U.K. cross-sectional equity data: do not trust the dataset! The case for robust investability filters

Francesco Rossi ()

MPRA Paper from University Library of Munich, Germany

Abstract: We propose a novel approach to cross-sectional equities sample selection, derived from best market practice in index construction and focused on investability. Using the U.K. market as a template, we first demonstrate how the popular Datastream dataset is plagued by data deficiencies that would surely invalidate statistical inferences, and that are not addressed by commonly used filters. We show the benefits and need for a supplementary data source. We then develop robust investability filters to ensure statistical results from cross-sectional analysis are economically meaningful, an issue overlooked by most studies on cross-sectional risk pricing

Keywords: cross-sectional equities; idiosyncratic risk; U.K. equities; asset pricing; investability; Datastream; Bloomberg; sample selection; turnover; volume; equities; equity (search for similar items in EconPapers)
JEL-codes: G10 G11 G12 G14 G15 (search for similar items in EconPapers)
Date: 2011-07, Revised 2011-11
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:38303

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