Analyze the Growth Rate of Price using Machine Learning

DOI

10.2991/aebmr.k.220307.151How to use a DOI?

Keywords

Crude Oil price; Machine Learning; Share Price; Linear Regression

Abstract

People buy things every day, and the prices of different items change every day for various reasons, such as economic or political issues. This paper will focus on the crude oil price. Crude Oil plays a significant role in the stability of the world economy, and it is also one of the indispensable materials in human modern social life. However, crude oil prices are not always stable, and there are many internal and external factors that determine oil prices. This report will build a Linear Regression Model, and the share price of the oil industry, US dollar index, and the inflation rate will be selected as features. The coefficients of these factors are calculated in order to see how these factors affect the growth rate of oil prices. Each feature selected in this paper is independent of the other. In the real world, these features sometimes affect the price at the same time. Some other features cannot be represented by numbers, so it is very difficult to analyze the growth rate of price. There are many other factors that affect the price of crude oil, so it is difficult to analyze what affects affect more. The linear Regression model might not be the best for analyzing prices. Besides Linear Regression, there are still many models for analyzing prices. Also, the paper did not consider all the problems.

Copyright

© 2022 The Authors. Published by Atlantis Press International B.V.

Open Access

This is an open access article under the CC BY-NC license.

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TY  - CONF
AU  - Yuxiao He
PY  - 2022
DA  - 2022/03/26
TI  - Analyze the Growth Rate of Price using Machine Learning
BT  - Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022)
PB  - Atlantis Press
SP  - 926
EP  - 930
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.220307.151
DO  - 10.2991/aebmr.k.220307.151
ID  - He2022
ER  -