Submitted by João Luiz Piccioni Junior (jpiccionijr@gmail.com) on 2011-08-31T00:14:51Z No. of bitstreams: 1 Dissertação JLPJ_Versão Final v2.pdf: 511997 bytes, checksum: 4bc86e9dcc6f2c5d4670840389eca1a5 (MD5) / Rejected by Gisele Isaura Hannickel (gisele.hannickel@fgv.br), reason: Prezado João Luiz, A capa de seu trabalho e a folha de rosto estão iguais. Na capa não deve contemplar "Dissertação apresentada à Escola....". Esta informação é somente na folha de rosto (2ª folha que está correta). Att, Gisele Hannickel Secretaria de Registro on 2011-08-31T13:21:35Z (GMT) / Submitted by João Luiz Piccioni Junior (jpiccionijr@gmail.com) on 2011-08-31T21:50:44Z No. of bitstreams: 1 Dissertação JLPJ_Versão Final v2.pdf: 511127 bytes, checksum: bf30747269af97ea98bc51ca5141b624 (MD5) / Approved for entry into archive by Gisele Isaura Hannickel (gisele.hannickel@fgv.br) on 2011-09-01T12:44:27Z (GMT) No. of bitstreams: 1 Dissertação JLPJ_Versão Final v2.pdf: 511127 bytes, checksum: bf30747269af97ea98bc51ca5141b624 (MD5) / Approved for entry into archive by Gisele Isaura Hannickel (gisele.hannickel@fgv.br) on 2011-09-01T12:44:39Z (GMT) No. of bitstreams: 1 Dissertação JLPJ_Versão Final v2.pdf: 511127 bytes, checksum: bf30747269af97ea98bc51ca5141b624 (MD5) / Made available in DSpace on 2011-09-01T12:46:39Z (GMT). No. of bitstreams: 1 Dissertação JLPJ_Versão Final v2.pdf: 511127 bytes, checksum: bf30747269af97ea98bc51ca5141b624 (MD5) Previous issue date: 2011-08-09 / In this paper, we observe the preferential characteristics of Foreign Mutual Fund Managers when investing in Latin America. The main objective was checking the hypothesis that those managers prefer companies with characteristics that amplifies its visibility, in other words, that reduces information asymmetry, a possible explanation for the existence of home bias. For this purpose, we observe mutual funds positions based on shareholders lists of the companies listed at the stock exchanges of the countries of the sample in three different periods (June 2008, 2009 and 2010). The results show that this class of investors prefers companies’ attributes that amplify their contact with international markets, like international listing, bigger analyst coverage and being part of exporter sectors, reinforcing the idea that information asymmetry reduces the ability of asset selection and, therefore, justifying home bias theory. The study also compare preferences of foreign fund managers with domestic ones, located in Latin America, and shows evidence that home basis fund managers expand their portfolio towards a market portfolio, and has different preferences that those observed by foreign fund managers. / Nesse trabalho são observadas as características preferencias dos gestores de fundos mútuos estrangeiros ao selecionar ações na América Latina. O objetivo foi verificar a hipótese de que esses gestores preferem companhias que possuam características que geram grande visibilidade, ou seja, que reduzam a assimetria de informação, uma das possíveis explicações para a existência do home bias. Para isso, foram observadas as posições dos fundos mútuos a partir das listas de acionistas das companhias listadas nas bolsas dos países da amostra em três períodos diferentes (junho de 2008, 2009 e 2010). A análise revela que essa classe de investidores prefere companhias que possuam atributos que ampliem seu contato com mercados internacionais, tais quais, a listagem internacional, maior cobertura de analistas e que façam parte de setores exportadores, reforçando a ideia de que a assimetria de informação reduz a capacidade de seleção de ativos por parte dos participantes de mercado e, portanto, justificando a teoria do home bias. O estudo ainda compara as preferências dos gestores estrangeiros com gestores domiciliados na América Latina e mostra evidências de que os gestores de fundos mútuos domésticos possuem maior dispersão de investimentos nas companhias listadas e, consequentemente, possuem preferências diferentes daquelas observadas para os gestores estrangeiros.

