Change detection in the Cox–Ingersoll–Ross model

IF 1.3 Q2 STATISTICS & PROBABILITY

Statistics & Risk Modeling Pub Date : 2015-02-25 DOI:10.1515/strm-2015-0008

G. Pap, Tamás T. Szabó

引用次数: 2

Abstract

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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Cox-Ingersoll-Ross模型中的变化检测

摘要针对著名的Cox-Ingersoll-Ross模型，提出了一种基于连续样本的离线变化检测方法。我们开发了该工艺的两个漂移参数的单侧和双侧测试程序。该检验过程基于离散时间最小二乘估计量，其在不变假设下的渐近分布为布朗桥的渐近分布。我们证明了该检验的渐近弱相合性，并在一个时点变化的备择假设下，导出了变点估计量的渐近性质。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Statistics & Risk Modeling STATISTICS & PROBABILITY-

CiteScore

1.80

自引率

6.70%

发文量

期刊介绍： Statistics & Risk Modeling (STRM) aims at covering modern methods of statistics and probabilistic modeling, and their applications to risk management in finance, insurance and related areas. The journal also welcomes articles related to nonparametric statistical methods and stochastic processes. Papers on innovative applications of statistical modeling and inference in risk management are also encouraged. Topics Statistical analysis for models in finance and insurance Credit-, market- and operational risk models Models for systemic risk Risk management Nonparametric statistical inference Statistical analysis of stochastic processes Stochastics in finance and insurance Decision making under uncertainty.