915 resultados para Conditional volatility
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This paper applies two measures to assess spillovers across markets: the Diebold Yilmaz (2012) Spillover Index and the Hafner and Herwartz (2006) analysis of multivariate GARCH models using volatility impulse response analysis. We use two sets of data, daily realized volatility estimates taken from the Oxford Man RV library, running from the beginning of 2000 to October 2016, for the S&P500 and the FTSE, plus ten years of daily returns series for the New York Stock Exchange Index and the FTSE 100 index, from 3 January 2005 to 31 January 2015. Both data sets capture both the Global Financial Crisis (GFC) and the subsequent European Sovereign Debt Crisis (ESDC). The spillover index captures the transmission of volatility to and from markets, plus net spillovers. The key difference between the measures is that the spillover index captures an average of spillovers over a period, whilst volatility impulse responses (VIRF) have to be calibrated to conditional volatility estimated at a particular point in time. The VIRF provide information about the impact of independent shocks on volatility. In the latter analysis, we explore the impact of three different shocks, the onset of the GFC, which we date as 9 August 2007 (GFC1). It took a year for the financial crisis to come to a head, but it did so on 15 September 2008, (GFC2). The third shock is 9 May 2010. Our modelling includes leverage and asymmetric effects undertaken in the context of a multivariate GARCH model, which are then analysed using both BEKK and diagonal BEKK (DBEKK) models. A key result is that the impact of negative shocks is larger, in terms of the effects on variances and covariances, but shorter in duration, in this case a difference between three and six months.
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This paper investigates the robustness of a range of short–term interest rate models. We examine the robustness of these models over different data sets, time periods, sampling frequencies, and estimation techniques. We examine a range of popular one–factor models that allow the conditional mean (drift) and conditional variance (diffusion) to be functions of the current short rate. We find that parameter estimates are highly sensitive to all of these factors in the eight countries that we examine. Since parameter estimates are not robust, these models should be used with caution in practice.
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Mestrado em Contabilidade e Análise Financeira
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The aim of this work project is to find a model that is able to accurately forecast the daily Value-at-Risk for PSI-20 Index, independently of the market conditions, in order to expand empirical literature for the Portuguese stock market. Hence, two subsamples, representing more and less volatile periods, were modeled through unconditional and conditional volatility models (because it is what drives returns). All models were evaluated through Kupiec’s and Christoffersen’s tests, by comparing forecasts with actual results. Using an out-of-sample of 204 observations, it was found that a GARCH(1,1) is an accurate model for our purposes.
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A number of existing studies have concluded that risk sharing allocations supported by competitive, incomplete markets equilibria are quantitatively close to first-best. Equilibrium asset prices in these models have been difficult to distinguish from those associated with a complete markets model, the counterfactual features of which have been widely documented. This paper asks if life cycle considerations, in conjunction with persistent idiosyncratic shocks which become more volatile during aggregate downturns, can reconcile the quantitative properties of the competitive asset pricing framework with those of observed asset returns. We begin by arguing that data from the Panel Study on Income Dynamics support the plausibility of such a shock process. Our estimates suggest a high degree of persistence as well as a substantial increase in idiosyncratic conditional volatility coincident with periods of low growth in U.S. GNP. When these factors are incorporated in a stationary overlapping generations framework, the implications for the returns on risky assets are substantial. Plausible parameterizations of our economy are able to generate Sharpe ratios which match those observed in U.S. data. Our economy cannot, however, account for the level of variability of stock returns, owing in large part to the specification of its production technology.
