一、研究動機與目的 由於國際經濟體系日趨複雜，持有資產的不確定性因而增加，投資者為了避免因為資 產報酬過大的波動而造成損失，紛紛尋求迴避風險的工具。而期貨由於具備了高度流 動性，融通功能的保證金制度及公正的中介機構等優點，使其產品種類及交易量日益 擴大，提供了金融資產持有者良好的避險管道。 本研究探討金融性期貨商品在各種避險期間長度及不同到期日的期貨契約，降低風險 的程度是否有差異，並就各避險策略理論，比較其績效。 二、研究期間與樣本。 本研究由華爾街日報及偷敦金融時報抄錄由1988年 1月到1990年1 月共108 週，每週 三金融性商品現貨及期貨收盤價格。包括黃金、英鎊、日圓、西德馬克、瑞士法郎及 S & P 500 NYSE股價指數和T-Bill Euro Dollar利率等九種。 三、研究方法。 主要比較以下三種避險策略降低風險的程度，並研究以期貨避險時，是否愈早簽訂契 約或選擇到期日距今較遠的契約愈能降低風險。 1.天真法則 (Naive Approch) 該策略假設任何資產的現貨與期貨價格變動方向一致且幅度相同。於是為了避免資產 因為價格波動造成損失，投資者的避險策略應該是分別持有數量相同但方向相反的現 貨與期貨部位(position)。如此現貨資產與期貨資產的損益可完全抵消，若不計交易 成本，則造成損失的可能性為零。 2.最小變異數法則 (Minimum Variance Approach) 該法則認為，現貨與期貨價格同方向且等幅度變動的假設並不合理，而將現貨與期貨 所持有的部位視為資產組合 (portfolio)，此資產組合價格的變異數視為風險；求出 使該資產組合風險最小的期貨部位。期貨相對現貨的持有比值就是最適避險比率，以 此比率構成資產組合風險最小。 3.風險迴避法則(Risk Aversion Approach) 該法則引用普雷特－亞羅(Pratt-Arrow) 絕對風險迴避的觀念，尋求報酬和風險間的 替代關係，在報酬不為負的要求下，求出使資產組合風險最小的避險比率。此法則由 於衡量的標準更為嚴格，故計算亦較繁複。

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Made available in DSpace on 2010-04-20T21:00:18Z (GMT). No. of bitstreams: 3 martincasalsturma2003.pdf.jpg: 11517 bytes, checksum: 930c75c74ff8269d877983110854646d (MD5) martincasalsturma2003.pdf: 975293 bytes, checksum: f41cfd3a5f3e659d07e2861acf4e23d4 (MD5) martincasalsturma2003.pdf.txt: 107784 bytes, checksum: e96ad0fb809a12f13ba7d3f08e24c1ee (MD5) Previous issue date: 2006-02-15T00:00:00Z / O objetivo deste trabalho é analisar a alocação de investimentos no mercado acionário brasileiro, utilizando a teoria do prospecto de Tversky e Kahneman (1979) e o conceito de Aversão a Perdas Míope (Myopic Loss Aversion) proposto por Benartzi e Thaler (1995). Foram levantados através de experimento de laboratório os parâmetros da função de valor e da função de ponderação de probabilidades da teoria do prospecto e foi verificada a alocação de investimentos entre ações e renda fixa que maximizam a utilidade. Chegamos à conclusão que o total de recursos atualmente direcionados ao mercado de ações no Brasil, que é de aproximadamente 2,7% para pessoas físicas e de 6,0% para pessoas jurídicas, é compatível com a teoria do prospecto. / The objective of this study is to analyze the investment allocation in the Brazilian stock market, using Tversky and Kahneman’s prospect theory (1979) and the concept of myopic loss aversion proposed by Benartzi and Thaler (1995). We run a laboratory experiment to obtain the parameters of the value function and the probability weighting function of the prospect theory and identify the allocation that maximizes utility in the Brazilian Market We conclude that the actual allocation of investment in the stock market, of around 2.7% for individuals and around 6% for all the segments, is in accordance with the prospect theory.

