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Since the financial crisis which started in 2007, the risk awareness in the financial sector is greater than ever. Financial institutions such as banks and insurance companies are heavily regulated in order to create a harmonic and resilient global economic environment. Sufficiently large capital buffers may protect institutions from bankruptcy due to some adverse financial events leading to an undesirable outcome for the company. In many regulatory frameworks, the institutions are obliged to estimate high quantiles of their loss distributions. This is relatively unproblematic when large samples of relevant historical data are available. Serious statistical problems appear when only small samples of relevant data are available. One possible solution would be to pool two or more samples that appear to have the same distribution, in order to create a larger sample. This thesis identifies the advantages and risks of pooling of small samples. For some mixtures of normally distributed samples, with what is considered to be the same variances, the pooled data may indicate heavy tails. Since a finite mixture of normally distributed samples has light tails, this is an example of spurious heavy tails. Even though two samples may appear to have the same distribution function it is not necessarily better to pool the samples in order to obtain a larger sample size with the aim of more accurate quantile estimation. For two normally distributed samples of sizes m and n and standard deviations s and v, we find that when v=s is approximately 2, n+m is less than 100 and m=(m+n) is approximately 0.75, then there is a considerable risk of believing that the two samples have equal variance and that the pooled sample has heavy tails. / Efter den finansiella krisen som hade sin start 2007 har riskmedvetenheten inom den finansiella sektorn ökat. Finansiella institutioner så som banker och försäkringsbolag är noga reglerade och kontrollerade för att skapa en stark och stabil världsekonomi. Genom att banker och försäkringsbolag enligt regelverken måste ha kapitalbuffertar som ska skydda mot konkurser vid oväntade och oönskade händelser skapas en mer harmonisk finansiell marknad. Dessa regelverk som institutionerna måste följa innebär ofta att de ansvariga måste skatta höga kvantiler av institutionens förväntade förlustfunktion. Att skapa en pålitligt modell och sedan skatta höga kvantiler är lätt när det finns mycket relevant data tillgänglig. När det inte finns tillr äckligt med historisk data uppkommer statistiska problem. En lösning på problemet är att poola två eller _era grupper av data som ser ut att komma från samma fördelningsfunktion för att på så sätt skapa en större grupp med historisk data tillgänglig. Detta arbetet går igenom fördelar och risker med att poola data när det inte finns tillräckligt med relevant historisk data för att skapa en pålitlig modell. En viss mix av normalfördelade datagrupper som ser ut att ha samma varians kan uppfattas att komma från tungsvansade fördelningar. Eftersom normalfördelningen inte är en tungsvansad fördelning kan denna missuppfattning skapa problem, detta är ett exempel på falska tunga svansar. Även fast två datagrupper ser ut att komma från samma fördelningsfunktion så är det inte nödvändigtvis bättre att poola dessa grupper för att skapa ett större urval. För två normalfördelade datagrupper med storlekarna m och n och standardavvikelserna s och v, är det farligaste scenariot när v=s är ungefär 2, n+m är mindre än 100 och m=(m+n)är ungefär 0.75. När detta inträffar finns det en signifikant risk att de två datagrupperna ser ut att komma från samma fördelningsfunktion och att den poolade datan innehar tungsvansade egenskaper.

Keeping response times low is crucial in order to provide a good user experience. Especially the tail latency proves to be a challenge to keep low as size, complexity and overall use of services scale up. In this thesis we look at reducing the tail latency for reads in the Apache Cassandra database system by implementing the new replica selection algorithm called C3, recently developed by Lalith Suresh, Marco Canini, Stefan Schmid and Anja Feldmann. Through extensive benchmarks with several stress tools, we find that C3 indeed decreases the tail latencies of Cassandra on generated load. However, when evaluating C3 on production load, results does not show any particular improvement. We argue that this is mostly due to the variable size records in the data set and token awareness in the production client. We also present a client-side implementation of C3 in the DataStax Java driver in an attempt to remove the caveat of token aware clients. The client-side implementation did give positive results, but as the benchmark results showed a lot of variance we deem the results to be too inconclusive to confirm that the implementation works as intended. We conclude that the server-side C3 algorithm will work effectively for systems with homogeneous row sizes where the clients are not token aware. / För att kunna erbjuda en bra användarupplevelse så är det av högsta vikt att hålla responstiden låg. Speciellt svanslatensen är en utmaning att hålla låg då dagens applikationer växer både i storlek, komplexitet och användning. I denna rapport undersöker vi svanslatensen vid läsning i databassystemet Apache Cassandra och huruvida den går att förbättra. Detta genom att implementera den nya selektionsalgoritmen för replikor, kallad C3, nyligen framtagen av Lalith Suresh, Marco Canini, Stefan Schmid och Anja Feldmann. Genom utförliga tester med flera olika stressverktyg så finner vi att C3 verkligen förbättrar Cassandras svanslatenser på genererad last. Dock så visade använding av C3 på produktionslast ingen större förbättring. Vi hävdar att detta framförallt beror på en variabel storlek på datasetet och att produktionsklienten är tokenmedveten. Vi presenterar också en klientimplementation av C3 i Java-drivrutinen från DataStax, i ett försök att åtgärda problemet med tokenmedventa klienter. Klientimplementationen av C3 gav positiva resultat, men då testresultaten uppvisade stor varians så anser vi att resultaten är för osäkra för att kunna bekräfta att implentationen fungerar så som den är avsedd. Vi drar slutsatsen att C3, implementerad på servern, fungerar effektivt på system med homogen storlek på datat och där klienter ej är tokenmedvetna.

