Cargando…
Correlation and the time interval over which the variables are measured – A non-parametric approach
It is known that when one (or both) variable is multiplicative, the choice of differencing intervals (n) (for example, differencing interval of n = 7 means a weekly datum which is the product of seven daily data) affects the Pearson correlation coefficient (ρ) between variables (often asset returns)...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6224093/ https://www.ncbi.nlm.nih.gov/pubmed/30408091 http://dx.doi.org/10.1371/journal.pone.0206929 |
_version_ | 1783369540081549312 |
---|---|
author | Schechtman, Edna Shelef, Amit |
author_facet | Schechtman, Edna Shelef, Amit |
author_sort | Schechtman, Edna |
collection | PubMed |
description | It is known that when one (or both) variable is multiplicative, the choice of differencing intervals (n) (for example, differencing interval of n = 7 means a weekly datum which is the product of seven daily data) affects the Pearson correlation coefficient (ρ) between variables (often asset returns) and that ρ converges to zero as n increases. This fact can cause the resulting correlation to be arbitrary, hence unreliable. We suggest using Spearman correlation (r) and prove that as n increases Spearman correlation tends to a limit which only depends on Pearson correlation based on the original data (i.e., the value for a single period). In addition, we show, via simulation, that the relative variability (CV) of the estimator of ρ increases with n and that r does not share this disadvantage. Therefore, we suggest using Spearman when one (or both) variable is multiplicative. |
format | Online Article Text |
id | pubmed-6224093 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-62240932018-11-19 Correlation and the time interval over which the variables are measured – A non-parametric approach Schechtman, Edna Shelef, Amit PLoS One Research Article It is known that when one (or both) variable is multiplicative, the choice of differencing intervals (n) (for example, differencing interval of n = 7 means a weekly datum which is the product of seven daily data) affects the Pearson correlation coefficient (ρ) between variables (often asset returns) and that ρ converges to zero as n increases. This fact can cause the resulting correlation to be arbitrary, hence unreliable. We suggest using Spearman correlation (r) and prove that as n increases Spearman correlation tends to a limit which only depends on Pearson correlation based on the original data (i.e., the value for a single period). In addition, we show, via simulation, that the relative variability (CV) of the estimator of ρ increases with n and that r does not share this disadvantage. Therefore, we suggest using Spearman when one (or both) variable is multiplicative. Public Library of Science 2018-11-08 /pmc/articles/PMC6224093/ /pubmed/30408091 http://dx.doi.org/10.1371/journal.pone.0206929 Text en © 2018 Schechtman, Shelef http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Schechtman, Edna Shelef, Amit Correlation and the time interval over which the variables are measured – A non-parametric approach |
title | Correlation and the time interval over which the variables are measured – A non-parametric approach |
title_full | Correlation and the time interval over which the variables are measured – A non-parametric approach |
title_fullStr | Correlation and the time interval over which the variables are measured – A non-parametric approach |
title_full_unstemmed | Correlation and the time interval over which the variables are measured – A non-parametric approach |
title_short | Correlation and the time interval over which the variables are measured – A non-parametric approach |
title_sort | correlation and the time interval over which the variables are measured – a non-parametric approach |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6224093/ https://www.ncbi.nlm.nih.gov/pubmed/30408091 http://dx.doi.org/10.1371/journal.pone.0206929 |
work_keys_str_mv | AT schechtmanedna correlationandthetimeintervaloverwhichthevariablesaremeasuredanonparametricapproach AT shelefamit correlationandthetimeintervaloverwhichthevariablesaremeasuredanonparametricapproach |