The current thesis presents five studies which consider the structure of normal range human personality as measured by psychometric inventories. The primary aim of the thesis was to develop a hierarchical model of the structure of human personality, which not only encapsulated the content of extant personality inventories, but extended the extant models to better represent the accumulated knowledge in the field of personality research. To do so, the thesis reports on the largest item level exploratory and confirmatory factor analytic investigation of the structure of personality to date. In Study 1, the utility of confirmatory factor analysis (CFA) for the investigation of personality structure was established by conducting dimensionality, structural and invariance analysis of the 16 Personality Factor Questionnaire, Version 5, using the US Standardization sample. The results clearly demonstrated that confirmatory models of personality inventories can display model fit, and that structures can be identified which are invariant across samples. In Study 2, 1,772 items from the Eugene-Springfield community sample were used to locate 78 unidimensional narrow personality facets, which were both substantively consistent and displayed strong psychometric properties. These 78 facets were then used to identify a second order 11 factor global structure to human personality, the 11+ Model. The 11+ Model was robust over different rotational criteria, and displayed excellent theoretical coverage of the personality sphere. However, confirmatory factor analyses of the 11 factor solution failed to demonstrate model fit. As a result, three further studies were conducted to explore the possible reasons for model misfit. In Study 3, the model fit of the new exploratory 11 factor solution was considered against model fit for extant structures and inventories. The results showed that across modelling strategy, the fit of newly identified structure was comparable to the extant inventories. In Study 4, the claim the model misfit is caused by the inherent complexity in personality was considered through an application of exploratory structural equation modelling (ESEM). ESEM has been argued to more adequately represent such complexity. Results suggested that the ESEM framework fails to offer additional information to help resolve the substantive problems in personality research. Finally, in Study 5, the sample size required to reliably estimate single factor confirmatory models, and second order structural models, was investigated using Monte Carlo simulations. The results suggest that samples of over 2000 are required to reliably estimate second order structural parameters in confirmatory factor analytic models. This finding suggests the samples used in much published research to investigate confirmatory structural models of personality inventories may be deficient.

Organizational commitment has been linked to several important outcomes, including employee turnover and work performance. Despite that the antecedents of organizational commitment have been a subject of research for several decades, the relation between personality and organizational commitment is relatively unexplored. The aim of this study was to examine the relations between the personality traits in the five-factor model (Conscientiousness, Agreeableness, Neuroticism, Openness to Experience, and Extraversion) and organizational commitment. Personality was measured by the IPIP30 questionnaire. Three types of organizational commitment (affective commitment, continuance commitment, and normative commitment) were measured by the Organizational Commitment Questionnaire. The respondents (N = 303) consisted of workers from both the public and the private sector in Sweden. Multiple linear regression analyzes showed that Conscientiousness was statistically significantly related to affective commitment. Agreeableness, Neuroticism, and Extraversion were statistically significantly related to continuance commitment. Practical implications of the results as well as future research directions are discussed.

EMU as the only functioning single currency area has been criticised as a non-optimal currency area since the Treaty on European Union was signed. Despite this, it has been seen as, probably, the most complete economic project that has ever been conducted by any group of governments. Through Dynamic Factor model and Panel VAR method, we are focusing on the issues of business cycle synchronisation, effectiveness of ECB monetary policy and the euro fiscal dividend, thus to advances the current studies on EMU through assessing whether it can be a sustainable system. For example, whether economic fluctuations can be effectively managed by implementing a single ECB monetary policy and financial market can be relied upon as a monitoring and enforcing device to discipline fiscal behaviour of Eurozone countries. Overall, we concluded that EMU could be more sustainable if it was just formed by its core members, leaving the periphery outside the single currency area. However, since the EU has recently conducted many rescue measures to save the Eurozone, we are unlikely to see those troubled countries to quit EMU, at least, at the present time. The sustainability of the current EMU can be improved if more intra-trade can be promoted to enhance business cycle convergence; hence, it will be more likely to have a union-wide appropriate monetary policy. This will also reduce the requirement of depending upon using fiscal measures to compensate the loss of monetary sovereignty. Moreover, fiscal activities can also be better monitored/enforced since the financial market has begun to adequately adjust the long-term interest rates on Eurozone government bonds according to the development in those countries fiscal stance.