With the technology and internet development, customers are moving towards online shopping, which made the new phenomena of e-loyalty emerge out of traditional loyalty. The literature on e-loyalty has been reviewed, and the most influential antecedents to e-loyalty formation were studied in this research, e-satisfaction, and e-trust. Also, the e-tail quality dimensions were studied in this research, fulfillment/reliability, website design, customer service, and security/privacy since these dimensions majorly affect e-satisfaction and e-trust, contributing to forming e-loyalty. This research describes how e-loyalty is being formed online from a customer’s perspective since multiple processes are involved in the formation. This purpose will be reached by finding out what contributes to forming e-loyalty online from a customer’s perspective. In order to answer this research question and capture the customer’s perspective, a qualitative study was conducted with a deductive approach. Six semi-structured in-depth interviews were conducted with participants who have online shopping experiences and are e-loyal to any e-commerce website. This thesis resulted in two different processes contributing to forming e-loyalty online from a customer’s perspective. The first process involves e-satisfaction contributing to form e-loyalty, and the second process involves e-trust contributing to form e-loyalty. Both processes have a specific order to form e-loyalty because the factors affect and depend on each other in a particular pattern.

Cette thèse se présente sous la forme d’un volume de 134 pages composé de 5 articles de recherche. La thèse est une contribution empirique à la littérature qui s’est développée depuis le début des années 2000 sur les bouleversements introduits par Internet sur le commerce des biens culturels. Elle examine plus particulièrement un ensemble de questions portant sur la complémentarité ou la substitution des canaux de distribution, physiques et virtuels, l’effet de « Longue Traîne » et la dispersion des prix sur Internet. L’intérêt de la thèse est d’apporter des éléments de preuve empiriques à ces débats, grâce notamment à la création de bases de données obtenues par captation automatisée de données observables sur Internet. Les résultats statistiques et économétriques issus de ces travaux détaillent les spécificités des meilleures ventes de Livres, CD et DVD selon les canaux de distribution (Amazon, Marketplace d’Amazon, magasins physiques) mais aussi selon leur format (livres papiers/ livres numériques). D’autre part, les résultats montrent une faible variabilité des prix par les vendeurs d’Amazon Marketplace ainsi qu’un faible impact des mesures traditionnelles de la réputation (notations des vendeurs) par rapport à la taille du catalogue des vendeurs remettant en question l’utilisation de la notation comme proxy de la réputation. / This thesis is a volume of 134 pages and includes 5 research articles. The thesis is a contribution to the empirical literature that has developed since the early 2000s on the changes introduced by the Internet trade in cultural property. It examines in particular a set of questions on the complementarity or substitution distribution channels, physical and virtual, the effect of the "Long Tail Theory" and price dispersion on the Internet. The interest of this thesis is to provide empirical evidence to the debate, thanks to the creation of databases obtained by automated data capture observable on the Internet. Statistical and econometric results from these studies detail the specifics of best-selling books, CDs and DVDs as distribution channels (Amazon, Amazon Marketplace, physical stores) but also according to their format (paper books / ebooks). Regarding price dispersion, the results show a low variability of prices by sellers of Amazon Marketplace and low impact of traditional measures of reputation (ratings of sellers) compared to the size of the catalog vendors challenging the using of notation as a proxy for reputation.

<p>Perfluoroalkyl substances are synthetic organic chemicals of environmental concern because they have been associated with adverse effects in both human epidemiological studies and standard laboratory animals. In the environment, PFAS occur as mixtures, especially in areas with a history of PFAS application, such as aqueous film forming foam (AFFF) sites. Among the PFAS, perfluorooctanesulfonic acid (PFOS) and perfluorohexanesulfonic acid (PFHxS) are the most common, and occur at the highest concentrations. Thus, amphibian populations at or near AFFF sites are at risk of exposure to known bioaccumulative and persistent chemicals, likely compromising the physiology and body condition of the animals. Here, we exposed northern leopard frogs to environmentally relevant concentrations of 0.5 and 1 ppb PFOS and PFHxS, alone or as a mixture comprised of 0.5 ppb PFOS and 0.5 ppb PFHxS. Univariate analyses showed that in the larval stages, tadpoles exposed to PFAS had significantly reduced scaled mass indexes (SMI’s) relative to the control, and only the organisms exposed to PFHxS 0.5 ppb were significantly larger. Sex did not significantly influence toxicity in the later stages (GS 42 & 46), indicating no sex-related effects. Altered body condition (i.e., fat stores) in the larval stages indicate potential effects to energy balance. There is a need to assess fitness-related effects as amphibians’ transition into the terrestrial environment, and include endpoints such as: reproductive, developmental, immunological, mating, feeding, competition, and survival. Early developmental effects in the larval stages also suggests that earlier developmental endpoints may be of interest. Establishing ecological risk assessments for PFAS are necessary, as they are toxic, persistent, and bioaccumulative.</p>