This thesis aims at determining the theoretical and empirical consequences of the consideration of socially responsible indicators in the traditional portfolio selection. The first chapter studies the significance of the mean-variance efficiency loss of a sovereign bond portfolio when introducing a constraint on the average socially responsible ratings of the governments. By using a sample of developed sovereign bonds on the period 1995-2008, we show that it is possible to increase sensibly the average socially responsible rating without significantly losing in terms of diversification. The second chapter proposes a theoretical analysis of the impact on the efficient frontier of a constraint on the socially responsible ratings of the portfolio. We highlight that different cases may arise depending on the correlation between the expected returns and the socially responsible ratings and on the investor’s risk aversion. Lastly, as the issue of the efficiency of socially responsible portfolios is a central point in the financial literature, the last chapter proposes a new mean-variance efficiency test in the realistic case where there is no available risk-free asset. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished

We present three chapters on theoretical issues of banking. These deal with bank runs, risk sharing, lending and profitability. In the first chapter, we examine the agency problem in the bank-depositor relationship. Depositors are the principals and banks are the agents. Banks choose investment portfolios and are subject to moral hazard in that they have incentive to take on more risk than desirable to depositors because they are residual claimants. We study an incentive-compatible mechanism that prompts banks to follow a safe investment policy. This mechanism leaves the bank a profit margin in a similar manner to a CEO being paid a bonus by a company. In the second chapter, we extend Allen and Gale (1998) by adding a long-term riskless investment opportunity to the original portfolio of a short-term liquid asset and a long-term risky illiquid asset. Through portfolio diversification, we identify the risk-sharing deposit contract in a three-period model that maximizes the ex-ante expected utility of depositors. Unlike Allen and Gale, there are no information-based bank runs in equilibrium. In addition, our model can improve consumers' welfare over the Allen and Gale model. I also show that the bank will choose to liquidate the cheaper investments, in terms of the gain-loss ratios for the two types of existing long-term assets, when there is liquidity shortage in some cases. Such a policy reduces the liquidation cost and enables the bank to meet the outstanding liability to depositors without large liquidation losses. In the third chapter, we study the role of banks in providing loans to borrower firms. This paper extends the theory of designing optimal loan contracts (for profits) in the Bolton and Scharfstein (1996) model to a setting where asymmetry of information exists. Based on the verifiability of information structure, we analyze complete and incomplete contracts. Through this analysis, optimal, incentive-compatible loan contracts that maximize the expected profit of the bank are characterized. Our analysis suggests that a bank could be induced to liquidate a borrower's project under specific conditions. Furthermore, we identify implementable mechanisms for the renegotiation game given the bargaining power between a borrower and a bank.

[pt] Esta tese é composta por quatro artigos que descrevem diferentes formas de inclusão de aversão a risco em problemas dinâmicos, ressaltando seus aspectos teóricos e consequências práticas envolvidas em técnicas de otimização sob incerteza aplicadas a problemas financeiros. O primeiro artigo propões uma interpretação econômica e analisa as consequencias práticas da consistência temporal, em que particular para o problema de seleção de portfólio. No segunfo artigo, também aplicado à seleção de portfólio, é proposto um modelo que considera empréstimo como variável de decisão e uma função convexa e linear por partes que representa a existência de diversos credores com diferentes limites de crédito e taxas de juros. A performance do modelo proposto é melhor que as aproximações existentes e garante otimalidade para a situação de vários credores. No terceiro artigo, desenvolve-se um modelo de emissão de títulos de dívida de uma empresa que seja financiar um conjunto pré-determinado de projetos. Trata-se de um modelo de otimização dinâmico sob incerteza que considera títulos pré e pós-fixados com diferentes maturidades e formas de amortização. As principais contribuições são o tratammento de um horizonte longuíssimo prazo através de uma estrutura híbrida dos cenários; a modelagem detalhada do pagamento de cupons e amortizações; o desenvolvimento de uma função objetivo multi-critério que reflete o trade-off entre risco-retorno além de outras medidas de performance financeiras como a taxa de alavancagem (razão passivos sobre ativos). No quarto artigo é desenvolvido um modelo de programação estocástica multi-estágio para obter a política ótima de caixa de uma empresa cujo custo de investimento e o custo da dívida são incertos e modelados em diferentes regimes. As contribuições são a extensão de metodologia de equilíbrio dual para um modelo estocástico; a proposição de uma regra de decisão baseada na estrutura de regime dos fatores de risco que aproxima de forma satisfatória o modelo original. / [en] This PhD Thesis is composed of four working papers, each one with a respective chapter on this thesis, with contributions on risk averse stochastic programming models. In particular, it focuses on analyzing the practical consequences of certain theoretical concepts of decision theory, finance and optimization. The first working paper analyzes the practical consequences and the economic interpretation of time consistent optimal policies, in particular for well known portfolio selection problem. The second paper has also a contribution to the portfolio selection literature. Indeed, we develop leverage optimal strategy considering a single-period debt with a piecewise linear borrowing cost function, which represents the actual situation faced by investors, and show a significant gap in comparison to the suboptimal solutions obtained by the usual linear approximation. Moreover, we develop a multistage extension where our cost function indirectly penalizes the excess of leverage, which is closely related to the contribution of the next working paper. The contribution of the third working paper is to penalize excess of leverage in a debt issuance multistage model that optimizes over several types of bonds with fixed or floating rate, different maturities and amortization patterns. For the sake of dealing with the curse of dimensionality of a long term problem, we divide the planning horizon into a detailed part at the beginning followed by a policy rule approximation for the remainder. Indeed, our approximation mitigates the end effects of a truncated model which is closely related to the contributions of the forth working paper. The forth paper develops a multistage model that seeks to obtain the optimal cash holding policy of a firm. The main contributions are a methodology to end effect treatment for a multistage model with infinite horizon and the development of a policy rule as approximation of the optimal solution.

