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Has oil price predicted stock returns for over a century?

Version 2 2024-06-18, 05:38
Version 1 2018-03-13, 12:31
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posted on 2024-06-18, 05:38 authored by PK Narayan, R Gupta
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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Pagination

1-23

Language

eng

Notes

School working paper (Deakin University. School of Accounting, Economics and Finance) ; 2015/08 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.

Publication classification

CN.1 Other journal article

Copyright notice

2015, The Authors

Publisher

Deakin University,School of Accounting, Economics and Finance

Place of publication

Geelong, Vic.

Series

School Working Paper - Financial Econometrics Series ; SWP 2015/08

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