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Magister Commercii - MCom / Over the past four decades, size, value and momentum effects have been uncovered on stock markets, and several multifactor asset pricing models have been proposed to explain them. The associated premiums have been found to be time-varying and the explanations behind the effects are still debated. In South Africa, contradictory findings have been reported on the existence of those effects and the explanatory power of multifactor models. More important, the cyclicality of the effects and the risk/mispricing debate have been given little attention. In this regard, this study purports to establish the existence of size, value and momentum effects, investigate the explanatory power of the Fama-French three- and five-factor models (FF3F and FF5F respectively), and Carhart four-factor model (C4F), and examine the cyclicality and risk-based rationale of the style premiums on the Johannesburg Stock Exchange (JSE). Using a research sample comprised of common stocks included in the FTSE/JSE All Share Index (ALSI) for the period 1 January 2002 - 31 December 2018, the study subdivides the examination period into two business cycles, with each cycle including one upward phase and one downward phase

I evaluate the methods of cladistic parsimony and maximum likelihood in phylogenetic systematics by their affinity to Popper‘s degree of corroboration. My work analyzes an important recent exchange between the proponents of the two methods. Until this exchange, only advocates of cladistic parsimony have claimed a basis for their method on epistemological grounds through corroboration. Advocates of maximum likelihood, on the other hand, have based the rational justification for their method largely on statistical grounds. In Part One I outline corroboration in terms of content, severity of test and explanatory power. In Part Two I introduce the two methods. In Part Three I analyze three important debates. The first involves the appropriate probability interpretation for phylogenetics. The second is about severity of test. The third concerns explanatory power. In Part Four I conclude that corroboration can decide none of these debates, and therefore cannot decide the debate between cladistic parsimony and maximum likelihood.

I evaluate the methods of cladistic parsimony and maximum likelihood in phylogenetic systematics by their affinity to Popper‘s degree of corroboration. My work analyzes an important recent exchange between the proponents of the two methods. Until this exchange, only advocates of cladistic parsimony have claimed a basis for their method on epistemological grounds through corroboration. Advocates of maximum likelihood, on the other hand, have based the rational justification for their method largely on statistical grounds. In Part One I outline corroboration in terms of content, severity of test and explanatory power. In Part Two I introduce the two methods. In Part Three I analyze three important debates. The first involves the appropriate probability interpretation for phylogenetics. The second is about severity of test. The third concerns explanatory power. In Part Four I conclude that corroboration can decide none of these debates, and therefore cannot decide the debate between cladistic parsimony and maximum likelihood.

This diploma thesis deals with credibility models and bankruptcy models as tools for evaluating financial health of company. The aim of this work is an evaluation of credibility models and bankruptcy models. The evaluation is focused on suitability, reliability and predictive ability for use the models in Czech environment. The main body of work constitutes a case study containing an application of eight models on Czech engineering company.The case study is supplemented with professional studies evaluating explanatory power of some models. On the basis of studies' results, the comparison of models was done and were identified their strengths and weaknesses.

The main objective of this thesis is to evaluate the explanatory power of the balance sheet based on French accouting regulation. The first part deals with the general theory of accounting and financial reporting regulation, factors influencing national regulation, form and objectives of financial reporting, with focus on the balance sheet. The second part deals with the French legislative sources for accounting and financial reporting. The third part introduces the definition, structure and method of valuation of assets and liabilities based on French regulation. The fourth and fifth parts are devoted to the profit and loss account and the notes to the financial statements in accordance with French law. The last section contains an analysis of financial statements of a real company, and on this basis explanatory power of balance sheet is evaluated.

