Author, as appears in the article.: Bariviera, Aurelio F. Plastino, Angelo Judge, George
Department: Gestió d'Empreses
URV's Author/s: Fernández Bariviera, Aurelio
Keywords: Symbolic analysis Stock market Ordinal patterns probabilities Ordinal patterns Daily seasonality
Abstract: This paper offers a general and comprehensive definition of the day-of-the-week effect. Using symbolic dynamics, we develop a unique test based on ordinal patterns in order to detect it. This test uncovers the fact that the so-called 'day-of-the-week' effect is partly an artifact of the hidden correlation structure of the data. We present simulations based on artificial time series as well. While time series generated with long memory are prone to exhibit daily seasonality, pure white noise signals exhibit no pattern preference. Since ours is a non-parametric test, it requires no assumptions about the distribution of returns, so that it could be a practical alternative to conventional econometric tests. We also made an exhaustive application of the here-proposed technique to 83 stock indexes around the world. Finally, the paper highlights the relevance of symbolic analysis in economic time series studies.
Thematic Areas: Economics and econometrics Economics Ciencias sociales
licence for use: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 22251146
Author's mail: aurelio.fernandez@urv.cat
Author identifier: 0000-0003-1014-1010
Record's date: 2023-04-29
Papper version: info:eu-repo/semantics/publishedVersion
Papper original source: Econometrics. 6 (1):
APA: Bariviera, Aurelio F. Plastino, Angelo Judge, George (2018). Spurious Seasonality Detection: A Non-Parametric Test Proposal. Econometrics, 6(1), -. DOI: 10.3390/econometrics6010003
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Entity: Universitat Rovira i Virgili
Journal publication year: 2018
Publication Type: Journal Publications
Repositori URV