AI & Machine Learning in Finance

Annual Conference at the Swedish House of Finance in Stockholm on 22-23 August 2022.

The Swedish House of Finance Annual Conference brought together leading academics and practitioners in the field of financial economics.

The abundance of data and new technology is fundamentally changing financial services. This year's conference focused on how Artificial Intelligence and Machine Learning are impacting the finance industry.

The conference was taking place on August 22-23, 2022. The first day consisted of academic keynote presentations and industry panel discussions. That day was primarily targeted to industry and government participants.

Some of the topics discussed:

  • Algorithm Aversion: Evidence from Robo-Advice
  • Algorithmic Discrimination in Credit Markets
  • Using AI and Machine Learning to Improve Investment Decisions
  • Stock Picking and Pricing Financial Assets in the Era of Big Data
  • Applications in the Financial Industry – Case Studies

First day of the conference

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Bryan T. KellyFinance Professor at Yale School of Management and Head of ML at AQR Capital Management.

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Stefan NagelFinance Professor at Chicago Booth School of Business at the University of Chicago.

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Tarun RamadoraiProfessor of Financial Economics at Imperial College London.

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Thierry FoucaultHEC Foundation Chaired Professor of Finance at HEC, Paris.

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Svante BergströmCEO and Founding Partner, Lynx Asset Management

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Kathryn KaminskiChief Research Strategist at AlphaSimplex

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Sara ÖhrvallAdvisor and digital strategist, Axel Johnson

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Erik ThedéenDirector General of Finansinspektionen, the Swedish Financial Supervisory Authority.

Sven TörnkvistCDO and Head of EQT Digital

Second day of the conference

Academic conference. Researchers presented and discussed new studies on the influence of AI and Machine Learning in different areas of finance:

  • Asaf Manela, Washington University, "Does Finance Benefit Society? A Language Embedding Approach".
  • Jillian Popadak Grennan, Duke University, Fuqua School of Business, "Artificial Intelligence and High-Skilled Work: Evidence from Analysts".
  • Alejandro Lopez-Lira, University of Florida, "Textual Analysis of Short-seller Research Reports, Stock Prices and Real Investment".
  • Leonidas Barbopoulos, University of Edinburgh, "Market Efficiency in the Age of Machine Learning".
  • Sean Cao, Maryland University, "From Man vs. Machine to Man + Machine: The Art and AI of Stock Analyses".
  • Simona Abis, Columbia Business School, "The Changing Economics of Knowledge Production".
  • Sudheer Chava, Georgia Institute of Technology, "Measuring Firm-Level Inflation Exposure: A Deep Learning Approach".