Analysis to indicate the impact Hindsight Bias have on the outcome when forecasting of stock in the South African equity market

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dc.contributor.advisorConradie, Willieen_ZA
dc.contributor.advisorAlfeus, Mesiasen_ZA
dc.contributor.authorHeyneke, Anton Lafrassen_ZA
dc.contributor.otherStellenbosch University. Faculty of Economic and Management Sciences. Dept. of Statistics and Actuarial Science.en_ZA
dc.date.accessioned2023-11-03T09:04:43Z
dc.date.accessioned2024-01-08T13:29:13Z
dc.date.available2023-11-03T09:04:43Z
dc.date.available2024-01-08T13:29:13Z
dc.date.issued2023-12
dc.descriptionThesis (MCom)--Stellenbosch University, 2023.en_ZA
dc.description.abstractENGLISH SUMMARY: A novel Artificial Neural Network (ANN) framework presented in this study has the ability to mimic the effect that cognitive biases, specifically hindsight bias has on the financial market. This study investigates how hindsight bias influences models and their outcomes. During this study the hindsight bias effect will be measured within a South African context. The decisions that people make when faced with uncertainty are characterized by heuristic judgments and cognitive biases. If these characteristics are systematic and confirmed through research and literature related to this topic, it would form a quintessential part to the explanation of the behaviour of financial markets. This research presents a methodology that could be used to model the impact of cognitive biases on the financial markets. In this study, an ANN will be used as a stand-in for the decision-making process of an investor. It is important to note that the selection of the companies, on which the ANN will be trained, validated and tested, demonstrated cognitive bias during the study's preparation. Though there are many cognitive biases that have been identified in the literature on behavioural finance, this study will concentrate solely on the impact of hindsight bias. On financial markets, hindsight bias manifests when outcomes seem more predictable after they have already happened. This study attempts and succeeds – to some degree - to replicate the return characteristics of the ten chosen companies for the assessment period from 2010 to 2021. The study described here may still be subject to various cognitive biases and systemic behavioural errors in addition to the hindsight bias. The further application of this technique will stimulate further research with respect to the influence of investor behaviour on financial markets.en_ZA
dc.description.abstractAFRIKAANSE OPSOMMING: 'n Nuwe Kunsmatige Neurale Netwerk (ANN) raamwerk wat in hierdie studie aangebied word, het die vermoe om die uitwerking van kognitiewe afwykings, spesifiek terugskouende sydigheid, op die finansiele mark na te boots. Hierdie studie ondersoek hoe terugskouende sydigheid, modelle en hulle uitkomste beinvloed. In hierdie studie word die terugskouende sydigheid-uitwerking binne 'n Suid-Afrikaanse konteks gemeet. Die besluite wat mense maak wanneer hulle met onsekerheid gekonfronteer word, word gekenmerk deur heuristiese oordele en kognitiewe afwykings. As hierdie eienskappe aangaande hierdie onderwerp sistematies en bevestig is deur navorsing en literatuur, dan sou dit 'n noodsaaklike deel vorm van die verklaring van die gedrag van finansiele markte. In hierdie studie word 'n metodologie wat gebruik kan word om die impak van kognitiewe afwykings op die finansiele markte te modelleer, aangebeied. 'n ANN as 'n vervanging vir die besluitnemingsproses van 'n belegger word gebruik. Dit is belangrik om daarop te let dat die keuse van die maatskappye, waarop die ANN geleer, gevalideer en getoets sal word, kognitiewe afwyking gedemonstreer het gedurende die voorbereiding van die studie. Alhoewel daar baie kognitiewe afwykings is wat in die literatuur oor gedragsfinansies geidentifiseer is, sal hierdie studie slegs konsentreer op die impak van terugskouende sydigheid. Op finansiele markte manifesteer terugskouende sydigheid wanneer uitkomste na hulle reeds plaasgevind het, meer voorspelbaar lyk. Hierdie studie poog en slaag – tot 'n mate – om die obrengs-eienskappe van die tien gekose maatskappye vir die beoordelingsperiode vanaf 2010 tot 2021 te repliseer. Hierdie studie mag steeds onderhewig wees aan verskeie kognitiewe afwykings en sistemiese gedragsfoute, naas die terugskouende sydigheid. Die verdere toepassing van hierdie tegniek sal verdere navorsing ten opsigte van die invloed van beleggingsgedrag op finansiele markte stimuleer.af_ZA
dc.description.versionMasters
dc.format.extent102 pages : illustrations
dc.identifier.urihttps://scholar.sun.ac.za/handle/10019.1/128854
dc.language.isoen_ZAen_ZA
dc.publisherStellenbosch : Stellenbosch University
dc.rights.holderStellenbosch University
dc.subject.lcshStock price forecasting -- South Africaen_ZA
dc.subject.lcshInvestments -- Decision making -- South Africaen_ZA
dc.subject.lcshInvestments -- Psychological aspects -- South Africaen_ZA
dc.subject.lcshFinancial risk management -- South Africaen_ZA
dc.subject.nameUCTD
dc.titleAnalysis to indicate the impact Hindsight Bias have on the outcome when forecasting of stock in the South African equity marketen_ZA
dc.typeThesisen_ZA
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