Within Central Counterparty Clearing, the Clearing House collects Initial Margin from its Clearing Members. The Initial Margin can be calculated in many ways, one of which is by applying the commonly used risk measure Value-at-Risk. However, Value-at-Risk has one major flaw, namely its inability to encapsulate Tail Risk. Due to this, there has for long been a desire to replace Value-at-Risk with Expected Shortfall, another risk measure that has shown to be much better suited to encapsulate Tail Risk. That said, Value-at-Risk is still used over Expected Shortfall, something which is mainly due to the fact that there is no consensus regarding how one should backtest Expected Shortfall. The goal of this thesis is to evaluate some of the most commonly proposed methods for backtesting Expected Shortfall. In doing this, several non-parametric backtests of Expected Shortfall are investigated using simulated data as well as market data from different types of securities. Moreover, this thesis aims to shed some light on the differences between Value-at-Risk and Expected Shortfall, highlighting why a change of risk measure is not as straightforward as one might believe. From the investigations of the thesis, several backtests are found to be sufficient for backtesting the Initial Margin with Expected Shortfall as the risk measure, the so called Minimally Biased Relative backtest showing the overall best performance of the looked at backtests. Further, the thesis visualizes how Value-at-Risk and Expected Shortfall are two risk measures that are inherently different in a real-world setting, emphasizing how one should be careful making conversions between the two based upon parametric assumptions.

No / Risks exist in all aspects of our lives. Using data in both Scopus and ISI Web of Science, this review paper identifies pioneer work and pioneer scholars in enterprise risk management (ERM). Being ranked the first based on the review data, Desheng Wu has been active in this area by serving as a good academic network manager on the global research network, His global efforts with diverse networking have enabled him to publish outstanding papers in the field of ERM. Therefore, this paper also conducts a literature review of his papers and critical analysis of the work of Wu and Olson, from the perspective of the ERM, to glean implications and suggestions for the optimization and customization of the ERM. / NFSC grant (Grant # 71471055), the 100-Talents plan Program at Chinese Academy of Sciences and 1000-Talents plan Program for the Young Scientists.

The 2007 financial crisis highlighted the severe risks posed by counterparty defaults in financial markets. Assessing and addressing counterparty credit risk has consequently been a focal point of new regulations introduced in the wake of the crisis. The Central Clearing Counterparty (CCP) is at the heart of the solution, an entity dedicated to managing and mitigating counterparty risk in a market. CPPs manage risk by collecting collateral, referred to as margin, from the participants trading on the market. Appropriately sizing the margin is of utmost importance for the CCP to maintain the integrity of its operation and, by extension, protect the participants in the market. Most contemporary margin methodologies require significant resources which precludes frequent margin updates. In light of this issue, our work examines the capability of replicating the popular margin methodology Historical Simulation Value at Risk using machine-learning-based methods envisioning that an adequate such model could be used as a complement to the traditional model, providing real-time margin estimations. The experiment concerns portfolios containing stocks, bonds, and options and uses static market data and scenarios. We conclude that neither of the ensemble methods are sufficiently accurate, while both of the neural network-based models show moderate promise, warranting further development.

台灣壽險業的利差損問題持續存在，但若想要進一步開放新投資項目，應先檢視新投資工具之特性以及研究對應之保險監理規範之修訂。 本研究針對國外另類投資進行實證分析，考慮風險與報酬之間的抵換關係(Trade-Off)，以Rockafeller and Uryasev (2000)以及Campbell,Huisman and Koedijk (2001)提出之投資組合模型，建立平均值-風險 值(Mean-Value-at-Risk)之 效 率 前 緣 和 平 均 值-條 件 風 險 值(MeanConditional Value-at-Risk)之效率前緣，探討另類投資對投資組合效率的影響，並檢視相關保險監理規範的適宜性。 實證結果顯示不同資產類別(Assets Class)之間的相關性低，加入另類投資的標的能夠提升投資組合的效率，因此建議可以開放一些另類投資的項目，或是設定門檻進行監理。 / Recently, many insurance companies in Taiwan increased their investments in foreign countries substantially due to the inadequacy of domestic investment markets. Some insurers started or have been preparing to invest in emerging alternative investment tools such as private equity funds and hedge funds. However,there is a trade-off between return and risk. In this study we utilized the methods developed by Rockafeller and Uryasev (2000) and Campbell, Huisman, and Koedijk (2001) to conduct risk-return analyses for the insurance companies who are interested in alternative investments. Our approach extends the traditional Mean-Variance approach by introducing value at risk (VaR) and conditional VaR as risk measures. We found that the correlations among asset classes were low and alternative investments could enhance the investment efficiency of insurance companies. We suggest loosening some regulations accordingly.

