The use of aggregate time series for testing conditional heteroscedasticity

• Type: Article in International Scientific Journal
• Date: 2022

Authors

Paulo Teles (Author) FEP; Chan, WS (Author) Other

Journal

Title: Statistics

Vol. 56

Pages: 1242-1269

ISSN: 0233-1888

Publisher: Taylor & Francis

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 1 Citation

Other information

Authenticus ID: P-00X-C0R

DOI: 10.1080/02331888.2022.2134386

Abstract (EN): Many time series exhibit conditional heteroscedasticity such as stock prices or returns, interest rates or exchange rates. Time series used in empirical analysis are often temporal aggregates. We study the effects of using temporally aggregated time series in testing for heteroscedasticity. The distribution of the test statistics is affected by aggregation which causes a severe power loss that worsens with the order of aggregation. Thus, the tests often fail to detect the heteroscedastic nature of the data which is a misleading outcome and can entail wrong decisions. Our conclusions are illustrated by an empirical application.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 28