Diese Dissertation behandelt die ökonometrische Analyse von hochfrequenten Finanzmarktdaten. Kapitel 1 stellt einen neuen Ansatz zur Modellierung von seriell abhängigen positiven Variablen, die einen nichttrivialen Anteil an Nullwerten aufweisen, vor. Letzteres ist ein weitverbreitetes Phänomen in hochfrequenten Finanzmarktzeitreihen. Eingeführt wird eine flexible Punktmassenmischverteilung, ein maßgeschneiderter semiparametrischer Spezifikationstest sowie eine neue Art von multiplikativem Fehlermodell (MEM). Kapitel 2 beschäftigt sich mit dem Umstand, dass feste symmetrische Kerndichteschätzer eine geringe Präzision aufweisen, falls eine positive Zufallsvariable mit erheblicher Wahrscheinlichkeitsmasse nahe Null gegeben ist. Wir legen dar, dass Gammakernschätzer überlegen sind, wobei ihre relative Präzision von der genauen Form der Dichte sowie des Kerns abhängt. Wir führen einen verbesserten Gammakernschätzer sowie eine datengetriebene Methodik für die Wahl des geeigneten Typs von Gammakern ein. Kapitel 3 wendet sich der Frage nach dem Nutzen von Hochfrequenzdaten für hochdimensionale Portfolioallokationsanwendungen zu. Wir betrachten das Problem der Konstruktion von globalen Minimum-Varianz-Portfolios auf der Grundlage der Konstituenten des S&P 500. Wir zeigen auf, dass Prognosen, welche auf Hochfrequenzdaten basieren, im Vergleich zu Methoden, die tägliche Renditen verwenden, eine signifikant geringere Portfoliovolatilität implizieren. Letzteres geht mit spürbaren Nutzengewinnen aus der Sicht eines Investors mit hoher Risikoaversion einher. / In three essays, this thesis deals with the econometric analysis of financial market data sampled at intraday frequencies. Chapter 1 presents a novel approach to model serially dependent positive-valued variables realizing a nontrivial proportion of zero outcomes. This is a typical phenomenon in financial high-frequency time series. We introduce a flexible point-mass mixture distribution, a tailor-made semiparametric specification test and a new type of multiplicative error model (MEM). Chapter 2 addresses the problem that fixed symmetric kernel density estimators exhibit low precision for positive-valued variables with a large probability mass near zero, which is common in high-frequency data. We show that gamma kernel estimators are superior, while their relative performance depends on the specific density and kernel shape. We suggest a refined gamma kernel and a data-driven method for choosing the appropriate type of gamma kernel estimator. Chapter 3 turns to the debate about the merits of high-frequency data in large-scale portfolio allocation. We consider the problem of constructing global minimum variance portfolios based on the constituents of the S&P 500. We show that forecasts based on high-frequency data can yield a significantly lower portfolio volatility than approaches using daily returns, implying noticeable utility gains for a risk-averse investor.

Diese Dissertation umfasst drei Papiere, die sich mit den Konsequenzen von verpflichtend aufzustellender finanzieller Berichterstattung befassen. Die erste Studie beschäftigt sich mit einer Gesetzesänderung, die Investoren betrifft, deren Stimmrechtsanteile offenzulegen sind. Sie untersucht, welche Investoren ihre Unternehmensanteile anpassen, nachdem die Gesetzesänderung, die in einer Herabsetzung des Eingangsschwellenwerts für Stimmrechtsmitteilungen resultiert, in Kraft tritt. Die Ergebnisse sind konsistent mit einer Umschichtung in der Eigentümerstruktur von Unternehmen. Sie zeigen, dass Investmentfonds und, in etwas geringerem Maße, Banken ihre Anteile reduzieren während nichtfinanzielle Unternehmen ihre Anteile erhöhen. Die zweite Studie befasst sich mit der Rolle von Offenlegungsinstrumenten für Portfolioentscheidungen von einem speziellen Investorentyp, Investmentfonds. Sie analysiert, ob die Vergleichbarkeit von Rechnungslegungsinformationen mit der Zugehörigkeit zu Portfolios von Investmentfonds assoziiert ist. Die Ergebnisse stehen im Einklang mit der Bedeutung von Vergleichbarkeit in der Rechnungslegung für die Selektion von Portfoliounternehmen. Investmentfonds nehmen Unternehmen mit einer größeren Wahrscheinlichkeit in ihr Portfolio auf, wenn die Rechnungslegungsinstrumente dieser Unternehmen eine höhere Vergleichbarkeit mit den Rechnungslegungsinstrumenten anderer Portfoliounternehmen aufweisen. Die dritte Studie legt die Aufmerksamkeit auf Fachkräfte in der Rechnungslegung, die die Erstellung von Offenlegungsinstrumenten unterstützen, Wirtschaftsprüfer und Berater. Sie betrachtet Determinanten ihrer Entscheidung, temporär innerhalb der Unternehmensstrukturen zu migrieren, mit Bezug auf länder- und berufsspezifische Charakteristika. Die Ergebnisse deuten an, dass Unterschiede in der Rechnungslegungs- und Steuerregulierung Migrationsentscheidungen beeinflussen können. / This dissertation comprises three papers on the consequences of mandatory, financial disclosures. The first study focuses on a rule change which applies to investors who are required to disclose their ownership in firms. It investigates which investor types adjust their holdings in response to this rule change, the introduction of lower reporting thresholds. Results are consistent with a reshuffling of the ownership structure of firms. Precisely, they show that mutual funds and, to a lesser extent, banks decrease their holdings while non-financial corporations increase their holdings. The second study concentrates on the role of disclosures in portfolio decisions of one particular investor type, mutual funds. It analyzes whether comparability of firms’ accounting disclosures is associated with their membership in mutual funds’ portfolios. Results are in line with accounting comparability mattering for portfolio selection. Specifically, mutual funds are more likely to include a firm in their portfolio if the firm is more comparable, in accounting terms, to existing portfolio peers. The third study shifts the attention to accounting professionals who assist in the preparation of financial disclosures, auditors and consultants. It studies country-level as well as occupation-specific determinants of the decision to temporarily migrate within firms. Results suggest that differences in accounting and tax rules across countries can affect migration decisions of these professionals.

