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The goal of our analysis was to use different time series methods to predict the oil price for the last 6 months of the data, September 2017 through February 2018, and determine the best prediction model for this data.
This project highlights a Spark application built on Scala. It utilizes Spark Core, Spark SQL and Spark ML (Machine Learning libraries) for predicting stock prices of specific airline companies. We have used the Google trending words (searched on internet and relevant to financial domain) and also macro-economic oil prices as alternate data to p…
Problem to solve: Determine what role oil plays in the Russia economy and predict outcomes in the years to come. Data: year (From 2004 to 2018), oilprice (The spot price of a barrel (159 liters) of benchmark crude oil in US dollars, gpd (Gross domestic product in billions of US dollars