Online consumption and e-tail have clearly increased in recent years, largely sinceaccessibility is an advantage that consumers notice as beneficial. The availability of e-tail has also received clear environmental disadvantages, as returns are an inevitable part of online orders. The increased return rate results in large amounts of greenhouse gas emissions, something customer groups with environmental awareness has perceived. Which leads to the purpose of this research, to provide information about environmentally conscious consumers, their behaviors, and intentions towards e-tail returns. Theinformation collected, can be of great significance to fast fashion companies, e-tail platforms, and decision-makers, to guide them in developing effective strategies aimed at promoting sustainable consumption behaviors and mitigating the detrimental environmental effects associated with returns.The empirical findings were gathered through qualitative research, where semi-structured interviews were conducted on 15 Swedish e-tail consumers in the ages 24-44. The empirical evidence was analysed with a Thematic Analysis and discussed in context with the secondary data to strengthen the collected empirical evidence.The conclusion of the thesis portray that the participating environmentally conscious consumers have a predominant insight regarding the environmental impact that occurs when returning e-tail purchases. The research shows that environmental awareness is considered when ordering and returning garments, however, to varying extents, which leads to inconsistent actions. The participants have more environmental thinking regarding the product, production, delivery and consumption i.e., the buying process that directly affects the participants. However, conflicts are identified in several aspects such as that environmental communication from e-tail companies is difficult to understand, economic aspects and the conflict of the desire for certain garments. In summary, the results show that the return process is not prioritized to the same extent as the buying process, because of indirect influence or lack of knowledge of the participants. The findings indicate that there is not always a harmony between the perceptions and actions of the participants.

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Congenital hypotrichosis in cattle is commonly referred to as "rat-tail" syndrome and is characterized by a dilution of black coat color and morphological changes to the hair shaft and tail switch. Two loci are involved in the inheritance of the rat-tail phenotype, the "extension locus" (MC1R) and an unknown locus. In order to express the rat-tail phenotype the animal must inherit at least one black allele at MC1R and be heterozygous at the unknown locus. The rat-tail locus was previously mapped to an 8.7 cM region of Bos Taurus autosome (BTA) 5. Pmel17 is known to be involved in the expression of pigmentation and maps to the same region of BTA5 as the rat-tail locus. Cattle from a population segregating for the rat-tail syndrome were sequenced at Pmel17 in order to identify putative causative mutations. Two mutations were detected, a three base pair (bp) deletion in exon 1 at codon 18 removing a leucine residue, and a single nucleotide polymorphism (SNP) at codon 612 resulting in an amino acid substitution (A?E). The 3-bp deletion in exon 1 of Pmel17 is in 100% concordance with the rat-tail phenotype in this research population and may be causative of the rat-tail phenotype.

Risk assessment for natural hazards and financial extreme events requires the statistical analysis of extreme events, often beyond observed levels. The characterization and extrapolation of the probability of rare events rely on assumptions about the extremal dependence type and about the specific structure of statistical models. In this thesis, we develop models with flexible tail dependence structures, in order to provide a reliable estimation of tail characteristics and risk measures. From a methodological perspective, this thesis makes the following novel developments. 1) We propose new copula-based models for multivariate and spatial extremes with flexible tail dependence structures, which are parsimonious and able to bridge smoothly asymptotic dependence and asymptotic independence classes, in both the upper and the lower tails; 2) Moreover, aiming at describing more general dependence structures using graphs, we propose a novel extremal dependence measure called the partial tail-correlation coefficient (PTCC) under the framework of regular variation to learn complex extremal network structures; 3) Finally, we develop a semi-parametric neural-network-based regression model to identify spatial causal effects at all quantile levels (including low and high quantiles). Overall, we make novel contributions to creating new flexible extremal dependence models, developing and implementing novel Bayesian computation algorithms, and taking advantage of machine learning and causal inference principles for modeling extremes. Our novel methodologies are illustrated by a range of applications to financial, climatic, and health data. Specifically, we apply our bivariate copula model to the historical closing prices of five leading cryptocurrencies and estimate the extremal dependence evolution over time, and we use the PTCC to learn the extreme risk network of historical global currency exchange data. Moreover, our multivariate spatial factor copula model is applied to study the upper and lower extremal dependence structures of the daily maximum and minimum air temperature from the state of Alabama in the southeastern United States; and we also apply the PTCC in extreme river discharge network learning for the Upper Danube basin. Finally, we apply the causal spatial quantile regression model in quantifying spatial quantile treatment effects of maternal smoking on extreme low birth weight of newborns in North Carolina, United States.