Monitoring Volatility Change for Time Series Based on Support Vector Regression

This paper considers monitoring an anomaly from sequentially observed time series with heteroscedastic conditional volatilities based on the cumulative sum (CUSUM) method combined with support vector regression (SVR). The proposed online monitoring process is designed to detect a significant change...

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Detalles Bibliográficos
Autores principales: Lee, Sangyeol, Kim, Chang Kyeom, Kim, Dongwuk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7712961/
https://www.ncbi.nlm.nih.gov/pubmed/33287077
http://dx.doi.org/10.3390/e22111312

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7712961/
https://www.ncbi.nlm.nih.gov/pubmed/33287077
http://dx.doi.org/10.3390/e22111312

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