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Quantifying empirical QQ plots: stock markets, executive pay, and weather

Doyle, John R. 2010. Quantifying empirical QQ plots: stock markets, executive pay, and weather. [Working Paper]. Social Science Research Network. Available at: http://dx.doi.org/10.2139/ssrn.1596602

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Abstract

This article introduces two new ideas in the use of QQ plots as visual aids to explore the comparative shapes of distributions. First, we investigate the situation where both x and y distributions are empirical. We derived a procedure for the QQ plot that is based on geometric mean regression, and is simple enough to be calculated in a spreadsheet. We also indicate how this procedure may be robustified, and how it maps onto the one-empirical/one-theoretical QQ plot normally encountered. The second innovation is to use bootstrap sampling to guard against over-interpreting what is seen in the QQ plot. This may also be implemented on a spreadsheet. We illustrate the method with three worked examples that compare the distributions of: (i) UK versus Chinese executive pay, (ii) daily returns for the Shanghai versus the Shenzhen stock markets, and (iii) annual temperatures in the USA, 1895-1951 versus 1952-2007.

Item Type: Monograph (Working Paper)
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HB Economic Theory
H Social Sciences > HD Industries. Land use. Labor
H Social Sciences > HG Finance
Q Science > QA Mathematics
Publisher: Social Science Research Network
ISSN: 15565068
Last Modified: 04 Jun 2017 03:49
URI: http://orca.cf.ac.uk/id/eprint/27495

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