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The present thesis is a philological study that describes Russian-English-Russian lexicographical works of the period between the sixteenth and the nineteenth century and concentrates on the most noteworthy English-Russian dictionaries. The aim of the thesis is to pay the intellectual debt to the compilers of English-Russian dictionaries of the period from the sixteenth to the end of the nineteenth century, whose works can be considered as inalienable parts of the evolution of the English-Russian lexicography. In total, eleven English-Russian and one Russian-English dictionaries are studied and described. The description of the dictionaries includes the information on the author(s), place and time of publishing, macro- and microstructures of the dictionaries, improvements and novelty as compared to their predecessors. The description of these dictionaries, their structural analysis and the research based on the related works on Russian bilingual lexicography allow to depict the gradual four centuries long process of English-Russian lexicography development. Throughout the evolution of the English-Russian lexicography, it is possible to see how the organization and presentation of word lists have become more uniform, and the amount of information provided for the user grew. A separate chapter is devoted to A. Alexandrow’s Complete English-Russian Dictionary (1891) that has been studied relatively little. Apart from depiction of the dictionary’s macro- and microstructures, transliteration patterns are illustrated, obsolete and archaic words, and lexemes that do not have a separate entry in the Oxford English Dictionary are demonstrated. The presence of these words has been verified against the dictionaries that are mentioned in the preface of Complete English-Russian Dictionary, namely Reiff’s New Parallel Dictionaries of the Russian, French, German and English Languages, Webster’s Complete Dictionary of the English Language and Nuttall’s Standard Pronouncing Dictionary of the English Language. Additionally, Grammatin and Parenogo’s New Dictionary English and Russian and Banks’s Dictionary of the English and Russian Languages have been examined as the possible sources of these lexemes. The comparative analysis of these lexemes shows that despite their absence from the Oxford English Dictionary almost all words can be met in one or several well-known nineteenth century dictionaries. This paper illustrates the gradual evolution of the English-Russian lexicography and shows that despite their absence from the Oxford English Dictionary almost all words can be met in one or several dictionaries analysed.

The purpose of this thesis is to act as a guide for the 2017 article A study guide for the l^2 decoupling theorem by J. Bourgain and C. Demeter. However, this thesis is self-sufficient. The aim has been to give a detailed presentation and handle the weight exponent E especially carefully in the arguments. We begin by presenting the decoupling inequality of the l^2 decoupling theorem and the associated Fourier transform -like operator. The theorem concerns finding a satisfactory upper bound for the decoupling constant related to the inequality. We also list some general results that a graduate student might not be very familiar with; among them are a few consequences of Hölder's inequality. We move on to study the properties of the weight functions that we use in the L^p-norms in the decoupling. We present two operator lemmas to which we can reduce many of our arguments. The other lemma gives us the opportunity to use certain Schwartz functions in our proofs. We then move on to prove the l^2 decoupling theorem in the lower range 2<= p <= (2n)/(n-1). This includes the definition of multilinear decoupling constants and an iterative process.

Corporate credit risk in fixed income markets refers to risk that debt issuing company will default before the maturity of the debt or to decrease in the market value of debt due to decreasing credit quality. A number of quantitative credit risk models have been developed to measure probability of default and/or credit spreads of fixed income investments. These models can be roughly divided into two categories based on their approach to credit risk modelling; structural and reduced form models. Several commercial applications have been developed based on both model branches and used in financial markets as tool for analyzing real life investment decisions. The aim of this thesis is to introduce the theoretical framework behind structural and reduced form credit risk models and present a comparative analysis on the strengths and weaknesses of different models. A base case model for structural (Merton 1974) and for reduced form (Jarrow-Turnbull 1995) is presented in more detail and differences are discussed based on earlier academic research in the area. Even the objectives of the models are similar the two approaches are totally different from the theoretical point of view. Structural models are based on Merton´s model and use Black- Scholes option pricing framework as foundation of credit risk analysis. Reduced form models instead can be considered as a statistical approach to credit risk modelling using market data on bond prices and credit spreads to measure probability of default. Empirical part of the thesis consists of review of several empirical studies testing the empirical soundness of different structural and reduced form models. The aim of this part is to find reasoning to recommend either structural or reduced form models for investor use. Main findings suggest that when choosing credit risk model the purpose of the use becomes a decisive factor. It can be argued that structural models in general are more suitable for analyzing credit risk of individual companies with company specific needs due to their ability to offer economic causality. In the other hand the reduced form models could be recommended to use for trading and hedging purposes for traders and credit managers working with liquid bond markets. Reduced form models are highly data sensitive and need high quality market data. Several studies suggest that structural models perform better when working with lower rated bonds (below investment grade) whereas reduced form models are more suitable for higher rated bonds (investment grade). Reduced form models can be seen as more modern approach to credit risk modelling.