Cette thèse s'inscrit dans le domaine de la prise de décision séquentielle en environnement inconnu, et plus particulièrement dans le cadre des bandits manchots (multi-armed bandits, MAB), défini par Robbins et Lai dans les années 50. Depuis les années 2000, ce cadre a fait l'objet de nombreuses recherches théoriques et algorithmiques centrées sur le compromis entre l'exploration et l'exploitation : L'exploitation consiste à répéter le plus souvent possible les choix qui se sont avérés les meilleurs jusqu'à présent. L'exploration consiste à essayer des choix qui ont rarement été essayés, pour vérifier qu'on a bien identifié les meilleurs choix. Les applications des approches MAB vont du choix des traitements médicaux à la recommandation dans le contexte du commerce électronique, en passant par la recherche de politiques optimales de l'énergie. Les contributions présentées dans ce manuscrit s'intéressent au compromis exploration vs exploitation sous deux angles spécifiques. Le premier concerne la prise en compte du risque. Toute exploration dans un contexte inconnu peut en effet aboutir à des conséquences indésirables ; par exemple l'exploration des comportements d'un robot peut aboutir à des dommages pour le robot ou pour son environnement. Dans ce contexte, l'objectif est d'obtenir un compromis entre exploration, exploitation, et prise de risque (EER). Plusieurs algorithmes originaux sont proposés dans le cadre du compromis EER. Sous des hypothèses fortes, l'algorithme MIN offre des garanties de regret logarithmique, à l'état de l'art ; il offre également une grande robustesse, contrastant avec la forte sensibilité aux valeurs des hyper-paramètres de e.g. (Auer et al. 2002). L'algorithme MARAB s'intéresse à un critère inspiré de la littérature économique(Conditional Value at Risk), et montre d'excellentes performances empiriques comparées à (Sani et al. 2012), mais sans garanties théoriques. Enfin, l'algorithme MARABOUT modifie l'estimation du critère CVaR pour obtenir des garanties théoriques, tout en obtenant un bon comportement empirique. Le second axe de recherche concerne le bandit contextuel, où l'on dispose d'informations additionnelles relatives au contexte de la décision ; par exemple, les variables d'état du patient dans un contexte médical ou de l'utilisateur dans un contexte de recommandation. L'étude se focalise sur le choix entre bras qu'on a tirés précédemment un nombre de fois différent. Le choix repose en général sur la notion d'optimisme, comparant les bornes supérieures des intervalles de confiance associés aux bras considérés. Une autre approche appelée BESA, reposant sur le sous-échantillonnage des valeurs tirées pour les bras les plus visités, et permettant ainsi de se ramener au cas où tous les bras ont été tirés un même nombre de fois, a été proposée par (Baransi et al. 2014). / This thesis focuses on sequential decision making in unknown environment, and more particularly on the Multi-Armed Bandit (MAB) setting, defined by Lai and Robbins in the 50s. During the last decade, many theoretical and algorithmic studies have been aimed at cthe exploration vs exploitation tradeoff at the core of MABs, where Exploitation is biased toward the best options visited so far while Exploration is biased toward options rarely visited, to enforce the discovery of the the true best choices. MAB applications range from medicine (the elicitation of the best prescriptions) to e-commerce (recommendations, advertisements) and optimal policies (e.g., in the energy domain). The contributions presented in this dissertation tackle the exploration vs exploitation dilemma under two angles. The first contribution is centered on risk avoidance. Exploration in unknown environments often has adverse effects: for instance exploratory trajectories of a robot can entail physical damages for the robot or its environment. We thus define the exploration vs exploitation vs safety (EES) tradeoff, and propose three new algorithms addressing the EES dilemma. Firstly and under strong assumptions, the MIN algorithm provides a robust behavior with guarantees of logarithmic regret, matching the state of the art with a high robustness w.r.t. hyper-parameter setting (as opposed to, e.g. UCB (Auer 2002)). Secondly, the MARAB algorithm aims at optimizing the cumulative 'Conditional Value at Risk' (CVar) rewards, originated from the economics domain, with excellent empirical performances compared to (Sani et al. 2012), though without any theoretical guarantees. Finally, the MARABOUT algorithm modifies the CVar estimation and yields both theoretical guarantees and a good empirical behavior. The second contribution concerns the contextual bandit setting, where additional informations are provided to support the decision making, such as the user details in the ontent recommendation domain, or the patient history in the medical domain. The study focuses on how to make a choice between two arms with different numbers of samples. Traditionally, a confidence region is derived for each arm based on the associated samples, and the 'Optimism in front of the unknown' principle implements the choice of the arm with maximal upper confidence bound. An alternative, pioneered by (Baransi et al. 2014), and called BESA, proceeds instead by subsampling without replacement the larger sample set. In this framework, we designed a contextual bandit algorithm based on sub-sampling without replacement, relaxing the (unrealistic) assumption that all arm reward distributions rely on the same parameter. The CL-BESA algorithm yields both theoretical guarantees of logarithmic regret and good empirical behavior.