Cette thèse de doctorat consiste en trois chapitres qui traitent des sujets de choix de portefeuilles de grande taille, et de mesure de risque. Le premier chapitre traite du problème d’erreur d’estimation dans les portefeuilles de grande taille, et utilise le cadre d'analyse moyenne-variance. Le second chapitre explore l'importance du risque de devise pour les portefeuilles d'actifs domestiques, et étudie les liens entre la stabilité des poids de portefeuille de grande taille et le risque de devise. Pour finir, sous l'hypothèse que le preneur de décision est pessimiste, le troisième chapitre dérive la prime de risque, une mesure du pessimisme, et propose une méthodologie pour estimer les mesures dérivées. Le premier chapitre améliore le choix optimal de portefeuille dans le cadre du principe moyenne-variance de Markowitz (1952). Ceci est motivé par les résultats très décevants obtenus, lorsque la moyenne et la variance sont remplacées par leurs estimations empiriques. Ce problème est amplifié lorsque le nombre d’actifs est grand et que la matrice de covariance empirique est singulière ou presque singulière. Dans ce chapitre, nous examinons quatre techniques de régularisation pour stabiliser l’inverse de la matrice de covariance: le ridge, spectral cut-off, Landweber-Fridman et LARS Lasso. Ces méthodes font chacune intervenir un paramètre d’ajustement, qui doit être sélectionné. La contribution principale de cette partie, est de dériver une méthode basée uniquement sur les données pour sélectionner le paramètre de régularisation de manière optimale, i.e. pour minimiser la perte espérée d’utilité. Précisément, un critère de validation croisée qui prend une même forme pour les quatre méthodes de régularisation est dérivé. Les règles régularisées obtenues sont alors comparées à la règle utilisant directement les données et à la stratégie naïve 1/N, selon leur perte espérée d’utilité et leur ratio de Sharpe. Ces performances sont mesurée dans l’échantillon (in-sample) et hors-échantillon (out-of-sample) en considérant différentes tailles d’échantillon et nombre d’actifs. Des simulations et de l’illustration empirique menées, il ressort principalement que la régularisation de la matrice de covariance améliore de manière significative la règle de Markowitz basée sur les données, et donne de meilleurs résultats que le portefeuille naïf, surtout dans les cas le problème d’erreur d’estimation est très sévère. Dans le second chapitre, nous investiguons dans quelle mesure, les portefeuilles optimaux et stables d'actifs domestiques, peuvent réduire ou éliminer le risque de devise. Pour cela nous utilisons des rendements mensuelles de 48 industries américaines, au cours de la période 1976-2008. Pour résoudre les problèmes d'instabilité inhérents aux portefeuilles de grandes tailles, nous adoptons la méthode de régularisation spectral cut-off. Ceci aboutit à une famille de portefeuilles optimaux et stables, en permettant aux investisseurs de choisir différents pourcentages des composantes principales (ou dégrées de stabilité). Nos tests empiriques sont basés sur un modèle International d'évaluation d'actifs financiers (IAPM). Dans ce modèle, le risque de devise est décomposé en deux facteurs représentant les devises des pays industrialisés d'une part, et celles des pays émergents d'autres part. Nos résultats indiquent que le risque de devise est primé et varie à travers le temps pour les portefeuilles stables de risque minimum. De plus ces stratégies conduisent à une réduction significative de l'exposition au risque de change, tandis que la contribution de la prime risque de change reste en moyenne inchangée. Les poids de portefeuille optimaux sont une alternative aux poids de capitalisation boursière. Par conséquent ce chapitre complète la littérature selon laquelle la prime de risque est importante au niveau de l'industrie et au niveau national dans la plupart des pays. Dans le dernier chapitre, nous dérivons une mesure de la prime de risque pour des préférences dépendent du rang et proposons une mesure du degré de pessimisme, étant donné une fonction de distorsion. Les mesures introduites généralisent la mesure de prime de risque dérivée dans le cadre de la théorie de l'utilité espérée, qui est fréquemment violée aussi bien dans des situations expérimentales que dans des situations réelles. Dans la grande famille des préférences considérées, une attention particulière est accordée à la CVaR (valeur à risque conditionnelle). Cette dernière mesure de risque est de plus en plus utilisée pour la construction de portefeuilles et est préconisée pour compléter la VaR (valeur à risque) utilisée depuis 1996 par le comité de Bâle. De plus, nous fournissons le cadre statistique nécessaire pour faire de l’inférence sur les mesures proposées. Pour finir, les propriétés des estimateurs proposés sont évaluées à travers une étude Monte-Carlo, et une illustration empirique en utilisant les rendements journaliers du marché boursier américain sur de la période 2000-2011. / This thesis consists of three chapters on the topics of portfolio choice in a high-dimensional context, and risk measurement. The first chapter addresses the estimation error issue that arises when