Covid-19 pandemin har orsakat ett stort antal sjukdom- och dödsfall i Sverige. Människors beteende är avgörande för smittspridningens utveckling och blir därför värdefullt att undersöka. Aktuell studie testade huruvida Femfaktormodellens personlighetsdimensioner respektive självbetjänande attributionsfelen, bättre-än-medel-effekten och orealistisk optimism, samvarierar med och predicerar smittförebyggande beteenden vid covid-19 pandemin. En enkät besvarades av 126 högskolestudenter från Mellansverige. Resultatet visade inget signifikant samband mellan någon personlighetsdimension och smittförebyggande beteenden. Personlighet kan inte predicera risk- respektive smittförebyggande beteenden. Samtliga mätningar av bättre-än-medel-effekter och orealistisk optimism visade positiva samband med smittförebyggande beteenden varav enbart bättre-än-medel-effekten vad gäller den egna förmågan att skydda sig mot smitta kunde förklara variation i smittförebyggande beteenden. Intressant för framtida studier är att undersöka vad som ligger till grund för dessa resultat samt vidare undersöka vad annat som kan förklara människors beteenden vid pandemiska kriser.

Market risk is the risk of capital loss due to unexpected changes in market prices. One risk measure used to estimate market risk is Value at Risk (VaR). The common historical simulation methodology of VaR forecasting usually does not capture the time-varying volatilities associated with financial data. Therefore, dynamic factor models (DFM) are employed to improve VaR forecasting. The paper’s main focus is to use different volatility model specifications in the DFM to evaluate which is the most appropriate for VaR forecasting. The volatility models considered are the Constant Conditional Correlation (CCC-) GARCH, the Dynamic Conditional Correlation (DCC-) GARCH, and the corrected Dynamic Conditional Correlation (cDCC-) GARCH. The method is applied to an empirical dataset consisting of Swedish large-cap stocks between 2017-2021 where two different portfolios are used, the equally- and the value-weighted portfolio. The data purposefully includes the COVID-19 pandemic such that the models can be compared during less- and more volatile periods. The method is further evaluated in a simulation study where randomized portfolio weights are used. It is found that the VaR forecasts produced by the three different model specifications are similar throughout the entire sample. Therefore the most restricted volatility model (CCC-GARCH) is recommended.

Background: KAM has received a lot of attention over the last decade, where organizations acknowledge the benefits, and choose to implement KAM programs within their companies. Research shows that the individual in a KAM manager role has a huge impact on the outcomes of KAM, crucially responsible for the relationships with the key accounts. Furthermore, there is a clear link between the selection of the right candidate in order to succeed with KAM, and the personality traits of a KAM manager.    Problem: Limited research has been carried out on the personality traits of KAM managers connected to the FFM, yet scholars indicate that the individual has a large effect on the outcomes of KAM. Also, few researchers study both the buyer´s and the supplier's side within KAM relationships, even though mutual benefits are an essential part of KAM.   Purpose: The purpose of the study is to identify if there is an existing mutual understanding between the buyer and supplier regarding valuable traits of a KAM manager to benefit KAM outcomes.    Method: The study utilizes a qualitative research approach, collecting primary data through six semi-structured interviews. The number of participants was equally distributed between buyers and suppliers, all experienced working with KAM. A thematic analysis was then used to analyze the empirical findings.     Conclusion: Based on the results, a conclusion is drawn that there is no mutual understanding between the buyer and supplier regarding valuable traits of a KAM manager. Aligning with previous research, all participants shared the view concerning the individual's importance in KAM, however having divided opinions about which personality traits would contribute to the valuable outcomes. The buyers emphasized the importance of structure and planning relating to the personality trait conscientiousness to optimize KAM outcomes, while the suppliers rather placed focus on aspects connecting to the personality trait extraversion.

A latent factor model for count data is popularly applied when deconvoluting mixed signals in biological data as exemplified by sequencing data for transcriptome or microbiome studies. Due to the availability of pure samples such as single-cell transcriptome data, the estimators can enjoy much better accuracy by utilizing the extra information. However, such an advantage quickly disappears in the presence of excessive zeros. To correctly account for such a phenomenon, we propose a zero-inflated non-negative matrix factorization that models excessive zeros in both mixed and pure samples and derive an effective multiplicative parameter updating rule. In simulation studies, our method yields smaller bias comparing to other deconvolution methods. We applied our approach to gene expression from brain tissue as well as fecal microbiome datasets, illustrating the superior performance of the approach. Our method is implemented as a publicly available R-package, iNMF. In zero-inflated non-negative matrix factorization (iNMF) for the deconvolution of mixed signals of biological data, pure-samples play a significant role by solving the identifiability issue as well as improving the accuracy of estimates. One of the main issues of using single-cell data is that the identities(labels) of the cells are not given. Thus, it is crucial to sort these cells into their correct types computationally. We propose a nonlinear latent variable model that can be used for sorting pure-samples as well as grouping mixed-samples via deep neural networks. The computational difficulty will be handled by adopting a method known as variational autoencoding. While doing so, we keep the NMF structure in a decoder neural network, which makes the output of the network interpretable.

