Aquaculture had already been distinguished as an important component of global food security and economics. However, aquaculture has expanded at the cost of natural resources and the environment. The vulnerability of the aquaculture industry due to the consequences of global environmental changes and energy price fluctuations has been addressed in various studies. The identification, planning, and implementation of sustainable energy systems are important to ensure the long term economic and environmental sustainability of aquaculture. This research investigated sustainable energy systems for aquaculture using a life cycle approach, allowing for the identification of the most sustainable energy options under different geographical and economic contexts. This also provides useful insights for the sustainable development of aquaculture with energy systems. The main objectives were to develop a statistical model for energy intensity of aquaculture (Chapter 2) and a user-friendly tool that can assist in the decision making of choosing the sustainable energy systems in aquaculture (Chapter 3), and to investigate the applicability of solar hot water systems for aquaculture (Chapter 4) and the potential improvement of the sustainability performance of aquaculture with energy systems (Chapter 5). In the first task, the main influencing factors on the energy use of aquaculture were investigated via a statistical analysis method. Results showed that natural trophic level of species, culture technology, culture system intensity, and local climatic conditions are important factors. With the key variables, an energy intensity prediction model was developed and applied to explore an energy efficient growth strategy for global aquaculture. Energy use in future global aquaculture would be significantly reduced with a selective extensification of global aquaculture. Also, climate change with consideration of temperature and precipitation would help reduce the energy use of global aquaculture as warm climate zones are more dominant in major aquaculture producing countries. In the second task, an MS-Excel based decision support tool was developed to assist the selection of environmentally and economically sustainable energy systems (single source or hybrid sources) in aquaculture. Through a case study, the most sustainable energy options for U.S. aquaponics systems were investigated, considering different geographical and economic contexts in five U.S. states (FL, HI, WA, LA, and ME). Results showed that solar systems (solar photo-voltaic and solar hot water heater) could be the most sustainable energy options for U.S. aquaponics due to their low environmental impacts and economic benefits. In the third task, results showed that heating strategies, setting (indoor or outdoor), and local climatic conditions played a pivotal role in determining the environmental and economic impacts of solar hot water systems in aquaculture. The lowest environmental impact was found with a 20% heating strategy for outdoor aquaculture systems under hot climate conditions, while the most economical case was found with an 80% heating strategy for indoor aquaculture systems under moderate climate conditions. Further improvements of environmental and economic performances could be achieved with consideration of water source (groundwater and surface) and design (horizontally fixed or optimally tilted solar thermal collector). In the fourth task, environmental and economic impacts of alternative energy systems were obtained using the tool which was developed in the second task. Results showed that local geographical and weather characteristics, local energy prices, and incentive availability were important parameters to determine the sustainability performance of alternative energy systems in aquaculture. The use of renewable energy was more sustainable than conventional energy systems in the regions where there are favorable geographical conditions, high electricity and fuel prices, and incentives. The use of solar photovoltaic with a thin-film technology was the most sustainable electricity generation options in most states of the U.S., while the use of natural gas boilers was the most sustainable heating options in most states of the U.S. The sustainability performance of the solar photovoltaic systems can be further improved through either a technological advancement or an incentive, while financial support is more effective for solar hot water systems. The application of anaerobic digestion as a backup system in general will reduce the sustainability of hybrid heating system; however, the hybrid biogas-diesel heating system has better sustainability performance compared with a diesel heating system if it is used for medium to large scale fish farms. This research provides an understanding of energy use characteristics of current aquaculture systems, and insights for the planning of sustainable energy supply systems in aquaculture, considering different growth strategies, effects of climate change, and alternative energy systems with various operational strategies and design factors. Furthermore, the decision-making tool was made to be accessible to fish farmers, state-wide planners, and regulators.