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Con este trabajo revisamos los Modelos de niveles de las tasas de intereses en Chile. Además de los Modelos de Nivel tradicionales por Chan, Karoly, Longstaff y Lijadoras (1992) en EE. UU, y Parisi (1998) en Chile, por el método de Probabilidad Maximun permitimos que la volatilidad condicional también incluya los procesos inesperados de la información (el modelo GARCH ) y también que la volatilidad sea la función del nivel de la tasa de intereses (modelo TVP-NIVELE) como en Brenner, Harjes y la Crona (1996). Para esto usamos producciones de mercado de bonos de reconocimiento, en cambio las producciones mensuales medias de subasta PDBC, y la ampliación del tamaño y la frecuencia de la muestra a 4 producciones semanales con términos(condiciones) diferentes a la madurez: 1 año, 5 años, 10 años y 15 años. Los resultados principales del estudio pueden ser resumidos en esto: la volatilidad de los cambios inesperados de las tarifas depende positivamente del nivel de las tarifas, sobre todo en el modelo de TVP-NIVEL. Obtenemos pruebas de reversión tacañas, tal que los incrementos en las tasas de intereses no eran independientes, contrariamente a lo obtenido por Brenner. en EE. UU. Los modelos de NIVELES no son capaces de ajustar apropiadamente la volatilidad en comparación con un modelo GARCH (1,1), y finalmente, el modelo de TVP-NIVEL no vence los resultados del modelo GARCH (1,1)
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Con este trabajo revisamos los Modelos de niveles de las tasas de intereses en Chile. Además de los Modelos de Nivel tradicionales por Chan, Karoly, Longstaff y Lijadoras (1992) en EE. UU, y Parisi (1998) en Chile, por el método de Probabilidad Maximun permitimos que la volatilidad condicional también incluya los procesos inesperados de la información (el modelo GARCH ) y también que la volatilidad sea la función del nivel de la tasa de intereses (modelo TVP-NIVELE) como en Brenner, Harjes y la Crona (1996). Para esto usamos producciones de mercado de bonos de reconocimiento, en cambio las producciones mensuales medias de subasta PDBC, y la ampliación del tamaño y la frecuencia de la muestra a 4 producciones semanales con términos(condiciones) diferentes a la madurez: 1 año, 5 años, 10 años y 15 años. Los resultados principales del estudio pueden ser resumidos en esto: la volatilidad de los cambios inesperados de las tarifas depende positivamente del nivel de las tarifas, sobre todo en el modelo de TVP-NIVEL. Obtenemos pruebas de reversión tacañas, tal que los incrementos en las tasas de intereses no eran independientes, contrariamente a lo obtenido por Brenner. en EE. UU. Los modelos de NIVELES no son capaces de ajustar apropiadamente la volatilidad en comparación con un modelo GARCH (1,1), y finalmente, el modelo de TVP-NIVEL no vence los resultados del modelo GARCH (1,1)
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Introduction This dissertation consists of three essays in equilibrium asset pricing. The first chapter studies the asset pricing implications of a general equilibrium model in which real investment is reversible at a cost. Firms face higher costs in contracting than in expanding their capital stock and decide to invest when their productive capital is scarce relative to the overall capital of the economy. Positive shocks to the capital of the firm increase the size of the firm and reduce the value of growth options. As a result, the firm is burdened with more unproductive capital and its value lowers with respect to the accumulated capital. The optimal consumption policy alters the optimal allocation of resources and affects firm's value, generating mean-reverting dynamics for the M/B ratios. The model (1) captures convergence of price-to-book ratios -negative for growth stocks and positive for value stocks - (firm migration), (2) generates deviations from the classic CAPM in line with the cross-sectional variation in expected stock returns and (3) generates a non-monotone relationship between Tobin's q and conditional volatility consistent with the empirical evidence. The second chapter proposes a standard portfolio-choice problem with transaction costs and mean reversion in expected returns. In the presence of transactions costs, no matter how small, arbitrage activity does not necessarily render equal all riskless rates of return. When two such rates follow stochastic processes, it is not optimal immediately to arbitrage out any discrepancy that arises between them. The reason is that immediate arbitrage would induce a definite expenditure of transactions costs whereas, without arbitrage intervention, there exists some, perhaps sufficient, probability that these two interest rates will come back together without any costs having been incurred. Hence, one can surmise that at equilibrium the financial market will permit the coexistence of two riskless rates that are not equal to each other. For analogous reasons, randomly fluctuating expected rates of return on risky assets will be allowed to differ even after correction for risk, leading to important violations of the Capital Asset Pricing Model. The combination of randomness in expected rates of return and proportional transactions costs is a serious blow to existing frictionless pricing models. Finally, in the last chapter I propose a two-countries two-goods general equilibrium economy with uncertainty about the fundamentals' growth rates to study the joint behavior of equity volatilities and correlation at the business cycle frequency. I assume that dividend growth rates jump from one state to other, while countries' switches are possibly correlated. The model is solved in closed-form and the analytical expressions for stock prices are reported. When calibrated to the empirical data of United States and United Kingdom, the results show that, given the existing degree of synchronization across these business cycles, the model captures quite well the historical patterns of stock return volatilities. Moreover, I can explain the time behavior of the correlation, but exclusively under the assumption of a global business cycle.