[pt] Finanças Corporativas tem como objetivo encontrar a política de investimentos e financiamentos que maximize o valor para o acionista. Baseada no modelo estático de Modigliani e Miller, a literatura recente apresenta modelos dinâmicos que buscam maior aderência à realidade. No entanto, para obter uma metodologia de solução computacionalmente tratável, duas simplificações são usualmente adotadas: (i) agentes financeiros são neutros a risco; (ii) custo de financiamento são fixos e independentes da alavancagem da empresa. Neste trabalho, é proposto um modelo de programação dinâmica estocástica para a determinação da política ótima de investimentos e financiamentos considerando acionistas avessos a risco e empresas que enfrentam incerteza na receita e custos marginais de financiamentos não-decrescentes com o nível de alavancagem da empresa. O modelo proposto é resolvido de maneira eficiente utilizando o algoritmo de Programação Dinâmica Dual Estocástica. Ao final do trabalho, são realizados estudos empíricos e análises de sensibilidade para melhor compreensão das políticas de investimentos e financiamentos das corporações. / [en] Corporate Finance is the study of investment and financing policies in order to maximize shareholder value. Based on the static model of Modigliani and Miller, recent literature presents dynamic models that seek greater adherence to reality. However, to obtain a computationally treatable solution methodology, two simplifications are usually adopted: (i) financial agents are risk neutral; (ii) cost of financing is static and independent of the company s leverage. In this work, a dynamic stochastic programming model is proposed to determine the optimum investment and financing policy, considering risk-averse shareholders and companies that face uncertainty on income and non-decreasing marginal costs of financing. The proposed model is efficiently solved using the Stochastic Dual Dynamic Programming algorithm. At the end of the study, empirical studies and sensitivity analyzes are carried out to the better understanding of corporate investment and financing policies.

Nombreux sont ceux à considérer que depuis le développement de la médecine curative, la prévention a occupé une place secondaire dans le système de santé français. La préoccupation majeure aurait été jusque-là d’assurer un accès aux soins plutôt que de favoriser une culture de la prévention. Depuis quelques années, les différents drames sanitaires (transfusion sanguine, amiante, canicule, hormone de croissance, épidémies de grippe, cancers,...) ont sensibilisé l’opinion à la notion de “sécurité sanitaire” et fait émerger une prise de conscience nouvelle autour des problématiques de la prévention. Le recours à la prévention permet aux individus et aux pouvoirs publics d’exercer un contrôle sur les risques de santé auxquels ils sont exposés et de mener des actions conséquentes dans le but d’améliorer l’état de santé en évitant l’apparition, le développement ou l’aggravation des maladies ou des accidents tout en favorisant des comportements individuels et collectifs pouvant contribuer à réduire les risques sanitaires. Une des réponses face aux risques de santé est d’inciter les individus à plus de prévention car ils ne sont plus seulement consommateurs de soins mais aussi producteurs de leur état de santé. Quel est donc le rôle des individus et quelle est la part de responsabilité dévolue à chacun dans la prévention des risques sanitaires ? De plus, la prévention des risques sanitaires s’inscrit dans un environnement d’ambiguïté et d’incertitudes car les risques auxquels sont exposés les individus sont diversement nombreux et pas toujours bien connus. Il n’est donc pas aisé de relier avec certitude un facteur de risque et un effet sanitaire pour ainsi adopter un comportement de prévention adéquat. Dans ce contexte d’incertitude, de nombreux modèles d’aide à la décision, ou de représentations des préférences ont été proposés ces dernières années (Klibanoff et al.(2005), Bleichrodt et Eeckhoudt(2006) Machina(2009), Etner et al.