Analysis of variance for multivariate time series

Hideaki Nagahata () and Masanobu Taniguchi
Additional contact information
Hideaki Nagahata: Waseda University
Masanobu Taniguchi: Waseda University

METRON, 2018, vol. 76, issue 1, No 4, 69-82

Abstract: Abstract This study establishes a new approach for the analysis of variance (ANOVA) of time series. ANOVA has been sufficiently tailored for cases with independent observations, but there has recently been substantial demand across many fields for ANOVA in cases with dependent observations. For example, ANOVA for dependent observations is important to analyze differences among industry averages within financial data. Despite this demand, the study of ANOVA for dependent observations is more nascent than that of ANOVA for independent observations, and, thus, in this analysis, we study ANOVA for dependent observations. Specifically, we show the asymptotics of classical tests proposed for independent observations and give a sufficient condition for the observations to be asymptotically $$\chi ^2$$ χ 2 distributed. If this sufficient condition is not satisfied, we suggest a likelihood ratio test based on the Whittle likelihood and derive an asymptotic $$\chi ^2$$ χ 2 distribution of our test. Finally, we provide some numerical examples using simulated and real financial data as applications of these results.

Keywords: Analysis of variance; DCC-GARCH model; Generalized linear process; Non-Gaussian vector stationary process; Spectral density matrix; Whittle likelihood (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s40300-017-0122-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:metron:v:76:y:2018:i:1:d:10.1007_s40300-017-0122-2

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/40300

DOI: 10.1007/s40300-017-0122-2

Access Statistics for this article

METRON is currently edited by Marco Alfo'

More articles in METRON from Springer, Sapienza Università di Roma
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().