Adaptive algorithms for change point detection in financial time series

The detection of change points in chaotic and non-stationary time series presents a critical challenge for numerous practical applications, particularly in fields such as finance, climatology, and engineering. Traditional statistical methods, grounded in stationary models, are often ill-suited to ca...

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Bibliographic Details
Main Authors: Alexander Musaev, Dmitry Grigoriev, Maxim Kolosov
Format: Article
Language:English
Published: AIMS Press 2024-12-01
Series:AIMS Mathematics
Subjects:
Online Access:https://www.aimspress.com/article/doi/10.3934/math.20241674
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