(2011)). Cette thèse analyse les comportements de prévention des individus face à des risques de santé tout en mettant l’accent sur les politiques publiques de prévention proposées. Elle consiste d’une part à des études théoriques des comportements de prévention et de gestion des risques sanitaires en utilisant des modèles récents de préférences. Ce travail analyse le comportement des individus qui doivent prendre des mesures de prévention pour protéger leur propre santé dans un contexte d’incertitude. D’autre part, elle se consacre à une étude empirique pour cerner les perceptions et informations qu’ont les individus en termes de risque de santé. En outre, tout au long de ce travail, nous avons cherché à étudier la pertinence du modèle théorique élaboré au regard des politiques pratiquées. Le premier chapitre présente les principes de modélisation des décisions économiques en présence d’un risque de santé plus ou moins bien connu. Après avoir détaillé lesdifférentes approches dans les modèles de décisions dans le risque et dans l’incertain, nous avons mis en relief l’importance de l’introduction de variables bidimensionnelles (ou multidimensionnelles) dans le modèle de choix pour permettre de rendre de l’environnement multidimensionnel des risques de santé. Le deuxième chapitre est une étude originale proposée sur l’analyse de la prévention en santé lorsque les individus présentent de l’aversion à l’ambiguïté. Dans ce chapitre, nous avons étudié les comportements individuels de prévention face à une incertitude sur l’état de santé et avons montré que l’aversion à l’ambiguïté incite les individus à faire plus de prévention primaire et secondaire sous l’hypothèse d’une utilité marginale de la richesse croissante avec l’état de santé. (...) / Many are those to consider that since the development of the curative medicine, the prevention occupied a secondary place in the French health care system. Major concern would have been up to that point to ensure an access to healthcare rather than to support a culture of prevention. Since a few years, various medical dramas (blood transfusion, asbestos, heat wave, growth hormone, flu epidemics,cancers,...) have raised awareness of the concept of “safety” and brings out a new awakening around the prevention problems.The use of prevention allows the individuals and the public authorities to exert a control on the health risks to which they are exposed and to conduct consequent actions in order to improve health and prevent the emergence, the development, the development or the aggravation of the diseases or accidents while promoting individual and collective behaviors that can help to reduce the risk health. One of the answers in front of the health risks is to incite the individuals to more prevention because they are not only consumers of care, but also producers of their health. What is the role of individuals and what is the share of responsibility reserved for each one in the prevention of health risks ? In addition, the prevention of health risks is part of an environment ambiguity and uncertainty because the risks to which are exposed individuals are many different ways and not always well known. It is thus not easy to connect with certainty a risk factor and a health effect for adopting an adequate prevention behavior. In this context of uncertainty, many support the decision models or representations of preferences have been proposed in recent years (and Klibanoff (al. (2005), and Bleichrodt Eeckhoudt (2006), Machina 2009), Etner et al. (2011)).This thesis analyzes the individual behaviors of prevention in front of health risks while focusing on the public policies of prevention proposed. It consists on the one hand in theoretical studies of the behaviors of prevention and management of the health risks by using recent models of preferences. This work analyzes the behavior of the individuals who need to take preventive measures to protect their own health in a context of uncertainty. On the other hand, it is devoted to an empirical study to determine perceptions and information which have the individuals in terms of risk of health. Moreover, throughout this work, we sought to examine the relevance of the theoretical model developed with regard to the policies practiced. The first chapter presents the principles of modeling economic decisions in the presence of a more or less well known health risk. After detailing the different approaches in models of decisions under risk and uncertainty, we have highlighted the importance of the introduction of two-dimensional variables (or multidimensional) in the model of choice to allow to report the multidimensional environment of health risks. The second chapter is an original proposed study on the analysis of preventive health when the individuals have an aversion to ambiguity. In this chapter, we studied individual behavior of prevention in front of an uncertainty on the health status and have showed that aversion to ambiguity encourages the individuals to make more primary and secondary prevention under the assumption of a marginal utility of the increasing wealth with the health status. (...)