Diploma thesis "Optimization capital charges in VaR model utilizing dynamic risk management strategies" deals with banks opportunity to reduce Basel capital requirements via estimation volatility in VaR model for separate time periods differently. It analyses current crisis, its sources, process, but especially its influence of new worldwide accepted regulatory standards, which require nearly doubled regulatory capital. Regarding high impact to industry return on equity the thesis discusses the possibility of dynamic capital optimization based on alternating conservative and aggressive risk management strategies. Empirical part of thesis tests outcomes of volatility modeling based on historical quotes of six European indexes since 2003, which are classified by volatility levels and broken down into several time periods. We suggest approach which enables financial institutions to reduce the impact of new Basel rules on their ROE, while they meet all VaR model conditions defined by the regulator. However, there are also negative consequences of this lowering level of capital represented by increasing failure rates of models. Although banks are able by suggested approach to achieve capital reduction by 20 percent, they are in the same time forced to use one of a very aggressive strategies. Dynamic...

[pt] A reestruturação do setor de energia elétrica, iniciada nos anos 90, teve como uma de suas principais implicações a introdução da competição na atividade de geração. A expansão do parque gerador, necessária para garantir o equilíbrio estrutural entre oferta e demanda, é estimulada por contratos de longo prazo negociados em leilões, na modalidade de menor tarifa. Destarte, o investidor deve oferecer um limite de preço para que o seu projeto seja competitivo (de forma a ganhar a licitação), mas que ao mesmo tempo seja suficiente para remunerar seu investimento, custos de operação e, sobretudo, protegê-lo contra todos os riscos intrínsecos ao projeto. Nesse contexto, as duas principais contribuições do presente trabalho são: (i) a proposição de uma metodologia de precificação de riscos, utilizando o critério do Value at Risk (VaR), que indica a máxima perda admitida pelo invetidor avesso a risco, com um determinado nível de confiança, e (ii) a aplicação de diferentes modelos de seleção de carteiras, que incorporam o critério do VaR para otimizar um portfolio com diferentes tecnologias de geração de energia. Os resultados da precificação de riscos são úteis para determinar os componentes críticos do projeto e calcular a competitividade (preço) de cada tecnologia. A aplicação de diferentes métodos de seleção de carteiras busca determinar o modelo mais indicado para o perfil das distribuições de retorno dos projetos de geração, que apresentam assimetria e curtose elevada (caldas pesadas). / [en] The new structure of the brazilian electric sector, consolidated by the end of the 90s main implication the introduction of competition in the power generation activity. The expansion of generation capacity, responsible to ensure structural equilibrium between supply and demand, is stimulated by long-term contracts negotiated through energy auctions. Therefore, the investor must give a competitive price (in order to win the auction), but also sufficient to pay his investment, operational costs and, especially, protect him against all project risks. In this role, the two main contributions of this work are: (i) to suggest a methodology of risk pricing, using the Value at Risk (VaR) criterium, which gives the maximum loss admitted by the risk averse investor, with a specified confidence level, and (ii) to apply different portfolio selection models, which incorporates the VaR criterium to optimize a portfolio with different power generation technologies. The risk pricing results are usefull to determine the project critical components and to calculate the competitiviness (price) of each technology. The study of different portfolio selection methods aims to investigate the most suitable model for the return distribution shape, characterized by having assimetry and curtosis (heavy tails).

