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ON THE SINGULARITY OF LEAST SQUARES ESTIMATOR FOR MEAN-REVERTING α-STABLE MOTIONS 被引量:2

ON THE SINGULARITY OF LEAST SQUARES ESTIMATOR FOR MEAN-REVERTING α-STABLE MOTIONS
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摘要 We study the problem of parameter estimation for mean-reverting α-stable motion, dXt = (a0 - θ0Xt)dt + dZt, observed at discrete time instants. A least squares estimator is obtained and its asymptotics is discussed in the singular case (a0, θ0) = (0, 0). If a0 = 0, then the mean-reverting α-stable motion becomes Ornstein-Uhlenbeck process and is studied in [7] in the ergodic case θ0 〉 0. For the Ornstein-Uhlenbeck process, asymptotics of the least squares estimators for the singular case (θ0 = 0) and for ergodic case (θ0 〉 0) are completely different. We study the problem of parameter estimation for mean-reverting α-stable motion, dXt = (a0 - θ0Xt)dt + dZt, observed at discrete time instants. A least squares estimator is obtained and its asymptotics is discussed in the singular case (a0, θ0) = (0, 0). If a0 = 0, then the mean-reverting α-stable motion becomes Ornstein-Uhlenbeck process and is studied in [7] in the ergodic case θ0 〉 0. For the Ornstein-Uhlenbeck process, asymptotics of the least squares estimators for the singular case (θ0 = 0) and for ergodic case (θ0 〉 0) are completely different.
出处 《Acta Mathematica Scientia》 SCIE CSCD 2009年第3期599-608,共10页 数学物理学报(B辑英文版)
基金 Hu is supported by the National Science Foundation under Grant No.DMS0504783 Long is supported by FAU Start-up funding at the C. E. Schmidt College of Science
关键词 asymptotic distribution of LSE consistency of LSE discrete observation least squares method Ornstein-Uhlenbeck processes mean-revertingprocesses singularity a-stable processes stable stochastic integrals asymptotic distribution of LSE consistency of LSE discrete observation least squares method Ornstein-Uhlenbeck processes mean-revertingprocesses, singularity a-stable processes stable stochastic integrals
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