Bakgrund: År 2022 kantades av Rysslands invasion av Ukraina, börsnedgång, stigande inflation och styrräntor. Det bidrog till att allt fler sökte hjälp av finansiella rådgivare för att utifrån livssituationen få hjälp med att nå sina sparmål och maximera sin avkastning. I tidigare forskning råder det delade meningar kring om den finansiella rådgivaren faktiskt bidrar till positiva ekonomiska utfall hos kunden. Å andra sidan får den finansiella rådgivaren, åtminstone privat, kunskap till sig via sitt arbete som torde leda till en hög finansiell bildning. Huruvida det faktiskt bidrar till positiva ekonomiska utfall i den finansiella rådgivarens egna investeringsbeslut och sparande under 2022 leder således till frågan, om de kan hjälpa andra, kan de även hjälpa sig själva? Syfte: Studien syftar till att skapa en förståelse för hur finansiella rådgivares privata sparande och investeringsbeslut samvarierar med olika faktorer såsom livssituation, psykologiska bias och erfarenheter under 2022. Vidare ämnar studien utforska hur finansiella rådgivare ställer sig till ytterligare utbildning inom beteendeekonomi och huruvida de tror att det kan bidra till bättre finansiellt beslutsfattande. Metod: En kvalitativ metod har använts för att uppfylla studiens syfte. Tio finansiella rådgivare intervjuades genom semistrukturerade djupintervjuer. Slutsats: Studien finner att placering i livscykeln, psykologiska bias samt erfarenhet samvarierar med den finansiella rådgivarens privata investeringsbeslut och sparande under 2022. Placeringen i livscykeln samvarierar främst med riskaversionen, därutöver har de finansiella rådgivarna inte kunnat motstå fall av samtliga undersökta bias i studien. Erfarenheten samvarierar med en minskad benägenhet att falla offer för vissa psykologiska bias, förutom överkonfidens, där effekten snarare är den motsatta. Vidare anser de finansiella rådgivarna att ytterligare utbildning inom beteendeekonomi inte skulle vara värdeskapande för deras privata investeringsbeslut, samtidigt som de anser sig ha behov av det i sitt arbete. / Background: The year 2022 was characterized by the invasion of Ukraine, the downturn of the stock market, rising inflation and increases in the benchmark interest rate. This led to the increasing search for financial advisors who, using life circumstances, could assist the individual in reaching personal saving goals and maximizing returns on investments. In prior research, there are divided opinions about whether financial advisors contribute to positive financial outcomes for the client. The financial advisors, at least privately, gain knowledge through their work which should lead to a high level of financial literacy. Whether it contributes to positive financial outcomes in the financial advisor's own investment decisions and savings in 2022 thus leads to the question, if they can help others, can they also help themselves? Aim: The study aims to create an understanding of how financial advisers' private investments decisions and savings in 2022 have been affected by various factors such as life situation, psychological bias, and experiences. Furthermore, the study intends to explore financial advisers' perception of how further education in behavioral economics could have contributed to better financial decision-making. Method: A qualitative method has been used to fulfill the purpose of the study. Ten financial advisors were interviewed through semi-structured in-depth interviews. Conclusion: The study finds that placement in the life cycle, psychological bias, and experience had an impact on financial advisors’ private investment decisions and savings during 2022. The placement in the lifecycle primarily influences the risk aversion, while the financial advisors have not been able to withstand cases of all investigated biases in the study. Experience has contributed to mitigating the impact of psychological biases to some extent while also creating overconfidence. The financial advisors believe that additional education in behavioral economics would not add value to their private investment decisions, while they consider themselves to need it in their work.