No / Purpose ¿ To examine the psychometric properties and construct validity of the general decision making style (GDMS) questionnaire in two UK samples. Design/methodology/approach ¿ The GDMS takes the form of a self-report questionnaire which identifies five decision making styles: rational, intuitive, dependent, avoidant, and spontaneous. It was administered to samples of business studies undergraduates in two UK business schools. Analyses included scale reliabilities, test-re-test reliability, and both exploratory and confirmatory factor analyses. Findings ¿ The instrument's internal and temporal consistencies were generally sound. Consistent with earlier studies, analyses undertaken on the two samples independently were generally supportive of a five factor model of decision making style. No relationships with gender or year of study were observed.

No / This study investigates the impact of LIFFE's introduction of individual equity futures contracts on the risk characteristics of the underlying stocks trading on the LSE. We employ the Fama and French three-factor model (TFM) to measure the change in the systematic risk of the underlying stocks which arises subsequent to the introduction of futures contracts. A GJR-GARCH(1,1) specification is used to test whether the futures contract listing affects the permanent and/or the transitory component of the residual variance of returns, and a control sample methodology isolates changes in the risk components that may be caused by factors other than futures contract innovation. The observed increase (decrease) in the impact of current (old) news on the residual variance implies that futures contract listing enhances stock market efficiency. There is no evidence that futures innovation impacts on either the systematic risk or the permanent component of the residual variance of returns.

This study aimed to examine the internal structure, score reliability, scoring, and interpretation of the Short Grit Scale (Grit-S; Duckworth & Quinn, 2009) using a sample of engineering students (N = 610) from one large southeastern university located in the United States. Confirmatory factor analysis was used to compare four competing theoretical models: (a) a unidimensional model, (b) a two-factor model, (c) a second-order model, and (d) a bi-factor model. Given that researchers have used Grit-S as a single factor, a unidimensional model was examined. Two-factor and second-order models were considered based upon the work done by Duckworth, Peterson, Matthew, and Kelly (2007), and Duckworth and Quinn (2009). Finally, Reise, Morizot, and Hays (2007) have suggested a bi-factor model be considered when dealing with multidimensional scales given its ability to aid researches about the dimensionality and scoring of instruments consisting of heterogeneous item content. Findings from this study show that Grit-S was best represented by a bi-factor solution. Results indicate that the general grit factor possesses satisfactory score reliability and information, however, the results are not entirely clear or supportive of subscale scoring for either consistency of effort subscale or interest. The implications of these findings and future research are discussed.

Bakgrund:CAPM räcker i flera tillfällen inte till för att estimera framtida avkastning. Vissa av prisavvikelsernafrån CAPM är väldokumenterade och har bestått över tid, vilket har lett till uppkomsten avkorrigerande faktorer. En modell som använder sig av två sådana korrigerande faktorer är Fama ochFrenchs tre-faktormodell. Den har testats flertalet gånger på den svenska marknaden där den visat gehögre förklaringsgrader än CAPM. År 2012 samt år 2014 presenterades två nya multifaktormodeller,som genom test på börsmarknaden i USA lyckats fånga upp prisavvikelser bättre än trefaktormodellen.Syfte:Denna studie ämnar undersöka om Fama och Frenchs fem-faktormodell samt Hue, Xue, Zhang´s Qfaktormodelltillför förklaringsvärde för Stockholmsbörsens avkastning i jämförelse med Fama-Frenchs trefaktormodell. Studien analyserar även modellernas konjunkturkänslighet samt faktorernasbetydelse.Metod:Forskningsprocessen är av deduktiv karaktär. Befintliga teorier i form av multifaktormodeller förprissättning av aktier testas med hjälp av empiriska observationer från den svenska marknaden.Studien tillämpar ett kvantitativt tillvägagångssätt och ekonometriska verktyg används för attsäkerställa statistisk signifikans.Resultat:Studien visar att Q-faktormodellen inte tillför förklaringsvärde jämfört med FF3M. FF5M ger resultatsom marginellt överträffar FF3M gällande dess förklaringsgrad. Anledningen till att FF5M presterarbättre bör rimligen ligga i faktorn HML. Resultaten visar också att modellerna är instabila i kortatidsperioder men tenderar ge bättre prediktioner i lågkonjunktur relativt till högkonjunktur. / Background:CAPM isn’t in some cases sufficient for explaining expected stock return. Some of CAPM´smispricing errors are well documented and time persistent which has led rise to the usage of correctivefactors. One model that make use of two such corrective factors are the Fama and French three factormodel. It´s been comprehensively tested on the Swedish market where it has shown to achieve higherexplanatory power then the CAPM. In the year of 2012 and 2014 two new Asset Pricing Models wereintroduced, which on the US stock market better captured many of the best known anomalies.Aim:The aim of the study is to test if the Fama and French five factor model as well as the Q-factor model,could contribute to increased explanatory power beyond the three factor model. The study also analyzethe models cyclical sensitivity as well as the individual factor significance.MethodologyThe knowledge building process takes a deductive approach. Existing theories in the form of assetpricing models are tested based on empirical observations in the Swedish market. The research take aquantitative approach and make use of econometric tools in order to ensure statistic accuratesignificance.Result:This research shows no contribution of explanatory power for the Q-factor model, beyond thatachieved from the Fama and French three factor model. The five factor model achieve marginallyhigher explanatory power compared to the tree factor model. The most likely reason why FF5Machieve better results than the Q-factor model is believed to lie in the usage of the factor HML. Theresults also shows that all of the tested models are very instable when used in a short time perspective.Although there are some clear indication on increasing explanatory power in recession compared to inan ongoing bull market.