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Last two decades have seen a rapid change in the global economic and financial situation; the economic conditions in many small and large underdeveloped countries started to improve and they became recognized as emerging markets. This led to growth in the amounts of global investments in these countries, partly spurred by expectations of higher returns, favorable risk-return opportunities, and better diversification alternatives to global investors. This process, however, has not been without problems and it has emphasized the need for more information on these markets. In particular, the liberalization of financial markets around the world, globalization of trade and companies, recent formation of economic and regional blocks, and the rapid development of underdeveloped countries during the last two decades have brought a major challenge to the financial world and researchers alike. This doctoral dissertation studies one of the largest emerging markets, namely Russia. The motivation why the Russian equity market is worth investigating includes, among other factors, its sheer size, rapid and robust economic growth since the turn of the millennium, future prospect for international investors, and a number of important major financial reforms implemented since the early 1990s. Another interesting feature of the Russian economy, which gives motivation to study Russian market, is Russia’s 1998 financial crisis, considered as one of the worst crisis in recent times, affecting both developed and developing economies. Therefore, special attention has been paid to Russia’s 1998 financial crisis throughout this dissertation. This thesis covers the period from the birth of the modern Russian financial markets to the present day, Special attention is given to the international linkage and the 1998 financial crisis. This study first identifies the risks associated with Russian market and then deals with their pricing issues. Finally some insights about portfolio construction within Russian market are presented. The first research paper of this dissertation considers the linkage of the Russian equity market to the world equity market by examining the international transmission of the Russia’s 1998 financial crisis utilizing the GARCH-BEKK model proposed by Engle and Kroner. Empirical results shows evidence of direct linkage between the Russian equity market and the world market both in regards of returns and volatility. However, the weakness of the linkage suggests that the Russian equity market was only partially integrated into the world market, even though the contagion can be clearly seen during the time of the crisis period. The second and the third paper, co-authored with Mika Vaihekoski, investigate whether global, local and currency risks are priced in the Russian stock market from a US investors’ point of view. Furthermore, the dynamics of these sources of risk are studied, i.e., whether the prices of the global and local risk factors are constant or time-varying over time. We utilize the multivariate GARCH-M framework of De Santis and Gérard (1998). Similar to them we find price of global market risk to be time-varying. Currency risk also found to be priced and highly time varying in the Russian market. Moreover, our results suggest that the Russian market is partially segmented and local risk is also priced in the market. The model also implies that the biggest impact on the US market risk premium is coming from the world risk component whereas the Russian risk premium is on average caused mostly by the local and currency components. The purpose of the fourth paper is to look at the relationship between the stock and the bond market of Russia. The objective is to examine whether the correlations between two classes of assets are time varying by using multivariate conditional volatility models. The Constant Conditional Correlation model by Bollerslev (1990), the Dynamic Conditional Correlation model by Engle (2002), and an asymmetric version of the Dynamic Conditional Correlation model by Cappiello et al. (2006) are used in the analysis. The empirical results do not support the assumption of constant conditional correlation and there was clear evidence of time varying correlations between the Russian stocks and bond market and both asset markets exhibit positive asymmetries. The implications of the results in this dissertation are useful for both companies and international investors who are interested in investing in Russia. Our results give useful insights to those involved in minimising or managing financial risk exposures, such as, portfolio managers, international investors, risk analysts and financial researchers. When portfolio managers aim to optimize the risk-return relationship, the results indicate that at least in the case of Russia, one should account for the local market as well as currency risk when calculating the key inputs for the optimization. In addition, the pricing of exchange rate risk implies that exchange rate exposure is partly non-diversifiable and investors are compensated for bearing the risk. Likewise, international transmission of stock market volatility can profoundly influence corporate capital budgeting decisions, investors’ investment decisions, and other business cycle variables. Finally, the weak integration of the Russian market and low correlations between Russian stock and bond market offers good opportunities to the international investors to diversify their portfolios.
