Risk factors in stock returns of U.S. oil and gas companies: evidence from quantile regression analysis

Sunil K. Mohanty (), Stein Frydenberg (), Petter Osmundsen, Sjur Westgaard () and Christian Skjøld ()
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Sunil K. Mohanty: Brooklyn College of the City University of New York (CUNY)
Stein Frydenberg: Norwegian University of Science and Technology
Sjur Westgaard: Norwegian University of Science and Technology
Christian Skjøld: Norwegian University of Life Sciences

Review of Quantitative Finance and Accounting, 2023, vol. 60, issue 2, No 10, 715-746

Abstract: Abstract The boom and bust in oil prices during the last two decades have attracted many investors to oil and gas companies in search of returns and risk diversification benefits. This study analyzes the impact of several risk factors, including oil and gas prices, overall stock market returns, stock market volatility index, and the trade-weighted U.S. Dollar Index (DXY) on stock returns of U.S. oil and gas companies, using a quantile regression (QR) method. The findings suggest that most firms in the U.S. oil and gas sector have significant risk exposures to changes in market portfolio returns and oil prices. The analysis also reveals that risk factor sensitivities are not equal across quantiles, indicating asymmetric responses of oil and gas stock returns to various systematic risk factors. Changes in oil prices, in general, are likely to have the strongest impact in the left tail, and this impact gradually decreases toward the right tail. This implies that an investor with a long position in an oil and gas stock will be exposed to a substantially greater risk than an investor with a short position.

Keywords: Stock returns; Crude oil; Value at Risk (VaR); Oil and gas industry; Quantile regression (search for similar items in EconPapers)
JEL-codes: C22 C3 C58 G12 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11156-022-01107-2

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