South Africa is one of the largest asylum seekers receiving countries in the world. Refugees in South Africa are often unable to enjoy their legal rights and freedoms because of the wide-spread xenophobia and public institutions’ unawareness of the refugees’ rights in the country. Forced migrants face multiple challenges to earn and maintain a sustainable livelihood in South Africa. Self-reliance has become an important goal in humanitarian aid organizations’ attempts to enhance the economic and social empowerment of the refugees. Various self-reliance programs aim to develop and strengthen the refugees’ livelihoods and reduce their vulnerability and long-term reliance on humanitarian aid. The research focuses on Cape Town Refugee Center’s Self-reliance Program that aims to enhance the economic security of the forced migrants in the region. The program gives small business grants to refugees and asylum seekers to set up a business of their own. The research seeks to find out how the program works in practice and what effects the program has had on the economic security of the beneficiaries. The research looks into the biggest challenges of the forced migrants to set up a business of their own and reach self-reliance in Cape Town. The research seeks to find out what factors lead to the success or failure of the forced migrants’ businesses and how xenophobia affects the forced migrants’ possibilities to reach self-reliance. In addition, the research seeks to find out how the concept of self-reliance is understood by the forced migrants and by the self-reliance officer of the Refugee Center. The research material was collected during a six weeks long fieldwork period in Cape Town. The research was carried out by using qualitative research methods. Sixteen beneficiaries of the Self-reliance Program and the self-reliance officer of the Cape Town Refugee Center were interviewed by semi-structured interviews. Content analysis was used as a method of analysis of the interviews. The Self-reliance Program’s beneficiaries’ experiences are compared with theoretical discussion of migration and livelihood research as well as with previous studies of the forced migrants’ experiences in South Africa. In addition, the research looks into South Africa’s refugee situation and policy as well as into the issue of xenophobia in the country. The research shows that besides material assistance the Self-reliance program offers empowering mental coaching for the beneficiaries. According to the research the social networks and the location of the business site are crucial for the success of the business, whereas the lack of support and social networks, insufficient business knowledge and having the business in an unsafe are the main reasons for the failure of the businesses. The biggest obstacles for the forced migrants to reach self-reliance in Cape Town are the documents, xenophobic attitude of people and public institutions, lack of support and safety, lack of information and possibilities to education as well as the difficulty to find employment in the formal sector. The main conclusion of the research is that the self-reliance programs for the forced migrants should highlight the importance of social networks, the safe location of the business site as well as offer good business training for the beneficiaries. South Africa’s refugee policy should be transformed to make it easier for the forced migrants to enjoy their legal rights and to be able to reach economic independence. Instead of depicting forced migrants as an economic threat to the country, the focus should be shifted on what value the forced migrants can offer to South Africa with their skills and know-how.

The study addresses an estimation problem faced by a large borrower, such as a government, related to an interest rate risk measure known as Cost-at-Risk, or CaR. The term denotes a threshold level of debt costs such that the actual debt costs incurred in a given time (say, one year) will be less than this threshold level with a given probability (say, 95 %). The main obstacle to determining CaR is that the probability distribution of future levels of interest rates is unknown. For this purpose, various models of the term structure of interest rates have been developed. This study takes one particular term structure model, the Longstaff–Schwartz model, under examination in order to determine its inherent suitability for the estimation of CaR. The model is an affine two-factor equilibrium model with analytic solutions for bond and option prices. The accuracy of the model is studied by simulating interest rate pseudo-data using a simulation program which corresponds exactly to the model’s assumptions, and then recalibrating the model to the pseudo-data. Given that the properties of the data-generating process (DGP) are known exactly, this approach allows us to compare the CaR estimates implied by the recalibrated model against the CaR implied by the actual properties of the DGP. Particular attention is paid to the methods by which the model is calibrated to data. In an effort to improve the accuracy of the Longstaff–Schwartz model, a new calibration method is developed. In order to appraise the accuracy of the Longstaff–Schwartz model, we compare its performance to that of a simpler benchmark model based on the Nelson–Siegel decomposition of the yield curve. The accuracy of the CaR estimates given by the two models is compared both in an environment where the DGP is of the Longstaff–Schwartz type, and in another environment where the DGP is of the Nelson–Siegel type. The results of the comparison can be summarized as follows. The new calibration method for the Longstaff–Schwartz model is highly accurate when the DGP is of the LS type, but is useless in the NS-type environment. When the LS model is calibrated using the technique proposed by Longstaff and Schwartz themselves, it turns out that the model gets no advantage from being correctly specified. When correctly specified, it fails to calibrate to data in about 25% of all cases, but when it is misspecified, the failure rate drops to 2.4%, and its accuracy improves and surpasses that of the NS model. These results are highly unexpected. It is possible that they are specific to the parameter values used in the simulations, but this issue is left for further research.