Current multifactor valuation pricing models use size (measured by market capitalization) of a firm as one factor to determine the value of a security. The problem with current standard models was that none of them could explain the value of a security consistently and accurately based on current factors and in particular the size factor. The purpose of this quantitative study using existing time-series data over a 10-year period from 2006 to 2015 was to examine the impact of size factor on the realized rate of return of financial securities, while controlling for the impact of market rate of return. There are currently many valuation models but there is no 2-factor model or a model that uses a size factor that includes mid-cap sized securities. The research questions examined mid-cap sized securities for the size factor in a 2-factor model to determine the accuracy of predicting financial returns compared to the current standard Fama-French 3-factor model. The main theoretical framework that guided the study was the efficient market hypothesis that postulates that the price of a stock reflects all relevant available information. Data were collected for historical returns of 15 individual firms and portfolios of securities based on size. Multiple regression analysis methodology was used to examine the impact of size factor on the realized rate of return of financial securities, while controlling for the impact of market rate of return in the modified 2-factor model that included mid-caps. The results of the study indicate that size is a statistically significant factor in a 2-factor model that included mid-caps. The positive social impact of this study is that it could provide greater confidence in financial markets by providing a fair and equitable means of investment and flow of capital for a robust economy.

This thesis investigates pricing-performance of two recently developed multifactor asset-pricing models with the implementation of dual-betas dependent upon prevailing market-conditions. The models included in the study are the Fama and French five-factor model and the Q-factor model by Hou, Xue and Zhang. We test the models on cross-sectional Swedish stock-market data between 2003 and 2015 from the Large-, Mid- and Small Cap-lists and their respective precursors. The models are tested in their ability to explain portfolios sorted on firm beta-values, on a twelve-year period as well as a six-year period characterized by changing market directions and high market volatility.  In our study, we support the presence of changing risk-return relationship in up and down market states by estimating separate market betas with the risk-free rate as threshold. However, we do not find the isolated and volatile period to give rise to a larger difference in the up and down market betas. We consistently find the models to have a decreasing explanatory power on the portfolios of firms with lower beta values. We also find the largest difference in the up and down market betas occurring in the low beta portfolios, suggesting that this is causing measurement problems in the models. While making the models conditional, the measurement problem with the static beta seems to be reduced for the portfolios where the difference between up and down betas differ most. In the applied context, we conclude the conditional dual beta adds explanatory power in the models when the market beta differs in up and down market states.  The insights of this thesis support the method of making the market-beta conditional as suggested by Pettengill, Sundaram & Mathur (Pettengill, et al., 1995), in new multifactor models.

This essay will compare the capital asset pricing model (CAPM), Fama and French threefactor model and Carhart´s four-factor model, to see which of these models that can explain portfolio excess returns best on the Swedish stock market. This thesis will tempt to validate the three and four-factor models because of the limited amount of research done on the Swedish stock market. The results indicate that the three-factor model improves explanatory power for portfolio returns in comparison to the CAPM, and the four-factor model gives a small improvement in the explanatory power compared to the three-factor model. The results also indicate that all models have a low explanatory power when the market is volatile.