Cette thèse porte sur la prédiction de la détresse financière et son impact sur le rendement des actions. L’objet principal de cette thèse est de : (i) prédire la détresse financière des petites et moyennes entreprises françaises en utilisant plusieurs spécifications économétriques tels que, le modèle Logit, les réseaux de neurones artificiels, la méthode SVM et la régression des moindres carrés partiels, et (ii) d’identifier les facteurs de risque de détresse financière à caractère systématique, explicatifs des rendements des actions, et additionnels au modèle de Fama et French (1993) tels que le momentum, la détresse relative, la liquidité et la Value-at-Risk, sur le marché boursier Français. Cette étude comporte deux parties. La première partie, composée de 2 chapitres, s’interroge sur les principaux indicateurs discriminants entre les petites et moyennes entreprises françaises saines et celles en détresse financière un an et deux ans avant la défaillance. Elle mobilise différentes approches de prédiction et aboutit à des résultats empiriques qui font l’objet d’analyse. La deuxième partie, composée aussi de 2 chapitres, étudie le pouvoir explicatif, du modèle de Fama et French (1993) augmenté de certains facteurs de risque, mais aussi des modèles alternatifs à cette approche dans le contexte français. Les tests portent aussi sur le caractère systématique des facteurs de risque additionnels ou alternatifs, explicatifs des rendements des actions. Les résultats empiriques obtenus font l’objet d’analyse et permettent de proposer des implications managériales aux décideurs. / This thesis focuses on financial distress and its impact on stock returns. The main goal of this dissertation is: (i) to predict the financial distress of French small and medium-sized firms using a number of techniques namely Logit model, Artificial Neural Networks, Support Vector Machine techniques, and Partial Least Squares, and (ii) to identify the systematic risk factors of financial distress that can explain stock returns, in addition to those of Fama and French (1993) such as the momentum, the relative distress, the liquidity, and the Value-at-Risk in the French stock market. This study has been concretized in two parts. The first part, composed of 2 chapters, wonders about the main indicators that can discriminate between distressed and non-distressed French small and medium-sized firms one and two years before default. It mobilizes different prediction techniques and leads to the empirical results that are the subject of the analysis. The second part, composed also of 2 chapters, investigates the explanatory power of Fama and French (1993) model augmented by a number of risk factors, as well as alternative models in the French context. The tests also focus on the systematic nature of the additional or alternative risk factors, explaining the stock returns. The obtained empirical results are analyzed and propose managerial implications to decision makers.

Made available in DSpace on 2016-03-15T19:25:23Z (GMT). No. of bitstreams: 1 Arthur Monteiro Gabbay.pdf: 425008 bytes, checksum: 1824b9dbd4b1080b887305933b95be36 (MD5) Previous issue date: 2010-08-11 / Fundo Mackenzie de Pesquisa / Many authors consider Operational Risk as a key variable for maintaining the balance of the global financial market. The objective of this dissertation is to study the development of a Advanced Measurement Approach (AMA), specifically the Loss Distribution Approach (LDA) on a database of actual operational losses. Being more specifically, this study promotes an analysis about the results and possible limitations related to the implementation of the model. To achieve these goals, it is needed to discuss the definitions of Operational Risk, Monte Carlo Simulation and value-at-risk (VaR), considering that these concepts are crucial to the implementation of the LDA. / O risco operacional é considerado por muitos autores uma variável determinante para a manutenção do equilíbrio do mercado financeiro global. O objetivo desta dissertação é estudar o desenvolvimento de uma modelo de Abordagem de Mensuração Avançada (AMA),mais especificamente a Loss Distribution Approach (LDA), sobre um banco de dados reais de perdas operacionais. Mais especificamente este estudo promove uma análise sobre os resultados e sobre eventuais limitações relacionadas à aplicação do modelo. Para realização destes objetivos, abordam-se as definições do risco operacional, simulação de Monte Carlo e value-at-risk (VaR), haja vista que estes são conceitos cruciais para a aplicação do LDA.