Sums of log-normally distributed random variables arise in numerous settings in the fields of finance and insurance mathematics, typically to model the value of a portfolio of assets over time. In particular, the use of the log-normal distribution in the popular Black-Scholes model allows future asset prices to exhibit heavy tails whilst still possessing finite moments, making the log-normal distribution an attractive assumption. Despite this, the distribution function of the sum of log-normal random variables cannot be expressed analytically, and has therefore been studied extensively through Monte Carlo methods and asymptotic techniques. The asymptotic behavior of log-normal sums is of especial interest to risk managers who wish to assess how a particular asset or portfolio behaves under market stress. This motivates the study of the asymptotic behavior of the left tail of a log-normal sum, particularly when the components are dependent. In this thesis, we characterize the asymptotic behavior of the left and right tail of a sum of dependent log-normal random variables under the assumption of a Gaussian copula. In the left tail, we derive exact asymptotic expressions for both the distribution function and the density of a log-normal sum. The asymptotic behavior turns out to be closely related to Markowitz mean-variance portfolio theory, which is used to derive the subset of components that contribute to the tail asymptotics of the sum. The asymptotic formulas are then used to derive expressions for expectations conditioned on log-normal sums. These formulas have direct applications in insurance and finance, particularly for the purposes of stress testing. However, we call into question the practical validity of the assumptions required for our asymptotic results, which limits their real-world applicability.

It is general industry practice to attach penalty and liquidated damages clauses to, for example, construction and supply contracts as well as non-compete clauses and confidentiality or non-disclosure agreements. The subject matter of this research project is the use and treatment of such penalty and liquidated damages clauses under Finnish and English laws. Contract terms constituting penalty and liquidated damages clauses are generally enforceable under Finnish law, while English law distinguishes between unenforceable penalty clauses and enforceable liquidated damages clauses. Therefore, the objective of this research project is to, through an examination and comparison of the subject matter, rethink penalty and liquidated damages clauses by looking past the enforceable/unenforceable divide, as it may not be as explicit as seems. Three points are made regarding the acute practical relevance of the subject matter: pervasiveness; balancing of interests in contractual relationships; and, not least, legal certainty. This research project contains seven chapters. Each chapter is built upon the discussion in the preceding chapters, rendering the structure both logical and methodologically viable. Chapter 1 introduces the subject matter, objectives and rationales for the carrying out of this research project as is. Chapter 2 describes, in brief, the methodological choices made over the course of this research project. The first substantive chapter, Chapter 3, presents the legal nature, functions and classification of penalty and liquidated damages clauses to facilitate their examination and comparison. Chapters 4 and 5 examine the use and treatment of penalty and liquidated damages clauses under Finnish and English laws respectively. Chapter 6 compares the use and treatment of such clauses under both approaches through an attempt to, if not answer, at least review each of the research questions set out in Chapter 1. Chapter 7 concludes. Functional comparative law methodology was chosen for the examination and comparison of the subject matter because of interest are particularly the prevailing solutions to the balancing of interests in contractual relationships, an exercise that arises when judges engage in the interpretation of contract terms. Such exercise entails, for example, the weighing of pacta sunt servanda and the principles of individual autonomy and freedom of contract against weaker party protection. Therefore, on one hand, the Finnish and English law approaches each recognize the intention of the parties to a contract as the starting point for the interpretation of contract terms. On the other hand, both approaches have in place a legal rule or practice that ensures weaker party protection. Under Finnish law, penalty and liquidated damages clauses are subject to review by judges under the adjustment mechanism set out in section 36 of the Finnish Contracts Act, while under English law, the same is possible under the penalty rule.

This thesis focuses on statistical topics that proved important during a research project involving quality control in chemical forensics. This includes general observations about the goals and challenges a statistician may face when working together with a researcher. The research project involved analyzing a dataset with high dimensionality compared to the sample size in order to figure out if parts of the dataset can be considered distinct from the rest. Principal component analysis and Hotelling's T^2 statistic were used to answer this research question. Because of this the thesis introduces the ideas behind both procedures as well as the general idea behind multivariate analysis of variance. Principal component analysis is a procedure that is used to reduce the dimension of a sample. On the other hand, the Hotelling's T^2 statistic is a method for conducting multivariate hypothesis testing for a dataset consisting of one or two samples. One way of detecting outliers in a sample transformed with principal component analysis involves the use of the Hotelling's T^2 statistic. However, using both procedures together breaks the theory behind the Hotelling's T^2 statistic. Due to this the resulting information is considered more of a guideline than a hard rule for the purposes of outlier detection. To figure out how the different attributes of the transformed sample influence the number of outliers detected according to the Hotelling's T^2 statistic, the thesis includes a simulation experiment. The simulation experiment involves generating a large number of datasets. Each observation in a dataset contains the number of outliers according to the Hotelling's T^2 statistic in a sample that is generated from a specific multivariate normal distribution and transformed with principal component analysis. The attributes that are used to create the transformed samples vary between the datasets, and in some datasets the samples are instead generated from two different multivariate normal distributions. The datasets are observed and compared against each other to find out how the specific attributes affect the frequencies of different numbers of outliers in a dataset, and to see how much the datasets differ when a part of the sample is generated from a different multivariate normal distribution. The results of the experiment indicate that the only attributes that directly influence the number of outliers are the sample size and the number of principal components used in the principal component analysis. The mean number of outliers divided by the sample size is smaller than the significance level used for the outlier detection and approaches the significance level when the sample size increases, implying that the procedure is consistent and conservative. In addition, when some part of the sample is generated from a different multivariate normal distribution than the rest, the frequency of outliers can potentially increase significantly. This indicates that the number of outliers according to Hotelling's T^2 statistic in a sample transformed with principal component analysis can potentially be used to confirm that some part of the sample is distinct from the rest.