Change detection in the Cox–Ingersoll–Ross model

Pap, Gyula and T. Szabó, Tamás (2016) Change detection in the Cox–Ingersoll–Ross model. STATISTICS AND RISK MODELING, 33 (1-2). pp. 21-40. ISSN 2193-1402

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Abstract

We propose an offline change detection method for the famous Cox–Ingersoll–Ross model based on a continuous sample. We develop one- and two-sided testing procedures for both drift parameters of the process. The test process is based on estimators that are motivated by the discrete time least-squares estimators, and its asymptotic distribution under the no-change hypothesis is that of a Brownian bridge. We prove the asymptotic weak consistence of the test, and derive the asymptotic properties of the change-point estimator under the alternative hypothesis of change at one point in time.

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