A new approach for testing the randomness of heteroskedastic time series data

Autor:	Kazuo Kishimoto
Rok vydání:	1995
Předmět:	Sequence Heteroscedasticity Index (economics) Stock exchange Autocorrelation Econometrics Economics Time series General Economics Econometrics and Finance Finance Randomness Stable distribution
Zdroj:	Financial Engineering and the Japanese Markets. 2:197-218
ISSN:	1573-6946 1380-2011
DOI:	10.1007/bf02425196
Popis:	Proposed is a conditional approach for testing the randomness of heteroskedastic time series data as well as for checking the validity of this testing. It is shown that the ordinary serial correlation test works correctly neither for daily sequence of the TOPIX index in Tokyo Stock Exchange nor for heteroskedastic models, while our approach works well for them. It is also shown that our approach is enough powerful for detecting the departure from the randomness.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c6e1f992523ea31184e1d6828afe600a https://doi.org/10.1007/bf02425196 Zobrazit plný text záznamu Full text from SpringerLink