Coefficients:

                          ar1                  intercept

                      -0.0056             0.0011

s.e.                   0.0254             0.0006

sigma^2 estimated as 0.0005566:  log likelihood = 3612.84,  aic = -7219.68

Box-Ljung test                         data:  ar1$residuals

X-squared = 39.4241, df = 20, p-value = 0.005902

AR(2)

Coefficients:

          ar1              ar2                  intercept

              -0.0059          -0.0498             0.0011

s.e.           0.0254           0.0254             0.0006

sigma^2 estimated as 0.000555      log likelihood = 3614.76,  aic = -7221.53

Box-Ljung test                         data:  ar2$residuals

X-squared = 32.654, df = 20, p-value = 0.03681

AR(3)

Coefficients:

          ar1                      ar2                     ar3                  intercept

      -0.0055                  -0.0497          0.0075             0.0011

s.e.   0.0254                     0.0254          0.0254             0.0006

sigma^2 estimated as 0.0005552:  log likelihood = 3614.81,  aic = -7219.61

Box-Ljung test                         data:  ar3$residuals

X-squared = 32.6176, df = 20, p-value = 0.03715

AR(4)

Coefficients:

          ar1                      ar2                     ar3                     ar4                  intercept

      -0.0059                  -0.0464          0.0079                  0.0678             0.0011

s.e.   0.0253                   0.0253                  0.0253                  0.0254             0.0006

sigma^2 estimated as 0.0005527:  log likelihood = 3618.35,  aic = -7224.7

Box-Ljung test                         data:  ar4$residuals

X-squared = 22.2278, df = 20, p-value = 0.3283

Without calculating t-statistics, answer intuitively which coefficients are significant across all the models                                                                                

...

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