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Title: | Oil Price Volatility and Its Impact on Industry Stock Return – Bi Variate Analysis |
Authors: | Bhat, Sandesh Ramakant Yadav, J Shashidhar Kumar, C M Naveen Amar, H A Rakesh, N Kumar, S V Pradeep |
Keywords: | Deep Learning Model Oil Price Volatility Returns Risk Factor Volatility Spillovers |
Issue Date: | 2024 |
Publisher: | Lecture Notes in Networks and Systems Springer Science and Business Media Deutschland GmbH |
Citation: | Vol. 1080 LNNS; pp. 102-111 |
Abstract: | Oil price volatility impacts industries differently depending on a country’s status as a net oil importer or exporter. In oil-importing nations like India, sectors such as banking, energy, materials, retailing, transportation, and manufacturing are adversely affected by price fluctuations, while industries like food, beverages, and pharmaceuticals tend to be more resilient. Conversely, oil-exporting countries experience milder effects, with the oil and gas sector bearing the brunt of supply disruptions while other industries remain insulated. Over time, the correlation between oil prices and stock market performance has strengthened, making oil price volatility a systemic risk factor. The source of oil price shocks, whether from demand changes or supply disruptions, significantly influences their impact on stock returns. Notably, there are substantial volatility spillovers between oil and stock markets. This study aims to explore the relationship between oil shocks and industry returns using various multivariate models, highlighting the importance of considering oil as a relevant risk factor in portfolio management. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. |
URI: | https://doi.org/10.1007/978-3-031-67444-0_10 https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16746 |
ISBN: | 9783031674433 |
ISSN: | 2367-3370 |
Appears in Collections: | Conference Papers |
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