The valuation performance of mathematically-optimised, equity-based composite multiples

Soon Nel, Niël le Roux

Abstract


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 multiples
models 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 period
between 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 conventional
single-factor, multiples-based modelling approach.


Keywords


Emerging markets; composite multiples; equity multiples; equity valuations; valuation precision

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