Intrinsic connectivity networks (ICNs) refer to brain functional networks that are consistently found under various conditions, during tasks or at rest. Some studies demonstrated that while some stimuli do not impact intrinsic connectivity, other stimuli actually activate intrinsic connectivity through suppression, excitation, moderation or modi cation. Most analyses of functional magnetic resonance imaging (fMRI) data use ad-hoc methods to estimate the latent structure of ICNs. Modeling the effects on ICNs has also not been fully investigated. Bayesian Intrinsic Connectivity Network (BICNet) captures the ICN structure with We propose a BICNet model, an extended Bayesian dynamic sparse latent factor model, to identify the ICNs and quantify task-related effects on the ICNs. BICNet has the following advantages: (1) It simultaneously identifies the individual and group-level ICNs; (2) It robustly identifies ICNs by jointly modeling resting-state fMRI (rfMRI) and task-related fMRI (tfMRI); (3) Compared to independent component analysis (ICA)-based methods, it can quantify the difference of ICNs amplitudes across different states; (4) The sparsity of ICNs automatically performs feature selection, instead of ad-hoc thresholding. We apply BICNet to the rfMRI and language tfMRI data from the Human Connectome Project (HCP) and identify several ICNs related to distinct language processing functions.

Relationen mellan ekonomisk framgång (inkomst), personlighetsdragetsamvetsgrannhet och begåvning undersöktes för könsuppdelade grupper medbegåvning i fjärde kvartilen. Syftet var att se om hög samvetsgrannhet och IKkunde predicera ekonomisk framgång bland personer med hög begåvning.Datainsamlingen skedde genom att extrahera relevanta individer urWisconsin Longitudinal Study. I den ursprungliga datainsamlingen deltogtotalt 10 317 personer. T-test genomfördes för att jämföra inkomster för högtbegåvade kvinnor och män. Multipla regressionsanalyser genomfördes föratt undersöka begåvningens och samvetsgrannhetens effekt på årsinkomstenför de högt begåvade männen och kvinnorna. Studien visade att högbegåvadekvinnor och män hade signifikanta löneskillnader samt att samvetsgrannhetoch hög begåvning med signifikans kunde användas för att predicera inkomstför såväl gruppen kvinnor som för gruppen män. / The relationship between economic success (income), the personality traitconscientiousness and IQ were examined for gender-segregated groups withIQ in the fourth quartile. The purpose was to see if high conscientiousnessand IQ could predict financial success in the subgroups. Data collection wascarried out by extracting relevant individuals from the WisconsinLongitudinal Study. A total of 10,317 people participated in the original datacollection. A t-test was performed to compare incomes for women and menwith high IQ. Multiple regression analysis was conducted to examine theeffect of IK and conscientiousness on the income of the high IQ group of menas well as for the high IQ group of women. The study showed that highlygifted women and men had significant pay differences as well as thatconscientiousness and IQ were significant predictors of income for both thegroup of women and the group of men.

