For this assignment, I am trying to find the covariates of lumber and test the lead-lag relationships. To test, I am thinking to do a linear regression and see if the two are correlated using either...

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For this assignment, I am trying to find the covariates of lumber and test the lead-lag relationships.

To test, I am thinking to do a linear regression and see if the two are correlated using either prices or returns (both would be ideal). You can use the close price ($). If expert feels something like an ANCOVA is necessary, that is also fine.

Also check to see if one leads/ lags the other.

Please run the regression for those against Lumber (IE you don’t need to run a linear regression on corn vs oil, but run it on corn vs. lumber and oil vs. lumber). Thank you!

CL=F is oil, ZC=F is Corn, HG=F is copper, LBS=f is Lumber, ETH is Ethereum (the cryptocurrency, GC=F is gold, and ALI=f is aluminum.

The last thing I want to test as a covariate is number of homes sold and the median price of those homes sold. I am unsure where to get that data – but maybe zillow, FRED, or census may have it. Let me know if expert is able to get this data. The test here would be to see if there is a correlation between lumber prices and number of homes sold, or lumber price and median price of the homes sold. I know the housing data only comes monthly - so I included LBS=Fmonthly as the monthly data. All the other data sets are daily. Thank you!


Please include interpretation for all of the results, as well as a conclusion of which is the best covariate, and whether there is a lead-lag relationship between any of them.

Answered Same DayMay 11, 2021

Solution

Mohd answered on May 12 2021
23 Votes
Regression
Regression
-
5/12/2021
knitr::opts_chunk$set(echo = TRUE,cache = TRUE,warning = FALSE,message = FALSE,dpi = 180,fig.width = 8,fig.height = 5)
We have run first...
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