Overview
Professor Bollerslev conducts research in the areas of time-series econometrics, financial econometrics, and empirical asset pricing finance. He is particularly well known for his developments of econometric models and procedures for analyzing and forecasting financial market volatility. Much of Bollerslev’s recent research has focused on the analysis of newly available high-frequency intraday, or tick-by-tick, financial data and so-called realized volatility measures, macroeconomic news announcement effects, and the pricing of volatility risk. Recent reviews of his work are available in the two Handbook chapters "Volatility and Correlation Forecasting” (with Torben G. Andersen, Peter Christoffersen and Francis X. Diebold), Handbook of Economic Forecasting, (eds. Graham Elliott, Clive W.J. Granger and Allan Timmermann), 2006, and "Parametric and Nonparametric Volatility Measurement” (with Torben G. Andersen and Francis X. Diebold), in Handbook of Financial Econometrics, (eds. Yacine Aït-Sahalia and Lars P. Hansen), 2009.
Current Duke Appointments & Affiliations
Juanita and Clifton Kreps Distinguished Professor of Economics, in Trinity College of Arts and Sciences
·
1998 - Present
Economics,
Trinity College of Arts & Sciences
Professor of Economics
·
1998 - Present
Economics,
Trinity College of Arts & Sciences
Recent Scholarly Works
Forecasting and Managing Correlation Risks
Journal article Management Science · April 24, 2026 We propose a novel and easy-to-implement framework for forecasting time-varying correlations based on a large set of salient realized correlation features and the sparsity-encouraging Least Absolute Shrinkage and Selection Operator technique. Consi ... Full text Open Access CiteOptimal Candlestick-Based Spot Volatility Estimation: New Tricks and Feasible Inference Procedures
Journal article Journal of Financial Econometrics · January 1, 2026 We contribute to the growing literature on high-frequency spot volatility estimation by deriving a new integral representation for the recently introduced asymptotic minimum risk equivariant (AMRE) candlestick-based class of estimators. Our new theoretical ... Full text CiteIntraday Market Return Predictability Culled from the Factor Zoo
Journal article Management Science · September 1, 2025 We provide strong empirical evidence for time-series predictability of the intraday return on the aggregate market portfolio by exploiting lagged high-frequency crosssectional returns on the factor zoo. Our results rely on the use of modern machine-learnin ... Full text CiteEducation
University of California, San Diego ·
1986
Ph.D.
University of Aarhus (Denmark) ·
1983
M.S.