constructing large portfolios in the mean-variance framework. The second chapter investigates the relevance of currency risk for optimal domestic portfolios, evaluates their ability of to diversify away currency risk, and study the links between portfolio weights stability and currency risk. Finally, under the assumption that decision makers are pessimistic, the third chapter derives the risk premium, propose a measure of the degree of pessimism, and provide a statistical framework for their estimation. The first chapter improves the performance of the optimal portfolio weig-hts obtained under the mean-variance framework of Markowitz (1952). Indeed, these weights give unsatisfactory results, when the mean and variance are replaced by their sample counterparts (plug-in rules). This problem is amplified when the number of assets is large and the sample covariance is singular or nearly singular. The chapter investigates four regularization techniques to stabilizing the inverse of the covariance matrix: the ridge, spectral cut-off, Landweber-Fridman, and LARS Lasso. These four methods involve a tuning parameter that needs to be selected. The main contribution is to derive a data-based method for selecting the tuning parameter in an optimal way, i.e. in order to minimize the expected loss in utility of a mean-variance investor. The cross-validation type criterion derived is found to take a similar form for the four regularization methods. The resulting regularized rules are compared to the sample-based mean-variance portfolio and the naive 1/N strategy in terms of in-sample and out-of-sample Sharpe ratio and expected loss in utility. The main finding is that regularization to covariance matrix significantly improves the performance of the mean-variance problem and outperforms the naive portfolio, especially in ill-posed cases, as suggested by our simulations and empirical studies. In the second chapter, we investigate the extent to which optimal and stable portfolios of domestic assets can reduce or eliminate currency risk. This is done using monthly returns on 48 U.S. industries, from 1976 to 2008. To tackle the instabilities inherent to large portfolios, we use the spectral cut-off regularization described in Chapter 1. This gives rise to a family of stable global minimum portfolios that allows investors to select different percentages of principal components for portfolio construction. Our empirical tests are based on a conditional International Asset Pricing Model (IAPM), augmented with the size and book-to-market factors of Fama and French (1993). Using two trade-weighted currency indices of industrialized countries currencies and emerging markets currencies, we find that currency risk is priced and time-varying for global minimum portfolios. These strategies also lead to a significant reduction in the exposure to currency risk, while keeping the average premium contribution to total premium approximately the same. The global minimum weights considered are an alternative to market capitalization weights used in the U.S. market index. Therefore, our findings complement the well established results that currency risk is significantly priced and economically meaningful at the industry and country level in most countries. Finally, the third chapter derives a measure of the risk premium for rank-dependent preferences and proposes a measure of the degree of pessimism, given a distortion function. The introduced measures generalize the common risk measures derived in the expected utility theory framework, which is frequently violated in both experimental and real-life situations. These measures are derived in the neighborhood of a given random loss variable, using the notion of local utility function. A particular interest is devoted to the CVaR, which is now widely used for asset allocation and has been advocated to complement the Value-at-risk (VaR) proposed since 1996 by the Basel Committee on Banking Supervision. We provide the statistical framework needed to conduct inference on the derived measures. Finally, the proposed estimators

Cette thèse de doctorat consiste en trois chapitres qui traitent des sujets de choix de portefeuilles de grande taille, et de mesure de risque. Le premier chapitre traite du problème d’erreur d’estimation dans les portefeuilles de grande taille, et utilise le cadre d'analyse moyenne-variance. Le second chapitre explore l'importance du risque de devise pour les portefeuilles d'actifs domestiques, et étudie les liens entre la stabilité des poids de portefeuille de grande taille et le risque de devise. Pour finir, sous l'hypothèse que le preneur de décision est pessimiste, le troisième chapitre dérive la prime de risque, une mesure du pessimisme, et propose une méthodologie pour estimer les mesures dérivées. Le premier chapitre améliore le choix optimal de portefeuille dans le cadre du principe moyenne-variance de Markowitz (1952). Ceci est motivé par les résultats très décevants obtenus, lorsque la moyenne et la variance sont remplacées par leurs estimations empiriques. Ce problème est amplifié lorsque le nombre d’actifs est grand et que la matrice de covariance empirique est singulière ou presque singulière. Dans ce chapitre, nous examinons quatre techniques de régularisation pour stabiliser l’inverse de la matrice de covariance: le ridge, spectral cut-off, Landweber-Fridman et LARS Lasso. Ces méthodes font chacune intervenir un paramètre d’ajustement, qui doit être sélectionné. La contribution principale de cette partie, est de dériver une méthode basée uniquement sur les données pour sélectionner le paramètre de régularisation de manière optimale, i.e. pour minimiser la perte espérée d’utilité. Précisément, un critère de validation croisée qui prend une même forme pour