This thesis addresses the current, ever-developing framework of rules governing trading in the most widespread financial instrument - OTC derivatives. The main objective of the thesis is to analyse the current state of the regulation of trading in OTC derivatives within the EU - namely, the EMIR Regulation. Subsequently, it examines whether the legal framework has been set up properly and effectively, and explores what steps should be taken in the near future in order to improve it. Given that the subject of this thesis is much more of an economic than a legal nature, its first part introduces OTC derivatives as a concept, and the specifics of trading in them. The second part examines the status of OTC derivatives within the financial market over time, starting from their modern-day beginnings in the 1990s, through their role in the global financial crisis of 2007 and 2008, to the current issues related to them. The main part of the thesis is devoted to the EMIR Regulation, its scope of application, and in particular the three main obligations which EMIR introduces in relation to OTC derivatives. These comprise, firstly, the obligation to perform a central clearing through central counterparties; secondly, the obligation to observe specific risk mitigation techniques for OTC derivative contracts...

Die Produktionsplanung in kommerziellen Enterprise Ressource Planning Systemen und Produktionsplanungs- und -steuerungssystemen erfolgt unter unzureichender Berücksichtigung von beschränkten Kapazitäten. Dies führt oft zu unzulässigen Plänen, welche nicht selten zu einer Verfehlung der termingerechten Bedarfsdeckung führen. Durch den Einsatz sogenannter Clearing Functions (CF) können die nicht linearen Abhängigkeiten zwischen der Arbeitslast eines Produktionssystems und der zu erwartenden Ausbringungsmenge beschrieben werden. Eine solche CF kann empirisch durch den Einsatz von Simulation ermittelt werden und zu einer verbesserten Kapazitätsabschätzung in der operativen Produktionsplanung und -steuerung beitragen.

A incessante busca do homem pela eficiência e sofisticação dos processos por ele manejados em todas as áreas do conhecimento, aliada aos grandes avanços tecnológicos das últimas décadas, tem gerado importantes alterações nos meios de pagamento e na sistemática de liquidação financeira de obrigações. Com o surgimento de mecanismos mais robustos de liquidação, estamos observando a substituição dos meios de pagamento em papel e das transações isoladas entre os indivíduos pela informatização da negociação e o aumento do raio de abrangência das caixas de liquidação. Este trabalho levanta o panorama histórico das câmaras de liquidação, traçando o estado da arte dessa figura no Brasil e suas principais questões jurídicas, também verificando sua aderência às melhores práticas experimentadas em mercados desenvolvidos / Mankinds endless quest for efficiency and sophistication of the processes managed by the men in all areas of knowledge, coupled with major technological advances of recent decades, has generated important changes in payment methods and the clearing of financial obligations. With the emergence of more robust mechanisms of settlement, we are watching the replacement of paper-based payment methods and transactions between isolated individuals by the computerization of trading and the increase of the radius of coverage of the settlement institutions. This work traces the historical view of the clearing houses, outlining the state of the art of this figure in Brazil and its main legal issues, and checking if it complies with the best practices already experienced in developed markets.

A incessante busca do homem pela eficiência e sofisticação dos processos por ele manejados em todas as áreas do conhecimento, aliada aos grandes avanços tecnológicos das últimas décadas, tem gerado importantes alterações nos meios de pagamento e na sistemática de liquidação financeira de obrigações. Com o surgimento de mecanismos mais robustos de liquidação, estamos observando a substituição dos meios de pagamento em papel e das transações isoladas entre os indivíduos pela informatização da negociação e o aumento do raio de abrangência das caixas de liquidação. Este trabalho levanta o panorama histórico das câmaras de liquidação, traçando o estado da arte dessa figura no Brasil e suas principais questões jurídicas, também verificando sua aderência às melhores práticas experimentadas em mercados desenvolvidos / Mankinds endless quest for efficiency and sophistication of the processes managed by the men in all areas of knowledge, coupled with major technological advances of recent decades, has generated important changes in payment methods and the clearing of financial obligations. With the emergence of more robust mechanisms of settlement, we are watching the replacement of paper-based payment methods and transactions between isolated individuals by the computerization of trading and the increase of the radius of coverage of the settlement institutions. This work traces the historical view of the clearing houses, outlining the state of the art of this figure in Brazil and its main legal issues, and checking if it complies with the best practices already experienced in developed markets.

