This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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604
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Type:
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Invited
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Date/Time:
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Thursday, August 5, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Business and Economic Statistics Section
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Abstract - #305972 |
Title:
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Quasi-Maximum Likelihood Estimation of Volatility with High-Frequency Data
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Author(s):
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Dacheng Xiu*+
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Companies:
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Princeton University
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Address:
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, , ,
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Keywords:
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Integrated volatility ;
Market microstructure noise ;
Quasi-Maximum Likelihood Estimator ;
Realized Kernels ;
Stochastic volatility
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Abstract:
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This paper investigates the properties of the well-known maximum likelihood estimator in the presence of stochastic volatility and market microstructure noise, by extending the classic asymptotic results of quasi-maximum likelihood estimation. When trying to estimate the integrated volatility and the variance of noise, this parametric approach remains consistent, efficient and robust as a quasi-estimator under misspecified assumptions. Moreover, it shares the model-free feature with nonparametric alternatives, for instance realized kernels, while being advantageous over them in terms of finite sample performance. Comparisons with a variety of implementations of the Tukey-Hanning 2 kernel are provided using Monte Carlo simulations, and an empirical study with the Euro/US Dollar future illustrates its application in practice.
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Authors who are presenting talks have a * after their name.
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