A risk model for assessing exposure factors influence oil price fluctuations

Book chapter

Jaddoa, A., Alshabandar, R. and Hussain, A. 2023. A risk model for assessing exposure factors influence oil price fluctuations. in: Advanced Intelligent Computing Technology and Applications 19th International Conference, ICIC 2023, Zhengzhou, China, August 10–13, 2023, Proceedings, Part V Singapore Springer.
AuthorsJaddoa, A., Alshabandar, R. and Hussain, A.
Abstract

The impact of oil price volatility on the global economy is considerable. However, the uncertainty of crude oil prices is affected by many risk factors. Several prior studies have examined the factors that impact oil price fluctuations, but these methods are unable to indicate their dynamic non-fundamental factors. To address this issue, we propose a risk model inspired by the Mean-Variance Portfolio theory. The model can automatically construct optimal portfolios that seek to maximize returns with the lowest level of risk without needing human intervention. The results demonstrate a significant asymmetric cointegrating correlation between oil price volatility and non-fundamental factors.

KeywordsModern portfolio theory; Conditional value at risk; Consumer price index
Year2023
Book titleAdvanced Intelligent Computing Technology and Applications 19th International Conference, ICIC 2023, Zhengzhou, China, August 10–13, 2023, Proceedings, Part V
PublisherSpringer
Output statusPublished
Place of publicationSingapore
SeriesLecture Notes in Computer Science
ISBN9789819947607
9789819947614
Publication dates
Online31 Jul 2023
Publication process dates
Deposited09 Aug 2023
Official URLhttps://link.springer.com/chapter/10.1007/978-981-99-4761-4_41
EventInternational Conference on Intelligent Computing
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