The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Has oil price predicted stock returns for over a century?
Open accessAbstract
This paper contributes to the debate on the role of oil prices in predicting stock returns. The novelty of the paper is that it considers monthly time-series historical data that span over 150 years (1859:10-2013:12) and applies a predictive regression model that accommodates three salient features of the data, namely, a persistent and endogenous oil price, and model heteroskedasticity. Three key findings are unraveled: First, oil price predicts US stock returns. Second, in-sample evidence is corroborated by out-sample evidence of predictability. Third, both positive and negative oil price changes are important predictors of US stock returns, with negative changes relatively more important. Our results are robust to the use of different estimators and choice of in-sample periods.
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Cites
A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets
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Predicting excess stock returns out of sample: Can anything beat the historical average?
Campbell, J. Y., & Thompson, S. B. (2008) · Review of Financial Studies · doi:10.1093/rfs/hhm055 · Cited by 2,919
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Lewellen, J. (2004) · Journal of Financial Economics · doi:10.1016/j.jfineco.2002.11.002 · Cited by 972
Asymptotics for out of sample tests of Granger causality
McCracken, M. W. (2007) · Journal of Econometrics · doi:10.1016/j.jeconom.2006.07.020 · Cited by 696
Do industries lead stock markets?
Hong, H., Torous, W., & Valkanov, R. (2007) · Journal of Financial Economics · doi:10.1016/j.jfineco.2005.09.010 · Cited by 666
Driesprong, G., Jacobsen, B., & Maat, B. (2008) · Journal of Financial Economics · doi:10.1016/j.jfineco.2007.07.008 · Cited by 615
Rapach, D., & Zhou, G. (2013) · Handbook of Economic Forecasting · doi:10.1016/b978-0-444-53683-9.00006-2 · Cited by 613
New evidence on oil price and firm returns
Narayan, P. K., & Sharma, S. S. (2011) · Journal of Banking & Finance · doi:10.1016/j.jbankfin.2011.05.010 · Cited by 532
Self-citationNONLINEARITIES AND THE MACROECONOMIC EFFECTS OF OIL PRICES
Hamilton, J. D. (2011) · Macroeconomic Dynamics · doi:10.1017/s1365100511000307 · Cited by 468
Oil price shocks and industry stock returns
Elyasiani, E., Mansur, I., & Odusami, B. (2011) · Energy Economics · doi:10.1016/j.eneco.2011.03.013 · Cited by 363
Cited by
Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence
Degiannakis, S., Filis, G., & Arora, V. (2018) · The Energy Journal · doi:10.5547/01956574.39.5.sdeg · Cited by 298
Can economic policy uncertainty predict stock returns? Global evidence
Phan, D. H. B., Sharma, S. S., & Tran, V. T. (2018) · Journal of International Financial Markets, Institutions and Money · doi:10.1016/j.intfin.2018.04.004 · Cited by 282
What do we know about oil prices and stock returns?
Smyth, R., & Narayan, P. K. (2018) · International Review of Financial Analysis · doi:10.1016/j.irfa.2018.03.010 · Cited by 266
Self-citationXiao, J., Zhou, M., Wen, F., & Wen, F. (2018) · Energy Economics · doi:10.1016/j.eneco.2018.07.026 · Cited by 266
Constructing a Global Fear Index for the COVID-19 Pandemic
Salisu, A. A., & Akanni, L. O. (2020) · Emerging Markets Finance and Trade · doi:10.1080/1540496x.2020.1785424 · Cited by 265
Metadata
- Authors
- Narayan, P. K., & Gupta, R.
- Venue
- Energy Economics
- Publisher
- Elsevier BV
- Published
- 2015-03
- Volume
- 48
- Pages
- 18-23
- ISSN
- 0140-9883 (ISSN-L)
- OpenAlex
- W2033343256
- Cited by
- 351
- References
- 20
- FWCI
- 34.42
- Type
- journal article
- Language
- en
- Open access
- green
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- Narayan, P. K., & Gupta, R. (2015). Has oil price predicted stock returns for over a century? Energy Economics. https://doi.org/10.1016/j.eneco.2014.11.018
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