les quatre méthodes de régularisation est dérivé. Les règles régularisées obtenues sont alors comparées à la règle utilisant directement les données et à la stratégie naïve 1/N, selon leur perte espérée d’utilité et leur ratio de Sharpe. Ces performances sont mesurée dans l’échantillon (in-sample) et hors-échantillon (out-of-sample) en considérant différentes tailles d’échantillon et nombre d’actifs. Des simulations et de l’illustration empirique menées, il ressort principalement que la régularisation de la matrice de covariance améliore de manière significative la règle de Markowitz basée sur les données, et donne de meilleurs résultats que le portefeuille naïf, surtout dans les cas le problème d’erreur d’estimation est très sévère. Dans le second chapitre, nous investiguons dans quelle mesure, les portefeuilles optimaux et stables d'actifs domestiques, peuvent réduire ou éliminer le risque de devise. Pour cela nous utilisons des rendements mensuelles de 48 industries américaines, au cours de la période 1976-2008. Pour résoudre les problèmes d'instabilité inhérents aux portefeuilles de grandes tailles, nous adoptons la méthode de régularisation spectral cut-off. Ceci aboutit à une famille de portefeuilles optimaux et stables, en permettant aux investisseurs de choisir différents pourcentages des composantes principales (ou dégrées de stabilité). Nos tests empiriques sont basés sur un modèle International d'évaluation d'actifs financiers (IAPM). Dans ce modèle, le risque de devise est décomposé en deux facteurs représentant les devises des pays industrialisés d'une part, et celles des pays émergents d'autres part. Nos résultats indiquent que le risque de devise est primé et varie à travers le temps pour les portefeuilles stables de risque minimum. De plus ces stratégies conduisent à une réduction significative de l'exposition au risque de change, tandis que la contribution de la prime risque de change reste en moyenne inchangée. Les poids de portefeuille optimaux sont une alternative aux poids de capitalisation boursière. Par conséquent ce chapitre complète la littérature selon laquelle la prime de risque est importante au niveau de l'industrie et au niveau national dans la plupart des pays. Dans le dernier chapitre, nous dérivons une mesure de la prime de risque pour des préférences dépendent du rang et proposons une mesure du degré de pessimisme, étant donné une fonction de distorsion. Les mesures introduites généralisent la mesure de prime de risque dérivée dans le cadre de la théorie de l'utilité espérée, qui est fréquemment violée aussi bien dans des situations expérimentales que dans des situations réelles. Dans la grande famille des préférences considérées, une attention particulière est accordée à la CVaR (valeur à risque conditionnelle). Cette dernière mesure de risque est de plus en plus utilisée pour la construction de portefeuilles et est préconisée pour compléter la VaR (valeur à risque) utilisée depuis 1996 par le comité de Bâle. De plus, nous fournissons le cadre statistique nécessaire pour faire de l’inférence sur les mesures proposées. Pour finir, les propriétés des estimateurs proposés sont évaluées à travers une étude Monte-Carlo, et une illustration empirique en utilisant les rendements journaliers du marché boursier américain sur de la période 2000-2011. / This thesis consists of three chapters on the topics of portfolio choice in a high-dimensional context, and risk measurement. The first chapter addresses the estimation error issue that arises when constructing large portfolios in the mean-variance framework. The second chapter investigates the relevance of currency risk for optimal domestic portfolios, evaluates their ability of to diversify away currency risk, and study the links between portfolio weights stability and currency risk. Finally, under the assumption that decision makers are pessimistic, the third chapter derives the risk premium, propose a measure of the degree of pessimism, and provide a statistical framework for their estimation. The first chapter improves the performance of the optimal portfolio weig-hts obtained under the mean-variance framework of Markowitz (1952). Indeed, these weights give unsatisfactory results, when the mean and variance are replaced by their sample counterparts (plug-in rules). This problem is amplified when the number of assets is large and the sample covariance is singular or nearly singular. The chapter investigates four regularization techniques to stabilizing the inverse of the covariance matrix: the ridge, spectral cut-off, Landweber-Fridman, and LARS Lasso. These four methods involve a tuning parameter that needs to be selected. The main contribution is to derive a data-based method for selecting the tuning parameter in an optimal way, i.e. in order to minimize the expected loss in utility of a mean-variance investor. The cross-validation type criterion derived is found to take a similar form for the four regularization methods. The resulting regularized rules are compared to the sample-based mean-variance portfolio and the naive 1/N strategy in terms of in-sample and out-of-sample Sharpe ratio and expected loss in utility. The main finding is that regularization to covariance matrix significantly improves the performance of the mean-variance problem and outperforms the naive portfolio, especially in ill-posed cases, as suggested by our simulations and empirical studies. In the second chapter, we investigate the extent to which optimal and stable portfolios of domestic assets can reduce or eliminate currency risk. This is done using monthly returns on 48 U.S. industries, from 1976 to 2008. To tackle the instabilities inherent to large portfolios, we use the spectral cut-off regularization described in Chapter 1. This gives rise