Tag: Natural Language Processing

Understanding climate-related disclosures of UK financial institutions

Jonathan Acosta-Smith, Benjamin Guin, Mauricio Salgado-Moreno and Quynh-Anh Vo

Over the past years, a growing consensus has acknowledged the need to construct a ‘system [wherein] every financial decision takes climate change into account‘. While such a system is still far from reality, market participants already produce and demand an increasing amount of climate-related information. Equally, many authorities around the world are considering mandatory climate-related reporting. These developments raise myriad unanswered questions. We focus on the following in a recent working paper:

  1. How have voluntary, climate-related disclosures of UK financial institutions changed over time?
  2. Can prudential regulators influence current climate-reporting levels just by announcing a future shift to mandatory reporting?

This post summarises the main insights from this paper.

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Animal spirits and environmental, social and governance asset prices: does market sentiment drive stock returns?

Gerardo Martinez

In 1936, John Maynard Keynes coined the famous term ‘Animal Spirits’ to illustrate how people take decisions based on urges, overlooking the benefits and drawbacks of their actions. To what extent are prices of Environmental, Social and Governance (ESG) assets driven by the sentiment of market participants, as opposed to economic fundamentals? To answer this question, I make use of Natural Language Processing (NLP) tools and an original corpus of tweets to capture market sentiment around climate change. Estimating a factor model, I find that sentiment is associated with immediate returns of climate change related stock indices. These results are stronger for days with the most extreme returns. Market sentiment might be particularly useful in explaining large movements in ESG asset prices.

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