Evaluation and prediction of polyolefin price development

Marek Vochozka, Lenka Neuschlova, Jana Janikova

ACTA MONTANISTICA SLOVACA(2023)

引用 0|浏览0
暂无评分
摘要
Over the past three years, many unprecedented events have happened which have significantly influenced the whole world. This paper deals with several topical issues, such as the impact of the coronavirus pandemic on Brent's oil prices, on the price of plastics, specifically polyolefins, i.e., polyethene and polypropylene, price trends of petroleum products, in different crisis periods from 2006 to the present and predicts the price trend of petroleum products (polyolefins) using artificial intelligence. In the application part of the research, the following research methods were used: time series regression using neural networks and correlation and regression analysis. Neural networks confirmed a significant effect of the coronavirus pandemic on Brent's oil price. Correlation analysis showed a long-term comparable trend in the development of Brent oil and polyolefin prices, which is a confirmation of the significant impact of COVID-19 on the price of polyethene and polypropylene. The greatest benefit of this research for the application sphere is the prediction of the price development of polyolefins. All generated variants of the ANS neural network module predict a decreasing trend of polypropylene and polyethene prices until the end of 2023. The conducted research on the prices of polyolefins is a unique study with practical benefits for companies producing the most in-demand material in the world - plastic. Analysing and predicting the price development of the commodities under study can be useful for entities in their strategic assessment and subsequent investment decisions. A limitation of the research is the ongoing war conflict in Ukraine, as the oil market is sensitive to political conflicts and becomes difficult to control and predict.
更多
查看译文
关键词
Oil,polyolefin,Prediction,price trend,neural networks,COVID-19,war in Ukraine
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要