P
Per A. Mykland
Researcher at University of Chicago
Publications - 104
Citations - 9264
Per A. Mykland is an academic researcher from University of Chicago. The author has contributed to research in topics: Estimator & Volatility (finance). The author has an hindex of 41, co-authored 102 publications receiving 8742 citations. Previous affiliations of Per A. Mykland include Humboldt University of Berlin.
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A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data
TL;DR: Under this framework, it becomes clear why and where the “usual” volatility estimator fails when the returns are sampled at the highest frequencies, and a way of finding the optimal sampling frequency for any size of the noise.
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How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise
TL;DR: In this article, the authors show that the optimal sampling frequency is finite and derive its closed-form expression, and demonstrate that modelling the noise and using all the data is a better solution, even if one misspecifies the noise distribution.
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Jumps in Financial Markets: A New Nonparametric Test and Jump Dynamics
Suzanne S. Lee,Per A. Mykland +1 more
TL;DR: In this paper, the authors introduce a nonparametric test to detect jump arrival times and realized jump sizes in asset prices up to the intra-day level, and demonstrate that the likelihood of misclassification of jumps becomes negligible when using high-frequency returns.
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A Tale of Two Time Scales
TL;DR: In this article, the authors propose an estimation approach that takes advantage of the rich sources in tick-by-tick data while preserving the continuous-time assumption on the underlying returns.
Journal ArticleDOI
Microstructure Noise in the Continuous Case: The Pre-Averaging Approach ∗
TL;DR: In this article, a generalized pre-averaging approach for estimating the integrated volatility is presented, which can generate rate optimal estimators with convergence rate n 1/4. But the convergence rate is not guaranteed.