to a family of stable global minimum portfolios that allows investors to select different percentages of principal components for portfolio construction. Our empirical tests are based on a conditional International Asset Pricing Model (IAPM), augmented with the size and book-to-market factors of Fama and French (1993). Using two trade-weighted currency indices of industrialized countries currencies and emerging markets currencies, we find that currency risk is priced and time-varying for global minimum portfolios. These strategies also lead to a significant reduction in the exposure to currency risk, while keeping the average premium contribution to total premium approximately the same. The global minimum weights considered are an alternative to market capitalization weights used in the U.S. market index. Therefore, our findings complement the well established results that currency risk is significantly priced and economically meaningful at the industry and country level in most countries. Finally, the third chapter derives a measure of the risk premium for rank-dependent preferences and proposes a measure of the degree of pessimism, given a distortion function. The introduced measures generalize the common risk measures derived in the expected utility theory framework, which is frequently violated in both experimental and real-life situations. These measures are derived in the neighborhood of a given random loss variable, using the notion of local utility function. A particular interest is devoted to the CVaR, which is now widely used for asset allocation and has been advocated to complement the Value-at-risk (VaR) proposed since 1996 by the Basel Committee on Banking Supervision. We provide the statistical framework needed to conduct inference on the derived measures. Finally, the proposed estimators

Portfolio selection has a long tradition in financial economics and plays an integral role in investment management. Portfolio selection provides the framework to determine optimal portfolio choice from a universe of available investments. However, the asset weightings from portfolio selection are optimal only if the empirical characteristics of asset returns do not violate the portfolio selection model assumptions. This thesis explores the empirical characteristics of traditional assets and hedge fund returns and examines their effects on the assumptions of linearity-in-the-mean testing and portfolio selection. The encompassing theme of this thesis is the empirical interplay between traditional assets and hedge fund returns. Despite the paucity of hedge fund research, pension funds continue to increase their portfolio allocations to global hedge funds in an effort to pursue higher risk-adjusted returns. This thesis presents three empirical studies which provide positive insights into the relationships between traditional assets and hedge fund returns. The first two empirical studies examine an emerging body of literature which suggests that the relationship between traditional assets and hedge fund returns is non-linear. For mean-variance investors, non-linear asset returns are problematic as they do not satisfy the assumption of linearity required for the covariance matrix in portfolio selection. To examine the linearity assumption as it relates to a mean-variance investor, a hypothesis test approach is employed which investigates the linearity-in-the-mean of traditional assets and hedge funds. The findings from the first two empirical studies reveal that conventional linearity-in-the-mean tests incorrectly conclude that asset returns are nonlinear. We demonstrate that the empirical characteristics of heteroscedasticity and autocorrelation in asset returns are the primary sources of test mis-specification in these linearity-in-the-mean hypothesis tests. To address this problem, an innovative approach is proposed to control heteroscedasticity and autocorrelation in the underlying tests and it is shown that traditional assets and hedge funds are indeed linear-in-the-mean. The third and final study of this thesis explores traditional assets and hedge funds in a portfolio selection framework. Following the theme of the previous two studies, the effects of heteroscedasticity and autocorrelation are examined in the portfolio selection context. The characteristics of serial correlation in bond and hedge fund returns are shown to cause a downward bias in the second sample moment. This thesis proposes two methods to control for this effect and it is shown that autocorrelation induces an overallocation to bonds and hedge funds. Whilst heteroscedasticity cannot be directly examined in portfolio selection, empirical evidence suggests that heteroscedastic events (such as those that occurred in August 1998) translate into the empirical feature known as tail-risk. The effects of tail-risk are examined by comparing the portfolio decisions of mean-variance analysis (MVA) versus mean-conditional value at risk (M-CVaR) investors. The findings reveal that the volatility of returns in a MVA portfolio decreases when hedge funds are included in the investment opportunity set. However, the reduction in the volatility of portfolio returns comes at a cost of undesirable third and fourth moments. Furthermore, it is shown that investors with M-CVaR preferences exhibit a decreasing demand for hedge funds as their aversion for tail-risk increases. The results of the thesis highlight the sensitivities of linearity tests and portfolio selection to the empirical features of heteroscedasticity, autocorrelation and tail-risk. This thesis contributes to the literature by providing refinements to these frameworks which allow improved inferences to be made when hedge funds are examined in linearity and portfolio selection settings.

