معرفی
Andreas Neuhierl is an Assistant Professor of Finance at the Olin Business School, Washington University in St. Louis. His research focuses on asset pricing, financial econometrics, machine learning, macroeconomics, and commodity markets. He explores the intersection of advanced analytical methods and financial market dynamics, with a particular interest in forecasting, data integrity, and policy impacts.
His work bridges theoretical frameworks with empirical applications, addressing topics like the influence of accounting rules on bond markets, machine learning uncertainties in asset pricing models, and the implications of missing data in financial studies. Recent projects examine noise in economic forecasts, segmentation premia in asset markets, and deep learning techniques for stock index predictions.
Neuhierl has contributed to understanding FOMC meeting effects on momentum strategies, commodity market financialization, and the robustness of arbitrage portfolios. His research often critiques data snooping biases and emphasizes methodological rigor in empirical finance.
