2023 - Research.com Mathematics in Denmark Leader Award
2022 - Research.com Mathematics in Denmark Leader Award
2001 - Fellow of the Royal Society of Edinburgh
1990 - Member of Academia Europaea
Ole E. Barndorff-Nielsen spends much of his time researching Econometrics, Realized variance, Quadratic variation, Volatility and Applied mathematics. His study on Stochastic volatility is often connected to Bartlett's test as part of broader study in Econometrics. His studies deal with areas such as Exchange rate, Mathematical economics, Jump process and Series as well as Stochastic volatility.
His Realized variance study integrates concerns from other disciplines, such as Analysis of covariance, Kernel, Estimator, Asymptotic distribution and Multivariate statistics. His Quadratic variation study which covers Semimartingale that intersects with Brownian motion. He interconnects Panel data, Cointegration and Time series in the investigation of issues within Volatility.
His main research concerns Econometrics, Stochastic volatility, Volatility, Statistical physics and Applied mathematics. His study in the fields of Realized variance under the domain of Econometrics overlaps with other disciplines such as Financial econometrics. His Stochastic volatility study combines topics in areas such as Implied volatility, Volatility smile and Valuation of options.
Many of his research projects under Volatility are closely connected to Context with Context, tying the diverse disciplines of science together. His biological study spans a wide range of topics, including Stochastic process, Gaussian process, Brownian motion and Turbulence, Intermittency. His Applied mathematics research includes themes of Calculus and Malliavin calculus.
Ole E. Barndorff-Nielsen focuses on Volatility, Econometrics, Stochastic volatility, Statistical physics and Brownian motion. The various areas that he examines in his Volatility study include Probabilistic logic, Stochastic integration, Quadratic variation, Applied mathematics and Malliavin derivative. Ole E. Barndorff-Nielsen studies Realized variance which is a part of Econometrics.
His work deals with themes such as Martingale, Volatility smile and Multivariate statistics, which intersect with Stochastic volatility. His research in Statistical physics focuses on subjects like Turbulence, which are connected to Dissipation. His Brownian motion study also includes
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Econometric analysis of realized volatility and its use in estimating stochastic volatility models
Ole E. Barndorff-Nielsen;Neil Shephard.
Journal of The Royal Statistical Society Series B-statistical Methodology (2002)
Power and Bipower Variation with Stochastic Volatility and Jumps
Ole E. Barndorff-Nielsen;Neil Shephard.
Journal of Financial Econometrics (2004)
Non-Gaussian Ornstein–Uhlenbeck-based models and some of their uses in financial economics
Ole E. Barndorff-Nielsen;Neil Shephard.
Journal of The Royal Statistical Society Series B-statistical Methodology (2001)
Processes of normal inverse Gaussian type
Ole E. Barndorff-Nielsen.
Finance and Stochastics (1997)
Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise ∗
Ole E. Barndorff-Nielsen;Peter Reinhard Hansen;Asger Lunde;Neil Shephard.
Econometrica (2008)
Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation
Ole Eiler Barndorff-Nielsen;Neil Shephard.
Journal of Financial Econometrics (2005)
Information and Exponential Families in Statistical Theory
J. F. C. Kingman;O. Barndorff-Nielsen.
Journal of the Royal Statistical Society: Series A (General) (1979)
Normal Inverse Gaussian Distributions and Stochastic Volatility Modelling
Ole E. Barndorff-Nielsen.
Scandinavian Journal of Statistics (1997)
Econometric Analysis of Realized Covariation: High Frequency Based Covariance, Regression, and Correlation in Financial Economics
Ole Eiler Barndorff-Nielsen;N. Shephard.
Econometrica (2004)
Information and Exponential Families in Statistical Theory
O. E. Barndorff-Nielsen.
(2014)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:
Harvard University
University of Oslo
Steklov Mathematical Institute
University of Copenhagen
Aarhus University
University of Oxford
Sorbonne University
University of North Carolina at Chapel Hill
Technical University of Munich
Leiden University
King's College London
Chinese University of Hong Kong
Wilmington University
Pusan National University
INRAE : Institut national de recherche pour l'agriculture, l'alimentation et l'environnement
Leipzig University
Monash University
Bedford Institute of Oceanography
University of Cambridge
Georgia Institute of Technology
Exponent (United States)
University of Utah
Johannes Gutenberg University of Mainz
The University of Texas Health Science Center at Houston
Autonomous University of Madrid
Hong Kong University of Science and Technology