Predicting Commodity Prices Using Time Series Analysis
The objective of this project is to develop a robust time series model that can predict future prices of key global commodities. This prediction model leverages historical price data to forecast future price movements. In our implementation, we have predicted the Fuel Price Index.
- Project Notebook
- Data
- Project Report
The dataset includes monthly prices and indexes for 53 commodities from 1992 to 2014, with 2005 as the reference year for indexes (value = 100). Key categories in the dataset include:
- All Commodity
- Food and Beverage
- Food
- Beverage
- Fuel Energy
Each category is represented by its respective price index.