Model-Based Testing has shown tangible benefits in previous research exploring widespread domains. Clearing systems in financial markets however are large software systems in which these approaches rarely have been explored. This paper in particular explores the Model-Based Testing approach using Modbat, a specialized tool based on extended finite-state machines, as a complementary testing approach on software clearing systems at Nasdaq. In particular, the approach is applied to functionalities of the system to test both its ability to find bugs undiscovered by traditional methods, as well as to measure its effectiveness and efficiency in creating reliable coverage in short amounts of time. In this study, we show that the model-based Modbat approach can achieve high code coverage with relatively little effort. 77 % of the production coverage was achieved with very few Modbat test runs. Additionally, only ∼ 9-14 % of the same lines of code, and a fraction of the time were required to achieve these results. From this, we conclude that Model-Based Testing approaches such as Modbat allow for significantly more efficient testing in terms of coverage over time compared to manual approaches. / Modellbaserad testning har visat på konkreta fördelar i tidigare forskning som utforskat omfattande områden. Clearingsystem inom finansmarknader är dock stora programvarusystem där dessa metoder sällan har utforskats. Denna arbete utforskar specifikt modellbaserad testning med användning av Modbat, ett specialiserat verktyg baserat på utökade ändliga automater, som ett kompletterande testningsmetodik för programvarurensningssystem på Nasdaq. Särskilt tillämpas metoden på specifika funktioner i systemet för att testa både dess förmåga att hitta buggar som inte upptäckts av traditionella metoder och att mäta dess effektivitet att skapa pålitlig täckning av kod på kort tid. I denna studie visar jag att den modellbaserade Modbat-metoden kan uppnå hög kodtäckning med relativt lite ansträngning. 77 % av produktionskoden täcktes med mycket få Modbat-testkörningar. Dessutom krävdes endast cirka 9-14 % av samma LOC, och en bråkdel av tiden för att uppnå dessa resultat.

Habitat fragmentation involves the break-up of continuous native vegetation into remnant patches that are set in a matrix of altered habitat. The consequences of habitat fragmentation include the loss of original habitat which is followed by reductions in remnant size that increase edge effects and reduce habitat quality, and also increase the isolation of remnants from one another. Habitat fragmentation is an international environmental concern that also effects Australia. Over the last ten years Queensland has been responsible for some ninety percent of the clearing occurring in Australia, and as a result recorded some of the highest vegetation clearing rates in the world. / thesis (PhDEnvironmentalManagement)--University of South Australia, 2004.

This thesis consists of four self-contained papers related to banking, credit markets and financial stability.    Paper [I] presents a credit market model and finds, using an agent based modeling approach, that credit crunches have a tendency to occur; even when credit markets are almost entirely transparent in the absence of external shocks. We find evidence supporting the asset deterioration hypothesis and results that emphasize the importance of accurate firm quality estimates. In addition, we find that an increase in the debt’s time to maturity, homogenous expected default rates and a conservative lending approach, reduces the probability of a credit crunch. Thus, our results suggest some up till now partially overlooked components contributing to the financial stability of an economy.     Paper [II] derives an econometric disequilibrium model for time series data. This is done by error correcting the supply of some good. The model separates between a continuously clearing market and a clearing market in the long-run such that we are able to obtain a novel test of clearing markets. We apply the model to the Swedish market for short-term business loans, and find that this market is characterized by a long-run nonmarket clearing equilibrium.    Paper [III] studies the risk-return profile of centralized and decentralized banks. We address the conditions that favor a particular lending regime while acknowledging the effects on lending and returns caused by the course of the business cycle. To analyze these issues, we develop a model which incorporates two stylized facts; (i) banks in which lendingdecisions are decentralized tend to have a lower cost associated with screening potential borrowers and (ii) decentralized decision-making may generate inefficient outcomes because of lack of coordination. Simulations are used to compare the two banking regimes. Among the results, it is found that even though a bank group where decisions are decentralizedmay end up with a portfolio of loans which is (relatively) poorly diversified between regions, the ability to effectively screen potential borrowers may nevertheless give a decentralized bank a lower overall risk in the lending portfolio than when decisions are centralized.    In Paper [IV], we argue that the practice used in the valuation of a portfolio of assets is important for the calculation of the Value at Risk. In particular, a seller seeking to liquidate a large portfolio may not face horizontal demand curves. We propose a partially new approach for incorporating this fact in the Value at Risk and Expected Shortfall measures and in an empirical illustration, we compare it to a competing approach. We find substantial differences.

