Thesis (PhD)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: The practice of combining single-factor multiples (SFMs) into composite multiples
models is underpinned by the theory that various SFMs carry incremental information,
which, if encapsulated in a superior value estimate, largely eliminates biases and
errors in individual estimates. Consequently, the chief objective of this study was to
establish whether combining single value estimates into an aggregate estimate will
provide a superior value estimate vis-á-vis single value estimates.
It is envisaged that this dissertation will provide a South African perspective, as an
emerging market, to composite multiples modelling and the multiples-based equity
valuation theory on which it is based. To this end, the study included 16 SFMs, based
on value drivers representing all of the major value driver categories, namely
earnings, assets, dividends, revenue and cash flows.
The validation of the research hypothesis hinged on the results obtained from the
initial cross-sectional empirical investigation into the factors that complicate the
traditional multiples valuation approach. The main findings from the initial analysis,
which subsequently directed the construction of the composite multiples models, were
the following: Firstly, the evidence suggested that, when constructing multiples, multiples whose
peer groups are based on a combination of valuation fundamentals perform more
accurate valuations than multiples whose peer groups are based on industry
classifications. Secondly, the research results confirmed that equity-based multiples
produce more accurate valuations than entity-based multiples. Thirdly, the research
findings suggested that multiples models that are constructed on earnings-based
value drivers, especially HE, offer higher degrees of valuation accuracy compared to
multiples models that are constructed on dividend-, asset-, revenue- or cash flowbased
value drivers.
The results from the initial cross-sectional analysis were also subjected to an industry
analysis, which both confirmed and contradicted the initial cross-sectional-based
evidence. The industry-based research findings suggested that both the choice of optimal Peer Group Variable (PGV) and the choice of optimal value driver are
industry-specific.
As with the initial cross-sectional analysis, earnings-based value drivers dominated
the top positions in all 28 sectors that were investigated, while HE was again
confirmed as the most accurate individual driver.
However, the superior valuation performance of multiples whose peer groups are
based on a combination of valuation fundamentals, as deduced from the crosssectional
analysis conducted earlier, did not hold when subjected to an industry
analysis, suggesting that peer group selection methods are industry-specific.
From this evidence, it was possible to construct optimal industry-specific SFMs
models, which could then be compared to industry-specific composite models. The
evidence suggested that composite-based modelling offered, on annual average,
between 20.21% and 44.59% more accurate valuations than optimal SFMs modelling
over the period 2001 to 2010.
The research results suggest that equity-based composite modelling may offer
substantial gains in precision over SFMs modelling. These gains are, however,
industry-specific and a carte blanche application thereof is ill advised. Therefore,
since investment practitioners’ reports typically include various multiples, it seems
prudent to consider the inclusion of composite models as a more accurate alternative. / AFRIKAANSE OPSOMMING: Die praktyk om Enkelfaktor Veelvoude (EFVe) te kombineer in saamgestelde
veelvoudmodelle word ondersteun deur die teorie dat verskillende EFVe oor
inkrementele inligting beskik, wat, indien dit in ’n superieure waardeskatting
opgeneem word, grootliks vooroordele en foute in individuele skattings elimineer.
Gevolglik was die hoofdoel van hierdie studie om vas te stel of die kombinering van
verskeie enkelfaktor waardeskattings in ’n totale waardeskatting ’n superieure
waardeskatting sal verskaf vis-á-vis enkelfaktor waardeskattings.
Dit word voorsien dat hierdie proefskrif ’n Suid-Afrikaanse perspektief, as ’n
ontluikende mark, sal bied aangaande saamgestelde veelvoudmodellering en die
veelvoud-gebaseerde ekwiteitswaardasie-teorie waarop dit gebaseer is. Hiermee ten
doel, sluit hierdie studie 16 EFVe in, gebaseer op waardedrywers wat al die
vernaamste waardedrywerkategorieë, naamlik verdienste, bates, dividende, omset en
kontantvloeie, verteenwoordig.