Value at Risk (VaR) and Expected Shortfall (ES) are methods often used to measure market risk. Inaccurate and unreliable Value at Risk and Expected Shortfall models can lead to underestimation of the market risk that a firm or financial institution is exposed to, and therefore may jeopardize the well-being or survival of the firm or financial institution during adverse markets. The objective of this study is therefore to examine various Value at Risk and Expected Shortfall models, including fatter tail models, in order to analyze the accuracy and reliability of these models. Thirteen VaR and ES models under three main approaches (Parametric, Non-Parametric and Semi-Parametric) are examined in this study. The results of this study show that the proposed model (ARMA(1,1)-GJR-GARCH(1,1)-SGED) gives the most balanced Value at Risk results. The semi-parametric model (Extreme Value Theory, EVT) is the most accurate Value at Risk model in this study for S&P 500. / October 2014

La libéralisation des échanges, le développement des moyens de transport de marchandises à faible coût et l’essor économique des pays émergents font de la globalisation (mondialisation) des chaînes logistiques un phénomène irréversible. Si ces chaines globalisées permettent de réduire les coûts, en contrepartie, elles multiplient les risques de rupture depuis la phase d’approvisionnement jusqu’à la phase finale de distribution. Dans cette thèse, nous nous focalisons sur la phase amont. Nous traitons plus spécifiquement le cas d’une centrale d’achat devant sélectionner des fournisseurs et allouer les commandes aux fournisseurs retenus. Chacun des fournisseurs risque de ne pas livrer ses commandes pour des raisons qui lui sont propres (problèmes internes, mauvaise qualité) ou externes (catastrophe naturelle, problèmes de transport). Selon que les fournisseurs sélectionnés livrent ou non leurs commandes, l’opération dégagera un profit ou sera déficitaire. L’objectif de cette thèse, est de fournir des outils d’aide à la décision à un décideur confronté à ce problème tout en prenant en compte le comportement du dit décideur face au risque. Des programmes stochastiques en nombre entiers mixtes ont été proposés pour modéliser ce problème. La première partie du travail porte sur l’élaboration d’un outil visuel d’aide à la décision permettant à un décideur de trouver une solution maximisant le profit espéré pour un risque de perte fixé. La deuxième partie applique les techniques d’estimation et de quantification du risque VAR et CVaR à ce problème. L’objectif est d’aider un décideur qui vise à minimiser la valeur de l’espérance du coût (utilisation de VaR) ou à minimiser la valeur de l’espérance du coût dans le pire des cas (utilisation de VAR et CVaR). Selon nos résultats, il apparaît que le décideur doit prendre en compte les différents scénarios possibles quelque soit leurs probabilités de réalisation, pour que la décision soit efficace. / Trade liberalization, the development of mean of transport and the development economic of emerging countries which lead to globalization of supply chain is irreversible phenomen. They can reduce costs, in return, they multiply the risk of disruption from upstream stage to downstream stage. In this thesis, we focus on the inbound supply chain stage. We treat more specifically the case of a purchasing central to select suppliers and allocate the orders. Each of the suppliers cannot deliver its orders due to internal reasons (poor quality problems) or external reasons (natural disasters, transport problems). According to the selected suppliers deliver their orders or not, the transaction operation will generate a profit or loss. The objective of this thesis is to provide decision support tools to a decision maker faced with this problem by taking into account the behavior of decision maker toward risk. We proposed stochastic mixed integer linear programs to model this problem. In the first part, we focuses on the development of a decision support visual tool that allows a decision maker to find a compromise between maximizing the expected profit and minimize the risk of loss. In the second part, we integrated the techniques of estimation of risk VaR and CVaR in this problem. The objective is to help decision maker to minimize the expected cost and minimize the conditional value at risk simultanously via calculating of VaR. Result shows that the decision maker must tack into account the different scenarios of disruption regardless their probability of realisation.