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Estimation and testing in generalized mean-reverting processes with change-point

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In this paper, we study an inference problem in generalized Ornstein–Uhlenbeck processes with an unknown change-point when the drift parameter is suspected to satisfy a linear restriction. The testing problem… Click to show full abstract

In this paper, we study an inference problem in generalized Ornstein–Uhlenbeck processes with an unknown change-point when the drift parameter is suspected to satisfy a linear restriction. The testing problem studied generalizes a very recent problem about testing the existence of a change-point. To this end, we derive the asymptotic properties of the unrestricted estimator (UE) and the restricted estimator for the drift parameters, and we construct some shrinkage estimators (SEs). Further, we derive a test for testing the uncertain restriction and establish its asymptotic power. Moreover, we derive the asymptotic distributional risk of the proposed estimators and we prove that SEs dominate the UE. Finally, we present some numerical results which confirm the consistency of the proposed test as well as the superiority of the SEs over UE.

Keywords: change point; generalized mean; testing generalized; estimation testing; point; mean reverting

Journal Title: Statistical Inference for Stochastic Processes
Year Published: 2018

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