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Oil and risk premia in equity markets

Author

Listed:
  • Satish Kumar
  • Riza Demirer
  • Aviral Kumar Tiwari

Abstract

Purpose - This study aims to explore the oil–stock market nexus from a novel angle by examining the predictive role of oil prices over the excess returns associated with the market, size, book-to-market and momentum factors via bivariate cross-quantilograms. Design/methodology/approach - This study makes use of the bivariate cross-quantilogram methodology recently developed by Hanet al.(2016) to analyze the predictability patterns across the oil and stock markets by focusing on various quantiles that formally distinguish between normal, bull and bear as well as extreme market states. Findings - The study analysis of systematic risk premia across the four regions shows that crude oil returns indeed capture predictive information regarding excess factor returns in stock markets, particularly those associated with market, size and momentum factors. However, the predictive power of oil return over excess factor returns is asymmetric and primarily concentrated on extreme quantiles, suggesting that large fluctuations in oil prices capture markedly different predictive information over stock market risk premia during up and down states of the oil market. Practical implications - The findings have significant implications for the profitability of factor- or style-based active portfolio strategies and suggest that the predictive information contained in oil market fluctuations could be used to enhance returns via conditional strategies based on these predictability patterns. Originality/value - This study contributes to the vast literature on the oil–stock market nexus from a novel perspective by exploring the effect of oil price fluctuations on the risk premia associated with the systematic risk factors including market, size, value and momentum.

Suggested Citation

  • Satish Kumar & Riza Demirer & Aviral Kumar Tiwari, 2020. "Oil and risk premia in equity markets," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 37(4), pages 697-723, September.
  • Handle: RePEc:eme:sefpps:sef-03-2020-0059
    DOI: 10.1108/SEF-03-2020-0059
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    Citations

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    Cited by:

    1. Popkova, Elena G. & Bogoviz, Aleksei V. & Lobova, Svetlana V. & DeLo, Piper & Alekseev, Alexander N. & Sergi, Bruno S., 2023. "Environmentally sustainable policies in the petroleum sector through the lens of industry 4.0. Russians Lukoil and Gazprom: The COVID-19 crisis of 2020 vs sanctions crisis of 2022," Resources Policy, Elsevier, vol. 84(C).
    2. Nonejad, Nima, 2022. "Equity premium prediction using the price of crude oil: Uncovering the nonlinear predictive impact," Energy Economics, Elsevier, vol. 115(C).
    3. Mehmet Balcilar & Riza Demirer & Festus V. Bekun, 2021. "Flexible Time-Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold," Mathematics, MDPI, vol. 9(8), pages 1-20, April.

    More about this item

    Keywords

    Predictability; Quantile; Cross-quantilogram; Risk premia; Oil return; C22; F31;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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