The Seventh Annual Volatility and Risk Institute Conference, hosted by NYU Stern on April 24, 2026, featured a research-focused session on "AI for Research," chaired by João Sedoc. Four experts presented cutting-edge papers demonstrating how artificial intelligence and machine learning are transforming financial research.
Key Presentations
Bryan Kelly (Yale School of Management & AQR Capital Management) discussed "The Inefficient Pricing of News," co-authored with Mo Pourmohammadi, Antoine Didisheim, and Hanqing Tian.
Robert Richmond (NYU Stern) presented "Asset Embeddings," a joint work with Xavier Gabaix, Ralph S.J. Koijen, and Motohiro Yogo.
Sebastian Hillenbrand (Harvard Business School) explored "Inflation Uncertainty: Measurement, Causes, and Consequences," co-authored with Viral Acharya, Venky Venkateswaran, and Margaret Underwood.
Sophia Kazinnik (Stanford University) delivered "Ex Machina: Financial Stability in the Age of Artificial Intelligence," co-authored with Kartik Anand, Agnese Leonello, and Ettore Panetti.
The conference highlighted AI's vast potential to enhance productivity, reduce costs, and improve efficiency in finance, particularly through the analysis of massive datasets.