Assessment Questions On Econometrics

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Question 2

  1. Explain why you choose this stock (Please do a due diligence of company’s background, Do Not copy online articles, etc).
  2. Provide appropriate graphs of the continuously compounded returns of the stock you have chosen to study. Does your return series have the characteristics that confirm to the stylised facts of financial returns data?
  3. Is the stock price stationary?
  4. Obtain the continuously compounded return of the stocks, denoted as rt, is rt stationary?
  5. Is the return rt consistent with the efficient market hypothesis?
  6. Choose an appropriate model from the ARMA(p,q) family for the returns. You should justify your choice of model using a relevant criterion for model selection
  7. Is there ARCH effect in the returns?
  8. Fit an ARCH(1) model to the return and write down the estimated model.
  9. Is the ARCH(1) model adequate/well specified?
  10. Fit an ARCH(3) model and write down the estimated model (Show whether the model is adequate/well specified)
  11. Fit a GARCH(1,1) model, and estimate and write down the estimated model (Show whether the model is adequate/well specified).
  12. What is “leverage effect” (Provide your own interpretation, Do not copy from online materials)?
  13. Use an appropriate model to estimate the leverage effect in the data. Write down the estimated model.
  14. Plot the News impact curve (NIC) from the ARCH(3) model estimated in (j), the GARCH(1,1) model estimated in (k) and from the model estimated in (m). Discuss and compare the NIC from these two models.
  15. What is the value for γ1, is the sign consistent with your expectation? Why?
  16. Conduct the hypothesis test to determine whether the leverage effect is significant.
  17. What is risk-premium (Provide your own interpretation, Do not copy from online materials)?
  18. Is the risk-premium present in the data? Use an bf appropriate model and test to explain.
  19. Based on the (G)ARCH model used in (j), (k), (m) and (r), which one do you think is most suitable for your data? Explain.

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