Has oil price predicted stock returns for over a century

By Paresh Kumar Narayan, Rangan Gupta. 2015

360 citations recorded by the source corpus.

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.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/d69a59b84756f1f0072fc64b541754ad5bff91ef

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In Economics and Econometrics

Citations in the corpus

Forecasting oil and stock returns with a Qual VAR using over 150 years of data (2017, methodology): “In the process, we add to the literature on forecasting oil and stock prices or returns (see Huntington et al., (2013), Rapach and Zhou (2013) and Narayan and Gupta (2015) for detailed discussions of the literature on forecasting oil and stock prices (returns) respectively).”
Revisiting oil-stock nexus during COVID-19 pandemic: Some preliminary results (2020, background): “Predicting exchange rate with commodity prices: New evidence from Westerlund and Narayan (2015) estimator with structural breaks and asymmetries.”
Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence (2018, background): “Finally, Narayan and Gupta (2015) suggest that there is evidence of asymmetric oil price effects, given that negative changes in oil prices allow for superior prediction of stock price returns, compared to positive changes.”
Improving the predictability of the oil–US stock nexus: The role of macroeconomic variables (2019, methodology): “Here, the model for the single-factor case ( Sk ) is the parsimonious model, having been found to be a good predictive model for US stock returns by Westerlund and Narayan (2015), while the model for the multiple-factor case ( Mk ) is the larger model.”
Uncertainty Due to Infectious Diseases and Energy Market Volatility (2020, background): “…it also simultaneously resolves any inherent bias (see Westerlund & Narayan, 2012; Westerlund & Narayan, 2015, for the theoretical expositions; and also Narayan & Gupta, 2015; Narayan et al., 2018; Salisu, Raheem, et al., 2019; Salisu, Swaray, et al., 2019, among others, for recent applications).”