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.
Authors | Jaddoa, A., Alshabandar, R. and Hussain, A. |
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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. |
Keywords | Modern portfolio theory; Conditional value at risk; Consumer price index |
Year | 2023 |
Book title | Advanced Intelligent Computing Technology and Applications 19th International Conference, ICIC 2023, Zhengzhou, China, August 10–13, 2023, Proceedings, Part V |
Publisher | Springer |
Output status | Published |
Place of publication | Singapore |
Series | Lecture Notes in Computer Science |
ISBN | 9789819947607 |
9789819947614 | |
Publication dates | |
Online | 31 Jul 2023 |
Publication process dates | |
Deposited | 09 Aug 2023 |
Official URL | https://link.springer.com/chapter/10.1007/978-981-99-4761-4_41 |
Event | International Conference on Intelligent Computing |
https://repository.canterbury.ac.uk/item/953y5/a-risk-model-for-assessing-exposure-factors-influence-oil-price-fluctuations
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