Nel, Willem Soon (2014-10-09)
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.
Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/95808
Doctoral Degrees (School of Accountancy)4