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We apply machine learning techniques and use stock characteristics to predict the cross-section of stock returns in 33 international markets. We conduct a stringent out-of-sample test to examine concerns about overfitting: the models are trained with past U.S. data and used to predict...
Persistent link: https://www.econbiz.de/10012846699
We find that people revise their beliefs about climate change upward when experiencing warmer than usual temperatures in their area. Using international data, we show that attention to climate change, as proxied by Google search volume, increases when the local temperature is abnormally high. In...
Persistent link: https://www.econbiz.de/10012852282
We examine the actions of financial institutions and firms regarding greenhouse gas emissions. We find that financial institutions around the world reduce their exposure to stocks of high-emission industries after 2015, especially for those located in high-climate-awareness countries, suggesting...
Persistent link: https://www.econbiz.de/10012835398
We introduce a simple definition of carbon-intensive firms to measure institutional investors' exposure to the emission intensities of portfolio companies. The definition is based on major emission industry sectors identified by the Intergovernmental Panel on Climate Change (IPCC). All firms in...
Persistent link: https://www.econbiz.de/10012840102
Persistent link: https://www.econbiz.de/10012198064