We have examinined the problem of constructing efficient strategies for continuous-time dynamic asset allocation. In order to obtain efficient investment strategies; a stochastic optimal control approach was applied to find optimal transaction control. Two mathematical problems are formulized and studied: Model I; a dynamic programming approach that maximizes an isoelastic functional with respect to given underlying portfolio dynamics and Model II; a more sophisticated approach where a time-inconsistent state dependent mean-variance functional is considered. In contrast to the optimal controls for Model I, which are obtained by solving the Hamilton-Jacobi-Bellman (HJB) partial differential equation; the efficient strategies for Model II are constructed by attaining subgame perfect Nash equilibrium controls that satisfy the extended HJB equation, introduced by Björk et al. in [1]. Furthermore; comprehensive execution algorithms where designed with help from the generated results and several simulations are performed. The results reveal that optimality is obtained for Model I by holding a fix portfolio balance throughout the whole investment period and Model II suggests a continuous liquidation of the risky holdings as time evolves. A clear advantage of using Model II is concluded as it is far more efficient and actually takes time-inconsistency into consideration. / Vi har undersökt problemet som uppstår vid konstruktion av effektiva strategier för tidskontinuerlig dynamisk tillgångsallokering. Tillvägagångsättet för konstruktionen av strategierna har baserats på stokastisk optimal styrteori där optimal transaktionsstyrning beräknas. Två matematiska problem formulerades och betraktades: Modell I, en metod där dynamisk programmering används för att maximera en isoelastisk funktional med avseende på given underliggande portföljdynamik. Modell II, en mer sofistikerad metod som tar i beaktning en tidsinkonsistent och tillståndsberoende avvägning mellan förväntad avkastning och varians. Till skillnad från de optimala styrvariablerna för Modell I som satisfierar Hamilton-Jacobi-Bellmans (HJB) partiella differentialekvation, konstrueras de effektiva strategierna för Modell II genom att erhålla subgame perfekt Nashjämvikt. Dessa satisfierar den utökade HJB ekvationen som introduceras av Björk et al. i [1]. Vidare har övergripande exekveringsalgoritmer skapats med hjälp av resultaten och ett flertal simuleringar har producerats. Resultaten avslöjar att optimalitet för Modell I erhålls genom att hålla en fix portföljbalans mellan de riskfria och riskfyllda tillgångarna, genom hela investeringsperioden. Medan för Modell II föreslås en kontinuerlig likvidering av de riskfyllda tillgångarna i takt med, men inte proportionerligt mot, tidens gång. Slutsatsen är att det finns en tydlig fördel med användandet av Modell II eftersom att resultaten påvisar en påtagligt högre grad av effektivitet samt att modellen faktiskt tar hänsyn till tidsinkonsistens.

[pt] Nos últimos anos, observa-se crescente penetração da energia eólica na matriz energética mundial e brasileira. Em 2015, ela já representava (seis por cento) da capacidade total de geração de energia do país, colocando-o na (décima) posição entre os países com capacidade eólica instalada. A crescente penetração dessa fonte de energia e suas características de intermitência e forte sazonalidade, passaram a demandar modelos de otimização capazes de auxiliar tanto a gestão dos sistemas elétricos com geração intermitente de energia eólica, quanto a comercialização dessa energia. Avançaram, assim, os estudos de previsões de médias a cada (dez) minutos, horárias e diárias de geração eólica, para atender a sua inserção na programação dos sistemas elétricos e a sua comercialização em mercados diários e horários. Contudo, poucos estudos deram atenção à previsão e simulação de médias mensais de geração eólica, imprescindíveis para gestão e otimização da comercialização dessa energia no Brasil, visto que esta ocorre essencialmente em base mensal. Neste contexto, insere-se esta tese, que busca avaliar a otimização comercial de um parque eólico no mercado livre de energia brasileiro, considerando diferentes modelos de simulação da incerteza de geração eólica e níveis de aversão ao risco do gestor. Para representar diferentes níveis de aversão ao risco do gestor, desenvolveu-se uma nova função de preferência, capaz de modelar a variação do nível de aversão ao risco de um mesmo gestor, para diferentes faixas de preferência, definidas a partir de percentis αs de VaRα. A função de preferência desenvolvida é uma ponderação entre o valor esperado e níveis de CVaR dos resultados. De certo modo, ela altera as probabilidades dos resultados, de acordo as preferências do gestor, similar ao efeito dos pesos de decisão na Teoria do Prospecto. Para simulação da geração eólica são adotados modelos autorregressivos com sazonalidade representada por dummies mensais (ARX-11) e periódicos (PAR). Considera-se, ainda, a inclusão de variáveis climáticas exógenas no modelo ARX-11, com ganho de capacidade preditiva. Observou-se que, para um gestor neutro ao risco, as diferentes simulações de geração eólica não alteraram a decisão ótima. O mesmo não é válido para um gestor avesso ao risco, especialmente ao ser considerado o modelo de simulação com variáveis climáticas exógenas. Portanto, é importante a definição de um único modelo de simulação a ser considerado pelo gestor avesso ao risco ou, a adoção de alguma técnica multicritério para ponderação de diferentes modelos. O perfil de risco também altera as decisões ótimas do