World's Best Scientists 2026 revealed!

D-Index & Metrics

Economics and Finance

D-Index
36
Citations
11137
World Ranking
2725
National Ranking
1514

Mathematics

D-Index
37
Citations
11231
World Ranking
2418
National Ranking
1015

Research.com Recognitions

  • 2019 - Fellow of John Simon Guggenheim Memorial Foundation
  • 1999 - Fellow of the American Statistical Association (ASA)

Overview

Per A. Mykland is affiliated with the University of Chicago in the United States and has contributed extensively to the field of Economics, Econometrics, and Finance. Their research spans several subfields, including Finance, General Economics, Econometrics and Finance, Statistics and Probability, Economics and Econometrics, and Radiation.

The scientist's academic work focuses on a variety of topics related to financial and statistical analysis. Key topics covered in their publications include:

  • Financial Risk and Volatility Modeling
  • Monetary Policy and Economic Impact
  • Statistical Methods and Inference
  • Stochastic Processes and Financial Applications
  • Complex Systems and Time Series Analysis
  • Advanced Statistical Methods and Models
  • Market Dynamics and Volatility

Mykland has produced papers published in a range of reputable academic journals. Recent publications include:

  • Realized regression with asynchronous and noisy high frequency and high dimensional data, 2023, Journal of Econometrics
  • IN-SAMPLE ASYMPTOTICS AND ACROSS-SAMPLE EFFICIENCY GAINS FOR HIGH FREQUENCY DATA STATISTICS, 2021, Econometric Theory
  • High dimensional regression coefficient test with high frequency data, 2024, Journal of Econometrics
  • A CLT for second difference estimators with an application to volatility and intensity, 2022, The Annals of Statistics
  • The Observed Asymptotic Variance: Hard edges, and a regression approach, 2020, Journal of Econometrics

Frequent publication venues for their work include:

  • Journal of Econometrics
  • Econometric Theory
  • The Annals of Statistics
  • SSRN Electronic Journal
  • arXiv (Cornell University)

Mykland has collaborated often with several co-authors, contributing to multiple publications alongside:

  • Dachuan Chen
  • Lan Zhang
  • Long Feng
  • Emil Aas Stoltenberg
  • Éric Ghysels

Their career has been recognized with fellowships, including the Fellow of the John Simon Guggenheim Memorial Foundation awarded in 2019 and Fellow of the American Statistical Association awarded in 1999.

Best Publications

  • A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data

    Lan Zhang;Per A. Mykland;Yacine Ait-Sahalia

  • Jumps in Financial Markets: A New Nonparametric Test and Jump Dynamics

    Suzanne S. Lee;Per A. Mykland

  • A Tale of Two Time Scales

    Lan Zhang;Per A Mykland;Yacine Aït-Sahalia

  • How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise

    Yacine Aït-Sahalia;Per A. Mykland;Lan Zhang

  • Microstructure Noise in the Continuous Case: The Pre-Averaging Approach ∗

    Jean Jacod;Yingying Li;Per A. Mykland;Mark Podolskij

  • Ultra high frequency volatility estimation with dependent microstructure noise

    Yacine Aït-Sahalia;Per A. Mykland;Lan Zhang

  • A Tale of Two Time Scales: Determining Integrated Volatility with Noisy High Frequency Data

    Lan Zhang;Yacine Ait-Sahalia;Yacine Ait-Sahalia;Per A. Mykland

  • Regeneration in Markov chain samplers

    Per Mykland;Luke Tierney;Bin Yu

  • ANOVA for diffusions and Itô processes

    Per Aslak Mykland;Lan Zhang

  • Inference for Continuous Semimartingales Observed at High Frequency

    Per A. Mykland;Lan Zhang

  • Looking at Markov samplers through cusum path plots: a simple diagnostic idea

    Bin Yu;Per Mykland

  • THE EFFECTS OF RANDOM AND DISCRETE SAMPLING WHEN ESTIMATING CONTINUOUS-TIME DIFFUSIONS

    Yacine Ait-Sahalia;Per A. Mykland

  • How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise

    Yacine Ait-Sahalia;Per A. Mykland

  • How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise

    Yacine Ait-Sahalia;Yacine Ait-Sahalia;Per A. Mykland

  • Nonlinear Experiments: Optimal Design and Inference Based on Likelihood

    Probal Chaudhuri;Per A. Mykland

  • Jumps in equilibrium prices and market microstructure noise

    Suzanne S. Lee;Per A. Mykland

  • The Estimation of Leverage Effect With High-Frequency Data

    Christina D. Wang;Per A. Mykland

  • EVALUATING HEDGING ERRORS: AN ASYMPTOTIC APPROACH

    Takaki Hayashi;Per A. Mykland

  • The Econometrics of High Frequency Data

    Per. A. Mykland;Lan Zhang

  • ANOVA for diffusions and It\^{o} processes

    Per Aslak Mykland;Lan Zhang

  • ANOVA for diffusions and It\^{o} processes

    Per Aslak Mykland;Lan Zhang

  • Algorithms for computing self-consistent and maximum likelihood estimators with doubly censored data

    Per A. Mykland;Jian-Jian Ren

  • Realized volatility when sampling times are possibly endogenous

    Yingying Li;Per A. Mykland;Eric Renault;Lan Zhang

  • Inference for Continuous Semimartingales Observed at High Frequency: A General Approach

    Per A. Mykland;Lan Zhang

Frequent Co-Authors

Yacine Aït-Sahalia
Yacine Aït-Sahalia Princeton University
Jean Jacod
Jean Jacod Sorbonne University
Mark Podolskij
Mark Podolskij University of Luxembourg
Eric Renault
Eric Renault University of Warwick
Bin Yu
Bin Yu University of California, Berkeley
Eric Ghysels
Eric Ghysels University of North Carolina at Chapel Hill
Neil Shephard
Neil Shephard Harvard University
Francis X. Diebold
Francis X. Diebold University of Pennsylvania
Bing-Yi Jing
Bing-Yi Jing Hong Kong University of Science and Technology

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