TY - JOUR
T1 - Local Parametric Estimation in High Frequency Data
AU - Potiron, Yoann
AU - Mykland, Per
N1 - Funding Information:
Financial support from the National Science Foundation under grant DMS 14-07812 and Japanese Society for the Promotion of Science Grant-in-Aid for Young Scientists (B) No. 60781119 are greatly acknowledged. We are indebted to the editor, Todd Clark, two anonymous referees, and an anonymous associate editor, Simon Clinet, Takaki Hayashi, Dacheng Xiu, participants of the seminars in Berlin and Tokyo and conferences in Osaka, Toyama, the SoFie annual meeting in Hong Kong, the PIMS meeting in Edmonton for valuable comments, which helped in improving the quality of the paper.
Publisher Copyright:
© 2019, © 2019 American Statistical Association.
PY - 2020/7/2
Y1 - 2020/7/2
N2 - We give a general time-varying parameter model, where the multidimensional parameter possibly includes jumps. The quantity of interest is defined as the integrated value over time of the parameter process (Formula presented.). We provide a local parametric estimator (LPE) of Θ and conditions under which we can show the central limit theorem. Roughly speaking those conditions correspond to some uniform limit theory in the parametric version of the problem. The framework is restricted to the specific convergence rate n1∕2. Several examples of LPE are studied: estimation of volatility, powers of volatility, volatility when incorporating trading information and time-varying MA(1).
AB - We give a general time-varying parameter model, where the multidimensional parameter possibly includes jumps. The quantity of interest is defined as the integrated value over time of the parameter process (Formula presented.). We provide a local parametric estimator (LPE) of Θ and conditions under which we can show the central limit theorem. Roughly speaking those conditions correspond to some uniform limit theory in the parametric version of the problem. The framework is restricted to the specific convergence rate n1∕2. Several examples of LPE are studied: estimation of volatility, powers of volatility, volatility when incorporating trading information and time-varying MA(1).
KW - Integrated volatility
KW - Market microstructure noise
KW - Powers of volatility
KW - Quasi-maximum likelihood estimator
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U2 - 10.1080/07350015.2019.1566731
DO - 10.1080/07350015.2019.1566731
M3 - Article
AN - SCOPUS:85065394119
SN - 0735-0015
VL - 38
SP - 679
EP - 692
JO - Journal of Business and Economic Statistics
JF - Journal of Business and Economic Statistics
IS - 3
ER -