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The (time-varying) Importance of Oil Prices to U.S. Stock Returns: A Tale of Two Beauty-Contests

David C. Broadstock and George Filis

Year: 2020
Volume: Volume 41
Number: Number 6
DOI: 10.5547/01956574.41.6.dbro
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Abstract:
We evaluate the probability that oil prices affect excess stock returns for U.S. listed firms. The probabilities are obtained from a time-varying multi-factor asset pricing framework estimated using dynamic model averaging techniques, including oil price information among several other possible risk factors. Two widely used oil price measures are considered, one based on raw oil price changes and another based on disentangling the source of oil price changes due to supply-side or demand-side effects. As far as we know our dataset, which comprises 10,118 stock price series with up to 25,372,588 observations between 1995�2018, is the most comprehensive used for this purpose. We develop two �beauty-contests� in which we estimate the multi-factor models separately for individual stocks, for each of the two oil price measures. The results suggests that, when working with daily data (beauty contest 1), oil price changes are a significant (important) determinant for around 1�3% of the sample. When using oil price shocks�as opposed to oil price changes�(beauty contest 2) this percentage increases to 27�45%, suggesting that oil supply and demand shocks (as opposed to oil price changes) can better explain firm-level excess returns, at least for monthly frequency data where such a decomposition is available. We provide evidence that the increase in percentage is only partially attributable to data-frequency, and more likely attributed to the decomposition into supply/demand driven oil price changes. We reconcile differences between our findings and those reported in previous literature on the basis of the fully dynamic nature of our adopted methodology.



Selling Wind

Ali Kakhbod, Asuman Ozdaglar, and Ian Schneider

Year: 2021
Volume: Volume 42
Number: Number 1
DOI: 10.5547/01956574.42.1.akak
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Abstract:
We investigate the strategic behavior of wind producers in the presence of uncertain wind resource availability, where wind availability is correlated across firms. We study how the level of correlation between different firms' wind resources impacts strategy and market outcomes. The main insight of our analysis is that increasing heterogeneity in resource availability improves social welfare, as a function of its effects both on improving diversification and on reducing withholding by firms. We show that this insight is robust for common assumptions regarding electricity demand. The model is also used to analyze the effect of wind resource heterogeneity on firm profits and opportunities for collusion. Finally, we analyze the impacts of improving public information and weather forecasting; enhanced public forecasting increases welfare, but it is not always in the best interests of strategic producers.





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