gestor, observando-se redução do desvio-padrão e da média da distribuição dos resultados e, aumento dos CVaRs e prêmio de risco, à medida que aumenta a aversão ao risco. Assim, é importante a especificação de uma única função de preferência, que represente adequadamente o perfil de risco do gestor ou da empresa, para otimização da comercialização. A flexibilidade da função de preferência desenvolvida, ao permitir a definição de diferentes níveis de aversão ao risco do gestor, para diferentes faixas de preferência, contribui para essa especificação. / [en] In recent years, we have seen an increased penetration of wind power in the Brazilian energy matrix and also worldwide. In 2015, wind power already accounted for (six percent) of the Brazilian total power capacity and the country was the (tenth) in the world raking of wind power installed capacity. Due to the growing penetration of the source, its intermittency and strong seasonality, optimization models able to deal with the management of wind power, both in electrical systems operation and in trading environment, are necessary. Thus, we see the growth in the number of studies concerned about wind power forecasts for every (10) minutes, hours and days, meeting the electrical systems and international trading schedules. However, few studies have given attention to the forecasting and simulation of wind power monthly averages, which are essential for the management and optimization of energy trading in Brazil, since its occurs essentially on a monthly basis. In this context, we introduce this thesis, which seeks to assess the commercial optimization of a wind farm in the Brazilian energy free market, considering different simulation models for the wind power production uncertainty and different levels of manager s risk aversion. In order to represent the manager s different levels of risk aversion, we developed a new preference function, which is able to model the variation of risk aversion level of the same manager, for different preference groups. These groups are defined by α s percentiles of VaRα. The developed preference function is a weighted average between expected value of results and CVaR levels. In a way, it changes the odds of the results, according to the manager s preference, similar to the effect of the decision weights on Prospect Theory. We adopted autoregressive models to simulate wind power generation, with seasonality represented by monthly dummies (ARX -11) or periodic model (PAR). Furthermore, we consider the inclusion of climate exogenous variables in the ARX-11 model and obtain predictive gain. We observed that for a risk neutral manager, different simulations of wind power production do not change the optimal decision. However, this does not apply for risk averse managers, especially when we consider the simulation model with climate exogenous variables. Therefore, it is important that the risk averse manager establishes a single simulation model to consider or adopts some multi-criteria technique for weighting different models. The risk profile also changes the manager optimal decision. We observed that increasing risk aversion, the standard deviation and mean of the results distribution decrease, while risk premium and CVaRs increase. Therefore, to proceed the optimization, it is important to specify a single preference function, which represents adequately the manager or company risk profile. The flexibility of the developed preference function, allowing the definition of different manager s risk aversion levels for different preference groups, contributes to this specification.

L'approche traditionnelle des produits dérivés consiste, sous certaines hypothèses bien définies, à construire des stratégies de couverture à risque strictement nul. Cependant,dans le cas général ces stratégies de couverture "parfaites" n'existent pas,et la théorie doit plutôt s'appuyer sur une idée de minimisation du risque. Dans ce cas, la couverture optimale dépend de la quantité du risque à minimiser. Dans lecadre des options, on considère dans ce travail une nouvelle mesure du risque vial'approche de l'utilité espérée qui tient compte, à la fois, du moment d'ordre quatre,qui est plus sensible aux grandes fluctuations que la variance, et de l'aversion aurisque de l'émetteur d'une option vis-à-vis au risque. Comparée à la couverture endelta, à l'optimisation de la variance et l'optimisation du moment d'ordre quatre,la stratégie de couverture, via l'approche de l'utilité espérée, permet de diminuer lasensibilité de la couverture par rapport au cours du sous-jacent. Ceci est de natureà réduire les coûts des transactions associées / The traditional approach of derivatives involves, under certain clearly defined hypothesis, to construct hedging strategies for strictly zero risk. However, in the general case these perfect hedging strategies do not exist, and the theory must be rather based on the idea of risk minimization. In this case, the optimal hedging strategy depends on the amount of risk to be minimized. Under the options approach, we consider here a new measure of risk via the expected utility approach that takes into account both, the moment of order four, which is more sensitive to fluctuations than large variance, and risk aversion of the investor of an option towards risk. Compared to delta hedging, optimization of the variance and maximizing the moment of order four, the hedging strategy, via the expected utilitiy approach, reduces the sensitivy of the hedging approach reported in the underlying asset price. This is likely to reduce the associated transaction costs.