Soon Nel and Niël le Roux
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…
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.