Die bevestiging van die navorsingshipotese is afhanklik van die resultate soos bekom
vanuit die aanvanklike dwarsdeursnee-empiriese ondersoek na die faktore wat die
tradisionele veelvoudwaardasieproses kompliseer. Die hoofbevindinge van die
aanvanklike ontleding, wat daarna rigtinggewend was vir die komposisie van die
saamgestelde veelvoudmodelle, was die volgende: Eerstens, dui die bewyse daarop dat, wanneer veelvoude saamgestel word,
veelvoude waarvan die portuurgroepe op ’n kombinasie van fundamentele waardasieveranderlikes
gebaseer is, meer akkurate waardasies lewer as veelvoude waarvan
die portuurgroepe op industrie-klassifikasies gebaseer is. Tweedens, het die
navorsingsresultate bevestig dat ekwiteitsgebaseerde veelvoude meer akkurate
waardasies lewer as entiteitsgebaseerde veelvoude. Derdens, toon die
navorsingsbevindinge dat veelvoudmodelle wat saamgestel word uit verdienstegebaseerde
waardedrywers, veral wesensverdienste (WV), hoër grade van
waardasie-akkuraatheid bied in vergelyking met veelvoudmodelle wat saamgestel
word uit dividend-, bate-, omset- of kontantvloei-gebaseerde waardedrywers. Die resultate van die aanvanklike dwarsdeursnee-ontleding is ook onderwerp aan ’n
industrie-ontleding, wat die aanvanklike bevindinge van die dwarsdeursnee-ontleding
beide bevestig en weerspreek het. Die bevindinge vanaf die industrie-ontleding dui
daarop dat beide die keuse van optimale Portuurgroepveranderlike (PGV) en die
optimale keuse van waardedrywer, industrie-spesifiek is.
Soos met die aanvanklike dwarsdeursnee-ontleding, het verdienste-gebaseerde
waardedrywers die top posisies by al 28 sektore wat ondersoek is, gedomineer, terwyl
WV weer as die akkuraatste individuele waardedrywer bevestig is.
Die superieure waardasie-resultate van veelvoude waarvan die portuurgroepe
gebaseer was op ’n kombinasie van fundamentele waardasie-veranderlikes, soos
afgelei uit die aanvanklike dwarsdeursnee-ontleding, het egter nie dieselfde resultate
gelewer op ’n per sektor basis nie, wat aandui dat portuurgroep seleksiemetodes
industrie-spesifiek is.
Vanuit hierdie bevindinge was dit moontlik om optimale EFV-modelle saam te stel,
wat dan vergelyk kon word met industrie-spesifieke saamgestelde veelvoudmodelle.
Die bevindinge het voorgestel dat saamgestelde modellering gemiddeld jaarliks,
tussen 20.21% en 44.59% meer akkurate waardasies gelewer het as optimale EFVmodellering
oor die tydperk 2001 tot 2010. Die navorsingsresultate dui aan dat ekwiteitsgebaseerde saamgestelde modellering
aansienlike toenames in waardasie-akkuraatheid mag bewerkstellig bo dié van EFVmodellering.
Hierdie toenames is egter industrie-spesifiek en ’n carte blanche
toepassing daarvan is nie aan te beveel nie. Gevolglik, aangesien
beleggingspraktisyns se verslae tipies verskeie veelvoude insluit, blyk dit redelik om
die insluiting van saamgestelde modelle as ’n meer akkurate alternatief te oorweeg.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/95808 |
| Date | 09 October 2014 |
| Creators | Nel, Willem Soon |
| Contributors | Bruwer, Barbara Wilhelmina, Le Roux, Niel J., Stellenbosch University. Faculty of Economic and Management Sciences. School of Accounting. |
| Publisher | Stellenbosch : Stellenbosch University |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | Unknown |
| Type | Thesis |
| Format | 366 p. : ill. |
| Rights | Stellenbosch University |
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