Disertacija skirta geriausio paaiškinimo išvedimo (GPI) analizei. Pirma, tyrimas eksplikuoja, kas yra GPI, ką žymi sąvoka aiškinamoji galia. Antra, tyrimas įvertina GPI pretenzijų į tiesą apginamumą – ar teisinga yra hipotezė, jeigu ji yra geriausias tam tikro reiškinio paaiškinimas. GPI skleidžiamas kaip materialaus samprotavimo forma, kuri priskiria teisingumą toms hipotezėms, kurios tarp savo varžovių pasižymi aukščiausiu aiškinamųjų veiksnių laipsniu: mažiausiai prieštarauja pripažintam žinojimui, unifikuoja svarbiausius reiškinius, yra giliausias paaiškinimas ir yra paprasčiausias paaiškinimas. Kritikuojamas tikimybinis požiūris į GPI. Išskiriami ir aprašomi keturi literatūroje randami GPI kaip vedančio į tiesą pagrindimo būdai: patikimumo-koherentinis, evoliucinis, tikimybinis bei empirinis-istorinis. Teigiama, kad nors GPI padeda įvertinti paaiškinimų tikimybių pasiskirstymą ir yra plačiai paplitusi praktika, dėl prastos atrankos argumento, galimo aiškinamųjų veiksnių nebendramatiškumo, pesimistinės indukcijos argumento ir argumento „atsarga gėdos nedaro“ žinomi GPI kaip vedančio į tiesą pagrindimo būdai nėra pakankami – GPI išvadų teisingumas yra atsitiktinis. / The dissertation analyses inference to the best explanation (IBE). Firstly, the thesis explicates the concept of IBE, it analyzes what does the concept of explanatory power stands for. Secondly, the thesis evaluates the tenability of the truth aspirations of IBE, it analyzes to what extent a hypothesis can be claimed to be true, given that it is the best explanation for some phenomenon of interest. IBE is explicated as a form of material inference that ascribes truth to the hypothesis that has the highest degree of explanatory virtues among its competitors: is the most consistent with approved background knowledge, unifies the most the relevant phenomena, is the deepest explanation and is the most simple explanation. Probabilistic approaches to IBE are criticized. Four basic ways of justification of the truth-conduciveness of IBE that can be discerned in the literature are described: reliabilist-coherentist, evolutionary, probabilistic and empirical-historical. The thesis concludes that while IBE could facilitate the determination of probability distributions and is a wide psychological practice, due to the bad lot argument, possible incommensurability of explanatory virtues, pessimistic induction and better safe than sorry beliefs all the four ways of justification of IBE in terms of truth-conduciveness cannot be taken for granted which leaves IBE only accidentally valid.

The dissertation analyses inference to the best explanation (IBE). Firstly, the thesis explicates the concept of IBE, it analyzes what does the concept of explanatory power stands for. Secondly, the thesis evaluates the tenability of the truth aspirations of IBE, it analyzes to what extent a hypothesis can be claimed to be true, given that it is the best explanation for some phenomenon of interest. IBE is explicated as a form of material inference that ascribes truth to the hypothesis that has the highest degree of explanatory virtues among its competitors: is the most consistent with approved background knowledge, unifies the most the relevant phenomena, is the deepest explanation and is the most simple explanation. Probabilistic approaches to IBE are criticized. Four basic ways of justification of the truth-conduciveness of IBE that can be discerned in the literature are described: reliabilist-coherentist, evolutionary, probabilistic and empirical-historical. The thesis concludes that while IBE could facilitate the determination of probability distributions and is a wide psychological practice, due to the bad lot argument, possible incommensurability of explanatory virtues, pessimistic induction and better safe than sorry beliefs all the four ways of justification of IBE in terms of truth-conduciveness cannot be taken for granted which leaves IBE only accidentally valid. / Disertacija skirta geriausio paaiškinimo išvedimo (GPI) analizei. Pirma, tyrimas eksplikuoja, kas yra GPI, ką žymi sąvoka aiškinamoji galia. Antra, tyrimas įvertina GPI pretenzijų į tiesą apginamumą – ar teisinga yra hipotezė, jeigu ji yra geriausias tam tikro reiškinio paaiškinimas. GPI skleidžiamas kaip materialaus samprotavimo forma, kuri priskiria teisingumą toms hipotezėms, kurios tarp savo varžovių pasižymi aukščiausiu aiškinamųjų veiksnių laipsniu: mažiausiai prieštarauja pripažintam žinojimui, unifikuoja svarbiausius reiškinius, yra giliausias paaiškinimas ir yra paprasčiausias paaiškinimas. Kritikuojamas tikimybinis požiūris į GPI. Išskiriami ir aprašomi keturi literatūroje randami GPI kaip vedančio į tiesą pagrindimo būdai: patikimumo-koherentinis, evoliucinis, tikimybinis bei empirinis-istorinis. Teigiama, kad nors GPI padeda įvertinti paaiškinimų tikimybių pasiskirstymą ir yra plačiai paplitusi praktika, dėl prastos atrankos argumento, galimo aiškinamųjų veiksnių nebendramatiškumo, pesimistinės indukcijos argumento ir argumento „atsarga gėdos nedaro“ žinomi GPI kaip vedančio į tiesą pagrindimo būdai nėra pakankami – GPI išvadų teisingumas yra atsitiktinis.