Em diversas análises estatísticas, nos deparamos com dados multinomiais, dos quais precisamos analisar o comportamento ao longo do tempo e sua relação com fatores determinantes. Os métodos clássicos para modelos de regressão multinomiais consistem em utilizar a estrutura de modelos lineares generalizados para desenvolver tais modelos McCullagh & Nelder (1989). No entanto, este enfoque apresenta algumas desvantagens como não admiter a incidência de zeros em nenhuma categoria, a hipótese da proporcionalidade da razão de chances e o fato de não serem modelos adequados para análise de dados censurados. Com o objetivo de analisar dados multinomiais com essas características propomos um modelo que é uma extensão do modelo de intensidade multiplicativo desenvolvido por Aalen (1978) e apresentado em Fleming & Harrington (2005), para variáveis aleatórias multinomiais. Com isso, ao invés de modelarmos as probabilidades associadas às categorias, como nos métodos clássicos, modelamos a função intensidade associada à variável aleatória multinomial. Através do critério martingale, estimamos os parâmetros do modelo ajustado e propomos testes de hipóteses para estes parâmetros para uma e duas populações. O teste para comparação de duas populações é baseado na estatística de logrank / In several applications, we want to analyze the behavior of multinomial datas over the time and its relationship with important factors. The classic methods commonly used for multinomial regression models are based in the generalized linear model framework. However, this models presents some disadvantages such that: it does not admit the incidence of zeros in any category, the assumption of proportionality of odds ratio and the fact that they are not appropriate models to analyze censored data. For multinomial data analyses with this characteristics, we propose a model that it is an extension of the multiplicative intensity model developed by Aalen to random multinomial variables. Therefore, instead of modeling the categorical probabilities, as in the classics methods, we modeled the intensity fuction associated with the multinomial variable. Using the martingale criterion, we estimate the models parameters and propose hypothesis testing for these parameters for one and two populations. The test for comparing two populations is based in the logrank statistics

Em diversas análises estatísticas, nos deparamos com dados multinomiais, dos quais precisamos analisar o comportamento ao longo do tempo e sua relação com fatores determinantes. Os métodos clássicos para modelos de regressão multinomiais consistem em utilizar a estrutura de modelos lineares generalizados para desenvolver tais modelos McCullagh & Nelder (1989). No entanto, este enfoque apresenta algumas desvantagens como não admiter a incidência de zeros em nenhuma categoria, a hipótese da proporcionalidade da razão de chances e o fato de não serem modelos adequados para análise de dados censurados. Com o objetivo de analisar dados multinomiais com essas características propomos um modelo que é uma extensão do modelo de intensidade multiplicativo desenvolvido por Aalen (1978) e apresentado em Fleming & Harrington (2005), para variáveis aleatórias multinomiais. Com isso, ao invés de modelarmos as probabilidades associadas às categorias, como nos métodos clássicos, modelamos a função intensidade associada à variável aleatória multinomial. Através do critério martingale, estimamos os parâmetros do modelo ajustado e propomos testes de hipóteses para estes parâmetros para uma e duas populações. O teste para comparação de duas populações é baseado na estatística de logrank / In several applications, we want to analyze the behavior of multinomial datas over the time and its relationship with important factors. The classic methods commonly used for multinomial regression models are based in the generalized linear model framework. However, this models presents some disadvantages such that: it does not admit the incidence of zeros in any category, the assumption of proportionality of odds ratio and the fact that they are not appropriate models to analyze censored data. For multinomial data analyses with this characteristics, we propose a model that it is an extension of the multiplicative intensity model developed by Aalen to random multinomial variables. Therefore, instead of modeling the categorical probabilities, as in the classics methods, we modeled the intensity fuction associated with the multinomial variable. Using the martingale criterion, we estimate the models parameters and propose hypothesis testing for these parameters for one and two populations. The test for comparing two populations is based in the logrank statistics

信用風險對銀行、債券發行者及債券投資者而言是個很重要的考量，因此信用風險的管理成為一個很重要的課題。但管理信用風險的傳統方法，對控制信用風險都只能解決部分的問題。信用衍生性商品便應運而生。 評價信用衍生性商品的首要工作為對信用風險予以衡量及評價。本文採用違約強度模型評價信用風險並將其應用至信用價差選擇權的評價，試圖提供信用價差選擇權的合理價值及該評價公式在現實生活的可行性，並討論相關變數變動對信用價差選擇權價值的影響。 / Credit risk is an important consideration for banks, bond issuers, and bond investors. The conventional methods of managing credit risk, such as diversification, bank loan sales, and asset securitization, offer only a partial solution to controlling credit risk exposure. In recent years, the growing market for credit derivatives has provided powerful new tools for managing credit risk that can be less costly and more effective than traditional methods. How to measure and value credit risk is the main task of credit derivatives. The present study adopts an intensity model to value credit risk and applies this approach to price credit spread options. This study provides the reasonable premium for credit spread options and the practice of the pricing formula in the real world. It also covers the effects of the put premium for credit spread concerning the related variables.