Basés sur les outils théoriques et algorithmiques de la programmation DC et DCA, les travaux de recherche dans cette thèse portent sur les approches locales et globales pour l'optimisation non convexe et l'optimisation globale en variables mixtes entières. La thèse comporte 5 chapitres. Le premier chapitre présente les fondements de la programmation DC et DCA, et techniques de Séparation et Evaluation (B&B) (utilisant la technique de relaxation DC pour le calcul des bornes inférieures de la valeur optimale) pour l'optimisation globale. Y figure aussi des résultats concernant la pénalisation exacte pour la programmation en variables mixtes entières. Le deuxième chapitre est consacré au développement d'une méthode DCA pour la résolution d'une classe NP-difficile des programmes non convexes non linéaires en variables mixtes entières. Ces problèmes d'optimisation non convexe sont tout d'abord reformulées comme des programmes DC via les techniques de pénalisation en programmation DC de manière que les programmes DC résultants soient efficacement résolus par DCA et B&B bien adaptés. Comme première application en optimisation financière, nous avons modélisé le problème de gestion de portefeuille sous le coût de transaction concave et appliqué DCA et B&B à sa résolution. Dans le chapitre suivant nous étudions la modélisation du problème de minimisation du coût de transaction non convexe discontinu en gestion de portefeuille sous deux formes : la première est un programme DC obtenu en approximant la fonction objectif du problème original par une fonction DC polyèdrale et la deuxième est un programme DC mixte 0-1 équivalent. Et nous présentons DCA, B&B, et l'algorithme combiné DCA-B&B pour leur résolution. Le chapitre 4 étudie la résolution exacte du problème multi-objectif en variables mixtes binaires et présente deux applications concrètes de la méthode proposée. Nous nous intéressons dans le dernier chapitre à ces deux problématiques challenging : le problème de moindres carrés linéaires en variables entières bornées et celui de factorisation en matrices non négatives (Nonnegative Matrix Factorization (NMF)). La méthode NMF est particulièrement importante de par ses nombreuses et diverses applications tandis que les applications importantes du premier se trouvent en télécommunication. Les simulations numériques montrent la robustesse, rapidité (donc scalabilité), performance et la globalité de DCA par rapport aux méthodes existantes. / Based on theoretical and algorithmic tools of DC programming and DCA, the research in this thesis focus on the local and global approaches for non convex optimization and global mixed integer optimization. The thesis consists of 5 chapters. The first chapter presents fundamentals of DC programming and DCA, and techniques of Branch and Bound method (B&B) for global optimization (using the DC relaxation technique for calculating lower bounds of the optimal value). It shall include results concerning the exact penalty technique in mixed integer programming. The second chapter is devoted of a DCA method for solving a class of NP-hard nonconvex nonlinear mixed integer programs. These nonconvex problems are firstly reformulated as DC programs via penalty techniques in DC programming so that the resulting DC programs are effectively solved by DCA and B&B well adapted. As a first application in financial optimization, we modeled the problem pf portfolio selection under concave transaction costs and applied DCA and B&B to its solutions. In the next chapter we study the modeling of the problem of minimization of nonconvex discontinuous transaction costs in portfolio selection in two forms: the first is a DC program obtained by approximating the objective function of the original problem by a DC polyhedral function and the second is an equivalent mixed 0-1 DC program. And we present DCA, B&B algorithm, and a combined DCA-B&B algorithm for their solutions. Chapter 4 studied the exact solution for the multi-objective mixed zero-one linear programming problem and presents two practical applications of proposed method. We are interested int the last chapter two challenging problems: the linear integer least squares problem and the Nonnegative Mattrix Factorization problem (NMF). The NMF method is particularly important because of its many various applications of the first are in telecommunications. The numerical simulations show the robustness, speed (thus scalability), performance, and the globality of DCA in comparison to existent methods.