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D-Index & Metrics

Economics and Finance

D-Index
39
Citations
16223
World Ranking
2345
National Ranking
12

Overview

Asger Lunde is affiliated with Aarhus University in Denmark and focuses on research primarily within the fields of Economics, Econometrics, and Finance, with additional work in Decision Sciences. Their research encompasses a range of subfields including Economics and Econometrics, Finance, Management Science and Operations Research, General Economics, Econometrics and Finance, as well as Renewable Energy, Sustainability and the Environment.

The scientist's research topics include Market Dynamics and Volatility, Financial Risk and Volatility Modeling, Stock Market Forecasting Methods, Financial Markets and Investment Strategies, Complex Systems and Time Series Analysis, Monetary Policy and Economic Impact, and Forecasting Techniques and Applications.

Recent publications by Asger Lunde demonstrate engagement with journals known for quantitative finance and econometrics, including:

  • "Picking funds with confidence," 2020, Journal of Financial Economics
  • "News and Idiosyncratic Volatility: The Public Information Processing Hypothesis*," 2020, Journal of Financial Econometrics
  • "Decoupling the Short- and Long-Term Behavior of Stochastic Volatility," 2020, Journal of Financial Econometrics
  • "A Multivariate Realized GARCH Model," 2020, arXiv (Cornell University)
  • "Including news data in forecasting macro economic performance of China," 2020, Computational Management Science

Frequent co-authors in their research work include:

  • Mikkel Bennedsen
  • Niels S. Grønborg
  • Mikko S. Pakkanen
  • Ilya Archakov
  • Peter Reinhard Hansen

The main publication venues where Asger Lunde's work has appeared prominently are:

  • Journal of Financial Econometrics
  • Journal of Econometrics
  • arXiv (Cornell University)
  • Journal of Financial Economics
  • Computational Management Science

Best Publications

  • A forecast comparison of volatility models: does anything beat a GARCH(1,1)?

    Peter Reinhard Hansen;Asger Lunde

  • The Model Confidence Set

    Peter R. Hansen;Asger Lunde;James M. Nason

  • 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

  • Realized Variance and Market Microstructure Noise

    Peter R Hansen;Asger Lunde

  • Realized kernels in practice: trades and quotes

    O. E. Barndorff‐Nielsen;P. Reinhard Hansen;A. Lunde;N. Shephard

  • Multivariate realised kernels: Consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading

    Ole E. Barndorff-Nielsen;Peter Reinhard Hansen;Asger Lunde;Neil Shephard

  • Consistent ranking of volatility models

    Peter Reinhard Hansen;Asger Lunde

  • Duration Dependence in Stock Prices: An Analysis of Bull and Bear Markets

    Asger Lunde;Allan Timmermann

  • A Realized Variance for the Whole Day Based on Intermittent High-Frequency Data

    Peter Reinhard Hansen;Asger Lunde

  • Choosing the best volatility models: the model confidence set approach

    Peter Reinhard Hansen;Asger Lunde;James M. Nason

  • Integrated Covariance Estimation using High-frequency Data in the Presence of Noise

    Valeri Voev;Asger Lunde

  • Realized Variance and Market Microstructure Noise

    Peter Reinhard Hansen;Peter Reinhard Hansen;Peter Reinhard Hansen;Asger Lunde

  • A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?

    Peter Reinhard Hansen;Peter Reinhard Hansen;Peter Reinhard Hansen;Asger Lunde

  • Realised Kernels in Practice: Trades and Quotes

    Ole E. Barndorff-Nielsen;Peter Reinhard Hansen;Peter Reinhard Hansen;Peter Reinhard Hansen;Asger Lunde;Neil Shephard

  • Trades and Quotes: A Bivariate Point Process

    Robert F. Engle;Asger Lunde

  • Hybrid scheme for Brownian semistationary processes

    Mikkel Bennedsen;Asger Lunde;Mikko S. Pakkanen;Mikko S. Pakkanen

  • REALIZED BETA GARCH: A MULTIVARIATE GARCH MODEL WITH REALIZED MEASURES OF VOLATILITY

    Peter Reinhard Hansen;Asger Lunde;Valeri Voev;Valeri Voev

  • Decoupling the Short- and Long-Term Behavior of Stochastic Volatility

    Mikkel Bennedsen;Asger Lunde;Mikko S Pakkanen

  • Subsampling realised kernels

    Ole E. Barndorff-Nielsen;Peter Reinhard Hansen;Asger Lunde;Neil Shephard

  • The NIG‐S&ARCH model: a fat‐tailed, stochastic, and autoregressive conditional heteroskedastic volatility model

    Morten Berg Jensen;Asger Lunde

  • Testing the Significance of Calendar Effects

    Peter Hansen;Asger Lunde

  • Designing Realised Kernels to Measure the Ex-Post Variation of Equity Prices in the Presence of Noise

    Ole E. Barndorff-Nielsen;Peter Reinhard Hansen;Peter Reinhard Hansen;Peter Reinhard Hansen;Asger Lunde;Neil Shephard

  • Multivariate Realised Kernels: Consistent Positive Semi-Definite Estimators of the Covariation of Equity Prices with Noise and Non-Synchronous Trading

    Ole E. Barndorff-Nielsen;Peter Reinhard Hansen;Peter Reinhard Hansen;Peter Reinhard Hansen;Asger Lunde;Neil Shephard

Frequent Co-Authors

Peter Reinhard Hansen
Peter Reinhard Hansen University of North Carolina at Chapel Hill
Neil Shephard
Neil Shephard Harvard University
Allan Timmermann
Allan Timmermann University of California, San Diego
Robert F. Engle
Robert F. Engle New York University
Sébastien Laurent
Sébastien Laurent Aix-Marseille University
Peter Christoffersen
Peter Christoffersen University of Toronto
Russ Wermers
Russ Wermers University of Maryland, College Park
Ole Bernt Fasmer
Ole Bernt Fasmer University of Bergen
Hagop S. Akiskal
Hagop S. Akiskal University of California, San Diego
John R. Kelsoe
John R. Kelsoe University of California, San Diego

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