Under deregulated electric market, electricity price is no longer set by the monopoly utility company rather it responds to the market and operating conditions. Offering the right amount of electricity at the right time with the right bidding price has become the key for utility companies pursuing maximum profits under deregulated electricity market. Therefore, electricity market clearing price (MCP) forecasting became essential for decision making, scheduling and bidding strategy planning purposes. However, forecasting electricity MCP is a very difficult problem due to uncertainties associated with input variables.<p> Neural network based approach promises to be an effective forecasting tool in an environment with high degree of non-linearity and uncertainty. Although there are several techniques available for short-term MCP forecasting, very little has been done to do mid-term MCP forecasting. Two new artificial neural networks have been proposed and reported in this thesis that can be utilized to forecast mid-term daily peak and mid-term hourly electricity MCP. The proposed neural networks can simulate the electricity MCP with electricity hourly demand, electricity daily peak demand, natural gas price and precipitation as input variables. Two situations have been considered; electricity MCP forecasting under real deregulated electric market and electricity MCP forecasting under deregulated electric market with perfect competition. The PJM interconnect system has been utilized for numerical results. Techniques have been developed to overcome difficulties in training the neural network and improve the training results.

This paper deals with the effects of minimum wages on human capital accumulation, and steady state employment and growth. The minimum wage is introduced in a model of endogenous growth driven by human capital accumulation. Unemployed agents maximize utility given the information that they are unemployed facing changed budget constraints. This situation is implemented in a "non-market-clearing equilibrium" framework. We show that the steady state rate of growth is not affected by the minimum wage and that in the steady state the system yields full employment. These effects are generated by intertemporal adjustments of the employed households who re-act to the relatively higher minimum wage which increases skills accumulation. (author's abstract) / Series: Department of Economics Working Paper Series

Under deregulated electric market, electricity price is no longer set by the monopoly utility company rather it responds to the market and operating conditions. Offering the right amount of electricity at the right time with the right bidding price has become the key for utility companies pursuing maximum profits under deregulated electricity market. Therefore, electricity market clearing price (MCP) forecasting became essential for decision making, scheduling and bidding strategy planning purposes. However, forecasting electricity MCP is a very difficult problem due to uncertainties associated with input variables.<p> Neural network based approach promises to be an effective forecasting tool in an environment with high degree of non-linearity and uncertainty. Although there are several techniques available for short-term MCP forecasting, very little has been done to do mid-term MCP forecasting. Two new artificial neural networks have been proposed and reported in this thesis that can be utilized to forecast mid-term daily peak and mid-term hourly electricity MCP. The proposed neural networks can simulate the electricity MCP with electricity hourly demand, electricity daily peak demand, natural gas price and precipitation as input variables. Two situations have been considered; electricity MCP forecasting under real deregulated electric market and electricity MCP forecasting under deregulated electric market with perfect competition. The PJM interconnect system has been utilized for numerical results. Techniques have been developed to overcome difficulties in training the neural network and improve the training results.