Testing conditional heteroscedasticity with systematic sampling of time series

• Tipo: Artigo em Revista Científica Internacional
• Data: 2023

Autores

Paulo Teles (Autor) FEP

Revista

Título: Communications in Statistics - Theory and Methods

Vol. 52 Nº 12

Páginas: 5427-5450

ISSN: 0361-0926

Editora: Taylor & Francis

Indexação

ISI Web of Knowledge - 1 Citação

Scopus - 1 Citação

Outras Informações

ID Authenticus: P-00V-TK6

DOI: 10.1080/03610926.2021.2008976

Abstract (EN): It is well known that conditional heteroscedasticity is exhibited by many economic and financial time series such as stock prices or returns. Empirical analysis is often based on a subseries obtained through systematically sampling from an underlying time series and we analyze how that can affect testing for heteroscedasticity. The results show the distribution of the test statistics is changed by systematic sampling, causing a serious power loss that increases with the sampling interval. Consequently, the tests often fail to reject the hypothesis of no conditional heteroscedasticity, leading to the wrong decision and missing the true nature of the data-generating process.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 24