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Investor Attention to Fossil Fuel Divestment Movement and Stock Returns

Imane El Ouadghiri, Mathieu Gomes, Jonathan Peillex, and Guillaume Pijourlet

Year: 2022
Volume: Volume 43
Number: Number 6
DOI: 10.5547/01956574.43.6.ioua
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Abstract:
This study investigates whether the investor attention to the fossil fuel divestment (FFD) movement is related to the stock returns on firms involved in extracting fossil fuels. Three complementary indicators of investor attention to the FFD movement are considered: (1) the U.S. weekly Google Search Volume Index on the topic "fossil fuel divestment," (2) the U.S. weekly media coverage of fossil fuel divestment, and (3) the number of weekly visits to the "fossil fuel divestment" page on Wikipedia. Based on a sample of weekly returns on 1,850 U.S. firms over the period 2012–2020, our econometric estimations report a positive relationship between investor attention to FFD and excess stock returns for U.S. fossil fuel–related firms. Therefore, contrary to what the FFD campaigners might expect, the stigmatization of the fossil fuel industry does not drive down the stock returns on fossil fuel–related firms.



News Media and Attention Spillover across Energy Markets: A Powerful Predictor of Crude Oil Futures Prices

Oguzhan Cepni, Duc Khuong Nguyen, and Ahmet Sensoy

Year: 2022
Volume: Volume 43
Number: Special Issue
DOI: 10.5547/01956574.43.SI1.ocep
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Abstract:
We develop two news-based investor attention measures from the news trends function of the Bloomberg terminal and investigate their predictive power for returns on crude oil futures contracts with various maturities. Our main results after controlling for relevant macroeconomic variables show that the Oil-based Institutional Attention Index is useful in predicting oil futures returns, especially during price downturn periods, while the forecasting accuracy is further improved when the Commodity Market Institutional Attention Index is used. This forecasting accuracy decreases, however, with the maturity of oil futures contracts. Moreover, we find some evidence of Granger-causality and regime-dependent interactions between investor attention measures and oil futures returns. Finally, variable selection algorithms matter before making predictions since they create the best forecasting results in many cases considered. These findings are important for informed traders and policymakers to better understand the price dynamics of the oil markets.





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