Estimate a garch on the residuals of the ols regression

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Reference no: EM132227181

Problem: Feasible GLS

The file size-day-0918.csv contains the retuns on the 10 size-decile portfolios of the US stock market. For this exercise, you will use Decile 2. The goal is to estimate the portfolio beta and alpha. Use only the first 3 years of data for this. If you think you need more data, explain what it is and get it on KF's web site. Don't forget that KF's data are in %.

d) Estimate a GARCH on the residuals of the OLS regression. Report the parameter estimates, plot the time varying standard deviation of the residuals. Use it to construct the Ω matrix and a feasible GLS allowing for GARCH heteroskedasticity. Report your GLS estimate and its standard errors.

e) Starting from d). Implement a simple loop to iterate your GLS. Save the estimate at each iteration. Stop the iteration when the % change in the estimates is less than 0.5%. Is the final estimate very different from the initial one?

f) Explain but do not do it, how you would implement a feasible GLS accounting for both autocorrelation and heteroskedasticity.

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Autocorrelation is a characteristic of data in which the correlation between the values of the same variables is based on related objects.It violates the assumption of instance independence, which underlies most of the conventional models.

Reference no: EM132227181

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Reviews

inf2227181

7/24/2019 2:14:05 AM

Here is the data 31640147_1size-day-0918.csv here is the material 31640122_1EJ1Review-Inference.pdf Use R to solve the problem, attach R code I need the study materials which would be very useful in working with this task. Kindly get the same.. I think this is the material you may need to use in this problem, but I already sent you once. 31640112_1EJ1Review-Inference.pdf Are you done with the assignment ok, how long time do you still need to work on? Thanks for delivering the work on time R code assignments creates so much pressure on me since I am not good at all in this Lang. thanks for the help, I will come up with new assignment soon.

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