A General Framework For Constructing Locally Self-Normalized Multiple-Change-Point Tests

04/30/2022
by   Cheuk Hin Cheng, et al.
0

We propose a general framework to construct self-normalized multiple-change-point tests with time series data. The only building block is a user-specified one-change-point detecting statistic, which covers a wide class of popular methods, including cumulative sum process, outlier-robust rank statistics and order statistics. Neither robust and consistent estimation of nuisance parameters, selection of bandwidth parameters, nor pre-specification of the number of change points is required. The finite-sample performance shows that our proposal is size-accurate, robust against misspecification of the alternative hypothesis, and more powerful than existing methods. Case studies of NASDAQ option volume and Shanghai-Hong Kong Stock Connect turnover are provided.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/14/2020

Rank-based change-point analysis for long-range dependent time series

We consider change-point tests based on rank statistics to test for stru...
research
10/28/2021

Location-Adaptive Change-Point Testing for Time Series

We propose a location-adaptive self-normalization (SN) based test for ch...
research
04/03/2019

A new class of change point test statistics of Rényi type

A new class of change point test statistics is proposed that utilizes a ...
research
07/10/2023

Two-Sample and Change-Point Inference for Non-Euclidean Valued Time Series

Data objects taking value in a general metric space have become increasi...
research
12/10/2019

Testing and Estimating Change-Points in the Covariance Matrix of a High-Dimensional Time Series

This paper studies methods for testing and estimating change-points in t...
research
04/09/2019

Cusum tests for changes in the Hurst exponent and volatility of fractional Brownian motion

In this note, we construct cusum change-point tests for the Hurst expone...
research
03/01/2021

Multiscale change point detection via gradual bandwidth adjustment in moving sum processes

A method for the detection of changes in the expectation in univariate s...

Please sign up or login with your details

Forgot password? Click here to reset