Using Machine Learning to Identify Drivers of Oil Price

Follow us on LinkedIn

Machine learning is a subset of artificial intelligence that deals with the creation of algorithms that can learn from, and make predictions on, data. These algorithms are able to automatically improve given more data.

Machine learning is a powerful tool that can be used for a variety of tasks, such as detecting fraud, making financial predictions, and automating investment decisions. In the world of finance, machine learning is being used in a number of different ways.

For example, machine learning is being used to develop better credit scoring models. These models are used to assess an individual’s creditworthiness and are important in determining whether or not a person will be approved for a loan.

Machine learning is also being used to create algorithms that can trade stocks and other financial instruments automatically. These algorithms are able to make decisions based on data and can execute trades in a fraction of a second.

Reference [1] utilized a random forest model based on 1000 regression trees to identify different economic and financial factors that impact the price of oil. It identified the interest rates, the dollar, and the VIX index as the important drivers of the oil price.

All in all, the analysis finds strong relative performance of random forests in predicting monthly oil price changes. The performance of this purely data driven method, relative to more traditional linear methods, is likely driven by its ability to accommodate nonlinear effects and interactions between explanatory variables.

The model which was presented relies on much more timely data inputs (at daily frequency). This is particularly important, as the model promptly incorporates changes that may be occurring in financial markets. The large role of these factors in reducing prediction errors only underscores the importance of interpreting spot crude oil as an asset price.

In short, a pure data-driven method was successfully developed to identify economic and financial factors that impact the price of oil.

References

[1]  Emanuel Kohlscheen, Quantifying the Role of Interest Rates, the Dollar and Covid in Oil Prices, https://doi.org/10.48550/arXiv.2208.14254

Further questions

What's your question? Ask it in the discussion forum

Have an answer to the questions below? Post it here or in the forum

LATEST NEWSXcel Energy utility equipment started Texas wildfire, homeowner says in lawsuit
Xcel Energy utility equipment started Texas wildfire, homeowner says in lawsuit
Stay up-to-date with the latest news - click here
LATEST NEWSEarnings call: Dentsply Sirona sees growth in key segments, plans for 2024
Earnings call: Dentsply Sirona sees growth in key segments, plans for 2024
Stay up-to-date with the latest news - click here
LATEST NEWSEpsilon Energy Ltd. Announces the Following Headlines
Epsilon Energy Ltd. Announces the Following Headlines

Board declares dividend of $0.0625 per common share Company announces the timing of its 2023 year end earnings release and conference call HOUSTON, March 01, 2024 (GLOBE NEWSWIRE) — Epsilon Energy Ltd. (“Epsilon” or the “Company”) (NASDAQ: EPSN) today announced that its Board of Directors…

Stay up-to-date with the latest news - click here
LATEST NEWSHow Apache Stronghold’s fight to protect Oak Flat in central Arizona has played out over the years
How Apache Stronghold’s fight to protect Oak Flat in central Arizona has played out over the years

PHOENIX (AP) — Oak Flat, a piece of national forest land in central Arizona, is at the heart of a yearslong struggle between Native American groups and mining interests that both consider it important for their future. Resolution Copper, a subsidiary of international mining giants…

Stay up-to-date with the latest news - click here
LATEST NEWSBayer wins Arkansas trial over Roundup cancer claims
Bayer wins Arkansas trial over Roundup cancer claims
Stay up-to-date with the latest news - click here

Leave a Reply