Termen resiliens definieras som förmågan att mentalt eller känslomässigt hantera och återhämta sig efter stressfyllda situationer. Tidigare forskning inom området tyder på att det finns en korrelation mellan särskilda personlighetsdrag i femfaktorteorin och den individuella graden av resiliens. Syftet med denna studie var att undersöka detta samband hos chefer inom äldreomsorgen, ett yrke som omfattar en tung arbetsbelastning inom en redan stressfylld sektor i arbetslivet. I studien undersöktes även relationen mellan tiden som chef inom äldreomsorgen och den individuella graden av resiliens. En enkätstudie utfördes med deltagare som besitter chefsroller inom den kommunala äldreomsorgen (n=58, Målder=48,77, SD=9,54). Data analyserades med två multipla regressionsanalyser, och korrelationen mellan faktorerna analyserades med Pearsons korrelationskoefficient. Efter Bonferroni-korrigering var de enda signifikanta faktorerna samvetsgrannhet och neuroticism. Resultatet av studien påvisar att samvetsgrannhet har en signifikant positiv korrelation och neuroticism har en signifikant negativ korrelation med resiliens. Angående sambandet mellan tiden som chef inom äldreomsorgen och resiliens, så påvisar undersökningen att det inte fanns någon signifikant korrelation. De starkaste personlighetsdragen för att predicera en hög grad av individuell resiliens hos chefer inom den kommunala äldreomsorgen var samvetsgrannhet och neuroticism. Antalet år som chef inom äldreomsorgen och dess påverkan på resiliens överensstämde inte med tidigare studier, där antalet år som chef borde ha ökat den individuella graden av resiliens. Kunskapen om personlighet och erfarenhets samband med resiliens kan potentiellt bidra till att öka resiliens inom den kommunala äldreomsorgen. / The term resilience is defined as the ability to mentally and emotionally cope from stressful events. Research has shown that there is a correlation between some of the personality traits in the five-factor model, and the individual level of resilience. The purpose of this study was to examine this relationship in nursing management, an occupation which involves heavy workloads in an already stressful sector. This study also examined the relationship between time spent as an eldercare manager and the individual level of resilience. A survey was conducted with participants who are in managerial positions in the municipal eldercare (n=58, Mage=48,77, SD=9,54). The data were analyzed using two multiple regressionanalyses, and the correlation between the factors was analyzed with the use of Pearson’s correlation coefficient. After Bonferroni-correction the only significant factors were conscientiousness and neuroticism. The result corresponds with current research, which proposes that conscientiousness has a significant positive correlation, and neuroticism has a significant negative correlation with resilience. Regarding the relationship between time spent as an eldercare manager and resilience, the results showed that there was no significant correlation. The traits conscientiousness and neuroticism were the strongest to predict a higher level of individual resilience amongst municipal eldercare managers. Time spent as an eldercare manager and its impact on resilience did not correspond with previous studies, were time spent as an eldercare manager should raise the individual level of resilience. Knowledge of the relationship between personality, experience and resilience might contribute to increased resilience in municipal eldercare.

Syftet med studien är att undersöka om det går att predicera individers attribution av negativ kritik från sin chef till externa eller interna orsaker i hypotetiska situationer, beroende på individens personlighetsdrag enligt femfaktormodellen. Datainsamling genomfördes på sociala medier via en digital enkät, baserad på The Attributional Style Questionnaire och en svensk översättning av Ten-Item Personality Inventory. De 116 respondenterna i studien har varit verksamma i arbetslivet under minst ett år på en anställningsgrad på 50% eller mer. Studien visade att personlighetsdragen från femfaktorsmodellen inte kunde predicera om en individ attribuerade externt eller internt avseende negativ kritik från chefen. Ingen signifikant skillnad mellan könen hittades. / The purpose of the study was to investigate whether it was possible to predict an individual's attribution of negative criticism from their boss in hypothetical situations (based on internal- external attribution and the five-factor model). Data collection was carried out on social media through a digital survey, based on The Attributional Style Questionnaire and a Swedish translation of the Ten-Item Personality Inventory. The 116 participants involved in the study had a work experience of a minimum of one year, with a full-time position or part- time employment of 50% or higher. The study showed that personality traits could not predict whether an individual attributed external or internal negative criticism from the manager. No significant difference between the sexes was found.

Childhood adversity is linked with a variety of negative outcomes including suicide attempts and personality disorders, most commonly Borderline Personality Disorder (BPD). A core feature of BPD, emotion dysregulation is often reported following early childhood adversity and contributes to both suicidal ideation and attempts. One explanation for the development of emotion dysregulation within BPD, is the biosocial model, which states that there must be an interaction between childhood emotional vulnerability and parental invalidation. Recent literature suggests that this interaction may not be necessary. Thus, the current study extended previous literature by examining childhood risk factors (i.e., ACES, parental invalidation, and childhood emotional vulnerability) as individual and interactive effects in predicting both BPD and suicide directly, as well as indirectly predicting suicide through BPD. Overall, the results indicated that all three risk factors individually predicted BPD and suicide risk and that the biosocial interaction also significantly predicts BPD and suicide risk.

This study uses a sample of 600 companies from Europe to investigate the risk-adjusted returns of four portfolios with high and low ESG ratings between 2011 and 2021. Four asset pricing models and additional measures for risk and return are tested on different portfolio weights. The findings show that there are no statistical differences in risk-adjusted returns between portfolios with high and low ESG scores. These findings are evident when sole capital gain is considered, and when dividends are reinvested. Differences can however be discerned between portfolio weights. All portfolios show excess returns when adjusted for risk factors in the market. The results from this study contribute to the literature surrounding ESG assets by providing evidence of how high- and low-rated ESG stocks have performed in the European market. This study has practical implications for actors in the capital markets, as it is evident from the results that ESG ratings have no apparent effect on the risk-adjusted returns of a portfolio. If sustainability is of high importance, high ESG companies offer the advantage of aligning financial performance with stakeholder goals, as well as providing adequate returns.