Daniel Buncic

Daniel Buncic is Professor of Finance at Stockholm Business School, Stockholm University, specializing in empirical finance, macroeconomics, and econometrics. He holds a Ph.D. in Economics from the University of New South Wales and has held positions at Sveriges Riksbank and the University of St. Gallen. His research integrates machine learning with traditional econometric methods for financial forecasting and policy analysis.

Research Focus: Buncic's work spans asset pricing, volatility forecasting, exchange rate dynamics, and macroprudential policy. He employs advanced techniques like Bayesian econometrics, nonlinear time-series models, and high-dimensional data analysis to address questions in financial stability and market predictability. His recent work critiques methodological approaches in natural rate estimation and equity return prediction.

Publication Trends: His articles frequently address econometric methodology, financial market volatility, and monetary policy transmission, with a growing emphasis on machine learning applications in finance. Common themes include forecasting under structural breaks, model robustness, and cross-market interdependencies.

Grants & Advising: He secured a 1.74M SEK grant (2020-2023) from the Jan Wallander & Tom Hedelius Foundation. Currently advising PhD student Qinglin Ouyang, he previously directed Stockholm University's Master’s in Banking and Finance program (2019-2022).