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Artificial Intelligence in Asset Management

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Artificial Intelligence in Asset Management

Artificial intelligence (AI) has grown in presence in asset management and has revolutionized the sector in many ways. It has improved portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance. In particular, AI techniques help construct portfolios based on more accurate risk and return forecasts and more complex constraints. Trading algorithms use AI to devise novel trading signals and execute trades with lower transaction costs. AI also improves risk modeling and forecasting by generating insights from new data sources. Finally, robo-advisors owe a large part of their success to AI techniques. Yet the use of AI can also create new risks and challenges, such as those resulting from model opacity, complexity, and reliance on data integrity.

About the Authors

Söhnke M. Bartram

Söhnke M. Bartram is a research fellow, Centre for Economic Policy Research, and professor of finance, University of Warwick, Warwick Business School Department of Finance.

Jürgen Branke

Jürgen Branke is professor of operational research and systems, University of Warwick, Warwick Business School.

Mehrshad Motahari

Mehrshad Motahari is a research associate at Cambridge Centre for Finance and Cambridge Endowment for Research in Finance, University of Cambridge, Cambridge Judge Business School.