Unknown

Dataset Information

0

Correlation and the time interval over which the variables are measured - A non-parametric approach.


ABSTRACT: 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.

SUBMITTER: Schechtman E 

PROVIDER: S-EPMC6224093 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC6042830 | biostudies-literature
| S-EPMC3097007 | biostudies-other
| S-EPMC5290219 | biostudies-literature
| S-EPMC9244047 | biostudies-literature
| S-EPMC9041796 | biostudies-literature
| S-EPMC5590981 | biostudies-literature
| PRJEB39331 | ENA
| S-EPMC9707922 | biostudies-literature
| S-EPMC3037907 | biostudies-other
| S-EPMC6451633 | biostudies-literature