Peer Review

[petereman1337]

This project is trying to predict the price of oil, plain and simple. They will be using Bloomberg data for WTI Crude futures, macro indicators, and other indicator variables for natural disasters.

I like that the proposal's objective is clear and concise. The dataset being used is large and easily obtainable as well. Finally, there is undoubtedly a business need to make sense of such a volatile, unpredictable asset with methods more sophisticated than just using time series forecasting.

However, is the business need really what the project claims, which is to help prevent an oil shortage? Accurately predicting the future price of oil could be useful to either hedge against these price changes or to speculate on them, but preventing an oil shortage is a political and a foreign policy issue beyond the scope of machine learning. I would restructure your problem statement to not include the more grand issue of a shortage and purely focus on price prediction for financial / risk management purposes. If you are looking at oil dynamics on a global level, you may want to look at more than just WTI Crude prices (ex: look at Brent Crude as well). Finally, the project doesn't state which methods or algorithms it will be using- will it be mostly regression?