Monitoring Volatility Change for Time Series Based on Support Vector Regression

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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Bibliographic Details
Main Authors:	Sangyeol Lee, Chang Kyeom Kim, Dongwuk Kim
Format:	Article
Language:	English
Published:	MDPI AG 2020-11-01
Series:	Entropy
Subjects:	GARCH-type time series CUSUM monitoring support vector regression particle swarm optimization
Online Access:	https://www.mdpi.com/1099-4300/22/11/1312

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