Examinando por Autor "Le Roux, Niël"

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The valuation performance of mathematically-optimised equity-based composite multiples
(Universidad ESAN. ESAN Ediciones, 2017-12-01) Nel, Soon; Le Roux, Niël
Purpose – This paper aims to examine the valuation precision of composite models in each of six key industries in South Africa. The objective is to ascertain whether equity-based composite multiples models produce more accurate equity valuations than optimal equity-based single-factor multiples models. Design/methodology/approach – This study applied principal component regression and various mathematical optimisation methods to test the valuation precision of equity-based composite multiplesmodels vis-à-vis equity-based single-factor multiples models. Findings – The findings confirmed that equity-based composite multiples models consistently produced valuations that were substantially more accurate than those of single-factor multiples models for the periodbetween 2001 and 2010. The research results indicated that composite models produced up to 67 per cent more accurate valuations than single-factor multiples models for the period between 2001 and 2010 which represents a substantial gain in valuation precision. Research implications – The evidence therefore suggests that equity-based composite modelling may offer substantial gains in valuation precision over single-factor multiples modelling. Practical implications – In light of the fact that analysts’ reports typically contain various different multiples it seems prudent to consider the inclusion of composite models as a more accurate alternative. Originality/value – This study adds to the existing body of knowledge on the multiples-based approach to equity valuations by presenting composite modelling as a more accurate alternative to the conventionalsingle-factor multiples-based modelling approach.