The way we understand economics and its influence on financial markets is largely driven by expectations for the future. Financial markets and the commentary written about them naturally look to the future to understand what might happen next even though we only have information about what has already happened. The concept of ‘expectations’ is shorthand for the way we create a story with the data we do know, influenced by ‘sentiment’ about economic outcomes today and in the future.

Concepts like expectations and sentiment are difficult to measure in real-time and often rely on infrequent surveys. This infrequency and reliance on often small samples make it difficult to track how expectations are changing, except indirectly through the impact these changes have on financial data.

We have interviewed researchers at the University of Buckingham, University College London, Rutgers and Princeton who are training an AI model with the input from finance sector experts that they expect will help to evaluate sentiment from a richer and higher-frequency universe of articles to see if AI can help to more clearly deduce expectations than the methods used today.

This is an important project to understand how financial sector players create and update their perceptions of risk, which influences how external shocks to the economy and financial system are transmitted through the industry. The increase in impacts of climate change on the physical world and economy will represent a continuous series of ‘shocks’ to the physical environment and economy. A better understanding of the way that exogenous shocks are transmitted through the financial sector will be important to safeguarding against future crises.

The project discussed in the interview below also provides an opportunity for people with experience in the financial sector whose experience includes assessing types of financial risks. We have provided a form if you would like more information about participating in the project. The form should take about an hour to complete. Participants will receive information about the project and its results, and will have an opportunity to use the AI model that is being trained after the project concludes.