Submitted by Guilherme Candido (gui0488@hotmail.com) on 2018-03-07T00:37:23Z No. of bitstreams: 1 Dissertação - Guilherme Amaral Candido.pdf: 2626690 bytes, checksum: 1e894027eeaf3360d910fb69a4a1f0b2 (MD5) / Approved for entry into archive by Thais Oliveira (thais.oliveira@fgv.br) on 2018-03-07T23:11:03Z (GMT) No. of bitstreams: 1 Dissertação - Guilherme Amaral Candido.pdf: 2626690 bytes, checksum: 1e894027eeaf3360d910fb69a4a1f0b2 (MD5) / Made available in DSpace on 2018-03-08T13:03:44Z (GMT). No. of bitstreams: 1 Dissertação - Guilherme Amaral Candido.pdf: 2626690 bytes, checksum: 1e894027eeaf3360d910fb69a4a1f0b2 (MD5) Previous issue date: 2018-02-07 / Extensa literatura existe acerca de apreçamento de derivativos de crédito, em especial Credit Default Swaps, porém pouco foi discutido sobre o caso peculiar brasileiro, com convenções de taxas de juros e legislação específicas. Este trabalho foca na implementação de um modelo de intensidade, em particular o modelo padrão da ISDA, adaptado à um contrato de CDS no Brasil sobre um emissor corporativo. Spreads de Credit Default Swaps negociados no mercado offshore, yields de bonds e yields de debêntures foram utilizados como insumos para obtenção das taxas implícitas de intensidade de default e backtesting do modelo. Os dados utilizados compreendem o período de 2015 a 2017, englobando momentos de estresse relacionados à crise política brasileira. Algumas aplicações são, então, apresentadas, entre elas hedging, basis trading e estruturação de Credit Linked Notes. / Extensive literature exists on the pricing of credit derivatives, particularly Credit Default Swaps, yet little has been discussed about the distinctive Brazilian case, with specific legislation and interest rate conventions. This work aims to implement an intensity model, in particular the standard ISDA model, adapted to a CDS contract in Brazil on a corporate issuer. Spreads of Credit Default Swaps traded in the offshore market, offshore bond yields and local bond yields were used as inputs for obtaining the implicit hazard rates and for back testing the model. The data used cover the period from 2015 to 2017, including relevant moments of stress related to the Brazilian political crisis. Some applications are then presented, including hedging, basis trading and Credit Linked Notes structuring.

In this paper, Monte Carlo simulation for CCR (Counterparty Credit Risk) modeling is investigated. A jump-diffusion model, Bates' model, is used to describe the price process of an asset, and the counterparty default probability is described by a stochastic intensity model with constant intensity. In combination with Monte Carlo simulation, the variance reduction technique importance sampling is used in an attempt to make the simulations more efficient. Importance sampling is used for simulation of both the asset price and, for CVA (Credit Valuation Adjustment) estimation, the default time. CVA is simulated for both European and Bermudan options. It is shown that a significant variance reduction can be achieved by utilizing importance sampling for asset price simulations. It is also shown that a significant variance reduction for CVA simulation can be achieved for counterparties with small default probabilities by employing importance sampling for the default times. This holds for both European and Bermudan options. Furthermore, the regression based method least squares Monte Carlo is used to estimate the price of a Bermudan option, resulting in CVA estimates that lie within an interval of feasible values. Finally, some topics of further research are suggested. / I denna rapport undersöks Monte Carlo-simuleringar för motpartskreditrisk. En jump-diffusion-modell, Bates modell, används för att beskriva prisprocessen hos en tillgång, och sannolikheten att motparten drabbas av insolvens beskrivs av en stokastisk intensitetsmodell med konstant intensitet. Tillsammans med Monte Carlo-simuleringar används variansreduktionstekinken importance sampling i ett försök att effektivisera simuleringarna. Importance sampling används för simulering av både tillgångens pris och, för estimering av CVA (Credit Valuation Adjustment), tidpunkten för insolvens. CVA simuleras för både europeiska optioner och Bermuda-optioner. Det visas att en signifikant variansreduktion kan uppnås genom att använda importance sampling för simuleringen av tillgångens pris. Det visas även att en signifikant variansreduktion för CVA-simulering kan uppnås för motparter med små sannolikheter att drabbas av insolvens genom att använda importance sampling för simulering av tidpunkter för insolvens. Detta gäller både europeiska optioner och Bermuda-optioner. Vidare, används regressionsmetoden least squares Monte Carlo för att estimera priset av en Bermuda-option, vilket resulterar i CVA-estimat som ligger inom ett intervall av rimliga värden. Slutligen föreslås några ämnen för ytterligare forskning.