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.
Highlights
This paper examines the valuation precision of composite models in each of six key industries in South Africa
The aim of this paper was to determine whether industry-specific, equity-based, composite multiples models offer higher degrees of valuation precision compared to industry-specific, equity-based, singlefactor multiples models
The study focused on equity-based multiples, in particular, and the results were tested for the period between 2001 and 2010
Summary
In a similar study conducted in the USA and Europe, Schreiner (2007) tested the valuation precision of a two-factor composite model consisting of P/BVE and other earning-based multiples. The only documented study on composite modelling in emerging markets was conducted by Sehgal and Pandey (2010), who tested the valuation performance of two-factor composite models in Brazil, India, China, South Korea and South Africa, for the period 1993–2007. They concluded, among other findings, that two-factor composite models produce neither significantly nor consistently, more accurate valuations than single-factor, multiples models, which contradicts evidence from the developed market literature. This paper aims to broaden the scope of the South African case study, in particular, by including eight equity-based single-factor multiples, based on value drivers representing all of the major equity-based value driver categories, namely earnings, assets, dividends and cash flows
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