VAR model variable selection

External question — Cross Validated Stack Exchange Author: Rakamakafon Original post: https://stats.stackexchange.com/questions/504495 License: CC BY-SA 4.0 — https://creativecommons.org/licenses/by-sa/4.0/ Adaptation: HTML converted to plain text; contact email addresses removed. I'm required to use two time series models in my exam project. I want to use a stock price of an energy company, and then explain it first using ARIMA, and then adding other variables and using VAR. My problem is that I can't find variables which pass the Granger test of causality. I have tried prices of commodities, competitor stock prices, etc. So now I have opted to use two of the same company's stocks, but just listed on different stock exchanges (same company, same currency - one stock trading in Germany, the other in Brussels) Obviously, the stock on both markets is impacted by the same unobserved variables. Is this a huge mistake, or can I proceed if I discuss and show that I am aware of omitted variable bias?

External answer — Cross Validated Stack Exchange Author: Huang Ching Original post: https://stats.stackexchange.com/a/647114 License: CC BY-SA 4.0 — https://creativecommons.org/licenses/by-sa/4.0/ Adaptation: HTML converted to plain text; contact email addresses removed. Maybe it's a bit too late to your exam. I think it's natural that you can't find relationship for stocks, which have high noise to signal. My preliminary thought is that if you want to stick with stock prices, maybe do a grouping based on industry, in your case, electricity stocks, create an index tracking the average return of the industry, and then do the GC test on this new series instead. I think this way it reduces noise and is more likely to find relationship that you are looking for.