The aim of this work is to apply individual bankruptcy and credibility models and to undergo these results to a mutual confrontation as well as to evaluate the explanatory power and suitability of using aggregates. A brief analysis of the shortened version of the balance sheet and the profit and loss account for the financial activities from 2007 - 2011 is conducted in the case study of the thesis to zoom these. Furthermore, an analysis of the predictive model of bankruptcy and credibility is made. These become important especially at this time due to increasing number of company failures. All these analysis are applied to a particular company.

The ability to predict stock returns is an ability many wish to possess, and in an accurate way as possible. For many years there has been an interest in the field of factor models explaining the returns, with the aim to increase the explanatory power. This is however a complex business since the factors and their improvement of explanatory power need to be significant. Now and then, researchers come up with new significant factors that have a positive impact on models. AQR Capital Management is no exception to this, since they in 2013 presented the factor Quality Minus Junk, earning significant risk-adjusted returns. This bachelor thesis work within mathematical statistics and industrial engineering and management, aims to investigate whether or not the commercial multi-factor model used at the public pension fund Fjärde AP-fonden will be improved by adding the factor Quality Minus Junk, in the sense of explanatory power. The method used is mainly based on multiple linear regression and three three-year time periods are studied ranging from 2010 to 2018. The results from this thesis work show that the QMJ factor provides significant increases in explanatory power for one of three time periods, the most recent period 2016$-$2018. However, since the results are inconclusive further studies are needed in order to better understand how to interpret the results and whether or not to include the QMJ factor in the model. / Förmågan att förutsäga aktiers avkastning önskar många besitta, och på ett så precist sätt som möjligt. Under många år har forskning pågått inom området för faktormodeller som förklarar avkastningar, med målet att öka modellernas förklaringsgrad. Detta är dock en komplex verksamhet eftersom faktorerna och deras förbättring av förklaringsgraden måste vara signifikanta för modellen. Då och då kommer forskare fram med nya sådana faktorer som har positiv påverkan på modeller. AQR Capital Management är inget undantag eftersom de 2013 presenterade sin faktor Quality Minus Junk som visar signifikanta riskjusterade avkastningar. Detta kandidatexamensarbete inom matematisk statistik och industriell ekonomi, ämnar att utreda huruvida den kommersiella faktormodellen som används på Fjärde AP-fonden förbättras genom tillägget av faktorn Quality Minus Junk, i förklaringsgradsmening. Metoden som används är till största delen baserad på multipel linjär regression och tre treårsperioder studeras i tidsintervallet 2010 till 2018. Resultaten från detta projekt visar på att faktorn Quality Minus Junk bidrar med signifikanta ökningar av förklaringsgraden för en av tre perioder, den senaste perioden 2016-2018. Eftersom resultaten är inkonklusiva krävs vidare studier för att bättre förstå och konkludera vad dessa resultat faktiskt innebär samt för att inkludera QMJ-faktorn i modellen eller ej.