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      Firm‐Level Climate Change Exposure

      , , ,
      The Journal of Finance
      Wiley

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          ABSTRACT

          We develop a method that identifies the attention paid by earnings call participants to firms' climate change exposures. The method adapts a machine learning keyword discovery algorithm and captures exposures related to opportunity, physical, and regulatory shocks associated with climate change. The measures are available for more than 10,000 firms from 34 countries between 2002 and 2020. We show that the measures are useful in predicting important real outcomes related to the net‐zero transition, in particular, job creation in disruptive green technologies and green patenting, and that they contain information that is priced in options and equity markets.

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          Measuring Economic Policy Uncertainty

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            Risk, Return, and Equilibrium: Empirical Tests

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              On Persistence in Mutual Fund Performance

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                Author and article information

                Journal
                The Journal of Finance
                The Journal of Finance
                Wiley
                0022-1082
                1540-6261
                June 2023
                March 31 2023
                June 2023
                : 78
                : 3
                : 1449-1498
                Article
                10.1111/jofi.13219
                3ecf0810-7df9-4c2a-92c1-5c7c1957d715
                © 2023

                http://creativecommons.org/licenses/by/4.0/

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