Change point detection with multivariate observations based on characteristic functions
Abstract
We consider break-detection procedures for vector observations, both under independence as well as under an underlying structural time series scenario. The new methods involve L2-type criteria based on empirical characteristic functions. Asymptotic as well as Monte-Carlo results are presented. The new methods are also applied to time-series data from the financial sector
URI
http://hdl.handle.net/10394/26684https://link.springer.com/chapter/10.1007/978-3-319-50986-0_14
https://doi.org/10.1007/978-3-319-50986-0_14