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EONIA is a market based overnight interest rate, whose role as the starting point of the yield curve makes it critical from the perspective of the implementation of European Central Bank´s common monetary policy in the euro area. The financial crisis that started in 2007 had a large impact on the determination mechanism of this interest rate, which is considered as the central bank´s operational target. This thesis examines the monetary policy implementation framework of the European Central Bank and changes made to it. Furthermore, we discuss the development of the recent turmoil in the money market. EONIA rate is modelled by means of a regression equation using variables related to liquidity conditions, refinancing need, auction results and calendar effects. Conditional volatility is captured by an EGARCH model, and autocorrelation is taken into account by employing an autoregressive structure. The results highlight how the tensions in the initial stage of the market turmoil were successfully countered by ECB´s liquidity policy. The subsequent response of EONIA to liquidity conditions under the full allotment liquidity provision procedure adopted after the demise of Lehman Brothers is also established. A clear distinction in the behavior of the interest rate between the sub-periods was evident. In the light of the results obtained, some of the challenges posed by the exit-strategy implementation will be addressed.
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Les questions abordées dans les deux premiers articles de ma thèse cherchent à comprendre les facteurs économiques qui affectent la structure à terme des taux d'intérêt et la prime de risque. Je construis des modèles non linéaires d'équilibre général en y intégrant des obligations de différentes échéances. Spécifiquement, le premier article a pour objectif de comprendre la relation entre les facteurs macroéconomiques et le niveau de prime de risque dans un cadre Néo-keynésien d'équilibre général avec incertitude. L'incertitude dans le modèle provient de trois sources : les chocs de productivité, les chocs monétaires et les chocs de préférences. Le modèle comporte deux types de rigidités réelles à savoir la formation des habitudes dans les préférences et les coûts d'ajustement du stock de capital. Le modèle est résolu par la méthode des perturbations à l'ordre deux et calibré à l'économie américaine. Puisque la prime de risque est par nature une compensation pour le risque, l'approximation d'ordre deux implique que la prime de risque est une combinaison linéaire des volatilités des trois chocs. Les résultats montrent qu'avec les paramètres calibrés, les chocs réels (productivité et préférences) jouent un rôle plus important dans la détermination du niveau de la prime de risque relativement aux chocs monétaires. Je montre que contrairement aux travaux précédents (dans lesquels le capital de production est fixe), l'effet du paramètre de la formation des habitudes sur la prime de risque dépend du degré des coûts d'ajustement du capital. Lorsque les coûts d'ajustement du capital sont élevés au point que le stock de capital est fixe à l'équilibre, une augmentation du paramètre de formation des habitudes entraine une augmentation de la prime de risque. Par contre, lorsque les agents peuvent librement ajuster le stock de capital sans coûts, l'effet du paramètre de la formation des habitudes sur la prime de risque est négligeable. Ce résultat s'explique par le fait que lorsque le stock de capital peut être ajusté sans coûts, cela ouvre un canal additionnel de lissage de consommation pour les agents. Par conséquent, l'effet de la formation des habitudes sur la prime de risque est amoindri. En outre, les résultats montrent que la façon dont la banque centrale conduit sa politique monétaire a un effet sur la prime de risque. Plus la banque centrale est agressive vis-à-vis de l'inflation, plus la prime de risque diminue et vice versa. Cela est due au fait que lorsque la banque centrale combat l'inflation cela entraine une baisse de la variance de l'inflation. Par suite, la prime de risque due au risque d'inflation diminue. Dans le deuxième article, je fais une extension du premier article en utilisant des préférences récursives de type Epstein -- Zin et en permettant aux volatilités conditionnelles des chocs de varier avec le temps. L'emploi de ce cadre est motivé par deux raisons. D'abord des études récentes (Doh, 2010, Rudebusch and Swanson, 2012) ont montré que ces préférences sont appropriées pour l'analyse du prix des actifs dans les modèles d'équilibre général. Ensuite, l'hétéroscedasticité est une caractéristique courante des données économiques et financières. Cela implique que contrairement au premier article, l'incertitude varie dans le temps. Le cadre dans cet article est donc plus général et plus réaliste que celui du premier article. L'objectif principal de cet article est d'examiner l'impact des chocs de volatilités conditionnelles sur le niveau et la dynamique des taux d'intérêt et de la prime de risque. Puisque la prime de risque est constante a l'approximation d'ordre deux, le modèle est résolu par la méthode des perturbations avec une approximation d'ordre trois. Ainsi on obtient une prime de risque qui varie dans le temps. L'avantage d'introduire des chocs de volatilités conditionnelles est que cela induit des variables d'état supplémentaires qui apportent une contribution additionnelle à la dynamique de la prime de risque. Je montre que l'approximation d'ordre trois implique que les primes de risque ont une représentation de type ARCH-M (Autoregressive Conditional Heteroscedasticty in Mean) comme celui introduit par Engle, Lilien et Robins (1987). La différence est que dans ce modèle les paramètres sont structurels et les volatilités sont des volatilités conditionnelles de chocs économiques et non celles des variables elles-mêmes. J'estime les paramètres du modèle par la méthode des moments simulés (SMM) en utilisant des données de l'économie américaine. Les résultats de l'estimation montrent qu'il y a une évidence de volatilité stochastique dans les trois chocs. De plus, la contribution des volatilités conditionnelles des chocs au niveau et à la dynamique de la prime de risque est significative. En particulier, les effets des volatilités conditionnelles des chocs de productivité et de préférences sont significatifs. La volatilité conditionnelle du choc de productivité contribue positivement aux moyennes et aux écart-types des primes de risque. Ces contributions varient avec la maturité des bonds. La volatilité conditionnelle du choc de préférences quant à elle contribue négativement aux moyennes et positivement aux variances des primes de risque. Quant au choc de volatilité de la politique monétaire, son impact sur les primes de risque est négligeable. Le troisième article (coécrit avec Eric Schaling, Alain Kabundi, révisé et resoumis au journal of Economic Modelling) traite de l'hétérogénéité dans la formation des attentes d'inflation de divers groupes économiques et de leur impact sur la politique monétaire en Afrique du sud. La question principale est d'examiner si différents groupes d'agents économiques forment leurs attentes d'inflation de la même façon et s'ils perçoivent de la même façon la politique monétaire de la banque centrale (South African Reserve Bank). Ainsi on spécifie un modèle de prédiction d'inflation qui nous permet de tester l'arrimage des attentes d'inflation à la bande d'inflation cible (3% - 6%) de la banque centrale. Les données utilisées sont des données d'enquête réalisée par la banque centrale auprès de trois groupes d'agents : les analystes financiers, les firmes et les syndicats. On exploite donc la structure de panel des données pour tester l'hétérogénéité dans les attentes d'inflation et déduire leur perception de la politique monétaire. Les résultats montrent qu'il y a évidence d'hétérogénéité dans la manière dont les différents groupes forment leurs attentes. Les attentes des analystes financiers sont arrimées à la bande d'inflation cible alors que celles des firmes et des syndicats ne sont pas arrimées. En effet, les firmes et les syndicats accordent un poids significatif à l'inflation retardée d'une période et leurs prédictions varient avec l'inflation réalisée (retardée). Ce qui dénote un manque de crédibilité parfaite de la banque centrale au vu de ces agents.
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This paper contributes to the debate on the effects of the financialization of commodity futures markets by studying the conditional volatility of long–short commodity portfolios and their conditional correlations with traditional assets (stocks and bonds). Using several groups of trading strategies that hedge fund managers are known to implement, we show that long–short speculators do not cause changes in the volatilities of the portfolios they hold or changes in the conditional correlations between these portfolios and traditional assets. Thus calls for increased regulation of commodity money managers are, at this stage, premature. Additionally, long–short speculators can take comfort in knowing that their trades do not alter the risk and diversification properties of their portfolios.
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O objetivo do presente trabalho é analisar as características empíricas de uma série de retornos de dados em alta freqüência para um dos ativos mais negociados na Bolsa de Valores de São Paulo. Estamos interessados em modelar a volatilidade condicional destes retornos, testando em particular a presença de memória longa, entre outros fenômenos que caracterizam este tipo de dados. Nossa investigação revela que além da memória longa, existe forte sazonalidade intradiária, mas não encontramos evidências de um fato estilizado de retornos de ações, o efeito alavancagem. Utilizamos modelos capazes de captar a memória longa na variância condicional dos retornos dessazonalizados, com resultados superiores a modelos tradicionais de memória curta, com implicações importantes para precificação de opções e de risco de mercado
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Este estudo compara previsões de volatilidade de sete ações negociadas na Bovespa usando 02 diferentes modelos de volatilidade realizada e 03 de volatilidade condicional. A intenção é encontrar evidências empíricas quanto à diferença de resultados que são alcançados quando se usa modelos de volatilidade realizada e de volatilidade condicional para prever a volatilidade de ações no Brasil. O período analisado vai de 01 de Novembro de 2007 a 30 de Março de 2011. A amostra inclui dados intradiários de 5 minutos. Os estimadores de volatilidade realizada que serão considerados neste estudo são o Bi-Power Variation (BPVar), desenvolvido por Barndorff-Nielsen e Shephard (2004b), e o Realized Outlyingness Weighted Variation (ROWVar), proposto por Boudt, Croux e Laurent (2008a). Ambos são estimadores não paramétricos, e são robustos a jumps. As previsões de volatilidade realizada foram feitas através de modelos autoregressivos estimados para cada ação sobre as séries de volatilidade estimadas. Os modelos de variância condicional considerados aqui serão o GARCH(1,1), o GJR (1,1), que tem assimetrias em sua construção, e o FIGARCH-CHUNG (1,d,1), que tem memória longa. A amostra foi divida em duas; uma para o período de estimação de 01 de Novembro de 2007 a 30 de Dezembro de 2010 (779 dias de negociação) e uma para o período de validação de 03 de Janeiro de 2011 a 31 de Março de 2011 (61 dias de negociação). As previsões fora da amostra foram feitas para 1 dia a frente, e os modelos foram reestimados a cada passo, incluindo uma variável a mais na amostra depois de cada previsão. As previsões serão comparadas através do teste Diebold-Mariano e através de regressões da variância ex-post contra uma constante e a previsão. Além disto, o estudo também apresentará algumas estatísticas descritivas sobre as séries de volatilidade estimadas e sobre os erros de previsão.
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Esta tese é constituída por três ensaios. O primeiro ensaio analisa a informação pública disponível sobre o risco das carteiras de crédito dos bancos brasileiros, sendo dividido em dois capítulos. O primeiro analisa a limitação da informação pública disponibilizada pelos bancos e pelo Banco Central, quando comparada a informação gerencial disponível internamente pelos bancos. Concluiu-se que existe espaço para o aumento da transparência na divulgação das informações, fato que vem ocorrendo gradativamente no Brasil através de novas normas relacionadas ao Pilar 3 de Basileia II e à divulgação de informações mais detalhas pelo Bacen, como, por exemplo, aquelas do “Top50” . A segunda parte do primeiro ensaio mostra a discrepância entre o índice de inadimplência contábil (NPL) e a probabilidade de inadimplência (PD) e também discute a relação entre provisão e perda esperada. Através da utilização de matrizes de migração e de uma simulação baseada na sobreposição de safras de carteira de crédito de grandes bancos, concluiu-se que o índice de inadimplência subestima a PD e que a provisão constituída pelos bancos é menor que a perda esperada do SFN. O segundo ensaio relaciona a gestão de risco à discriminação de preço. Foi desenvolvido um modelo que consiste em um duopólio de Cournot em um mercado de crédito de varejo, em que os bancos podem realizar discriminação de terceiro grau. Neste modelo, os potenciais tomadores de crédito podem ser de dois tipos, de baixo ou de alto risco, sendo que tomadores de baixo risco possuem demanda mais elástica. Segundo o modelo, se o custo para observar o tipo do cliente for alto, a estratégia dos bancos será não discriminar (pooling equilibrium). Mas, se este custo for suficientemente baixo, será ótimo para os bancos cobrarem taxas diferentes para cada grupo. É argumentado que o Acordo de Basileia II funcionou como um choque exógeno que deslocou o equilíbrio para uma situação com maior discriminação. O terceiro ensaio é divido em dois capítulos. O primeiro discute a aplicação dos conceitos de probabilidade subjetiva e incerteza Knigthiana a modelos de VaR e a importância da avaliação do “risco de modelo”, que compreende os riscos de estimação, especificação e identificação. O ensaio propõe que a metodologia dos “quatro elementos” de risco operacional (dados internos, externos, ambiente de negócios e cenários) seja estendida à mensuração de outros riscos (risco de mercado e risco de crédito). A segunda parte deste último ensaio trata da aplicação do elemento análise de cenários para a mensuração da volatilidade condicional nas datas de divulgação econômica relevante, especificamente nos dias de reuniões do Copom.