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Submitted by Marcela Zuppini (marcela.zuppini@gmail.com) on 2018-09-17T15:29:45Z No. of bitstreams: 1 Dissertacao-MarcelaZuppini.pdf: 981569 bytes, checksum: 5370718f173516ac989c81abc20caba1 (MD5) / Approved for entry into archive by Joana Martorini (joana.martorini@fgv.br) on 2018-09-17T18:01:06Z (GMT) No. of bitstreams: 1 Dissertacao-MarcelaZuppini.pdf: 981569 bytes, checksum: 5370718f173516ac989c81abc20caba1 (MD5) / Approved for entry into archive by Suzane Guimarães (suzane.guimaraes@fgv.br) on 2018-09-18T14:11:35Z (GMT) No. of bitstreams: 1 Dissertacao-MarcelaZuppini.pdf: 981569 bytes, checksum: 5370718f173516ac989c81abc20caba1 (MD5) / Made available in DSpace on 2018-09-18T14:11:35Z (GMT). No. of bitstreams: 1 Dissertacao-MarcelaZuppini.pdf: 981569 bytes, checksum: 5370718f173516ac989c81abc20caba1 (MD5) Previous issue date: 2018-08-20 / A marcação a mercado de ativos ilíquidos é um desafio, dada a escassez de informações e negociações no mercado que possam indicar qual deve ser o seu preço justo. As debêntures, que são ativos de renda fixa do mercado brasileiro, são marcadas a mercado descontando-se os fluxos futuros do papel a valor presente. Quando as debêntures são ilíquidas, a dificuldade na determinação do valor justo está em encontrar o fator de desconto apropriado, ou seja, qual é o spread apropriado para o ativo. Este trabalho busca determinar o spread de debêntures ilíquidas com base nas suas características, nas informações sobre a saúde financeira dos emissores e na situação do mercado. As ferramentas utilizadas para esse fim são modelagem por redes neurais e clustering. Como base de comparação para os resultados obtidos, é utilizada regressão linear múltipla. / Market marking of illiquid assets is a challenge, given the scarcity of information and negotiations in the market that can indicate what the fair price should be. The debentures, which are fixed income assets of the Brazilian market, are marked to market discounting the future flows of paper to present value. When debentures are illiquid, the difficulty in determining fair value lies in finding the appropriate discount factor, i.e., what is the appropriate spread for the asset. This study seeks to determine the spread of illiquid debentures based on their characteristics, the information on the financial health of the issuers and the market situation. The tools used for this purpose are neural network modeling and clustering. Multiple linear regression is used as the basis of comparison for the obtained results.

Despite the fact that illiquid assets pose several difficulties regarding portfolio allocation problems for investors, more investors are increasing their allocation towards them. Alternative assets are characterized as being harder to value and trade because of their illiquidity which raises the question of how they should be managed from an allocation optimization perspective. In an attempt to demystify the illiquidity conundrum, shadow allocations are attached to the classical mean-variance framework to account for liquidity activities. The framework is further improved by replacing the variance for the coherent risk measure conditional value at risk (CVaR). This framework is then used to first stress test and optimize a theoretical portfolio and then analyze real-world data in a case study. The investors’ liquidity preferences are based on common institutional investors such as Foundations & Charities, Pension Funds, and Unions. The theoretical results support previous findings of the shadow allocations framework and decrease the allocation towards illiquid assets, while the results of the case study do not support the shadow allocations framework. / Trots det faktum att illikvida tillgångar medför flera svårigheter när det gäller portföljallokeringsproblem för investerare, så ökar allt fler investerare sin allokering mot dem. Alternativa tillgångar kännetecknas av att de är svårare att värdera och handla på grund av sin illikviditet, vilket väcker frågan om hur de ska hanteras ur ett allokeringsoptimeringsperspektiv. I ett försök att avmystifiera illikviditetsproblemet adderas skuggallokeringar till det klassiska ramverket för modern portföljteori för att ta hänsyn till likviditetsaktiviteter. Ramverket förbättras ytterligare genom att ersätta variansen mot det koherenta riskmåttet CVaR. Detta ramverk används sedan för att först stresstesta och optimera en teoretisk portfölj, och sedan analysera verkliga data i en fallstudie. Investerarnas likviditetspreferenser baseras på vanliga institutionella investerare såsom stiftelser & välgörenhetsorganisationer, pensionsfonder samt fackföreningar. De teoretiska resultaten stödjer tidigare forskning om ramverket för skuggallokeringer och sänker allokeringen mot illikvida tillgångar, samtidigt som resultaten från fallstudien inte stödjer ramverket för skuggallokeringar.

Notre thèse consiste à expliquer, en apportant quelques éléments théoriques, les imperfections des stress tests macro-prudentiels d’EBA/BCE, et de proposer une nouvelle méthodologie de leur application ainsi que deux stress tests spécifiques en complément. Nous montrons que les stress tests macro-prudentiels peuvent être non pertinents lorsque les deux hypothèses fondamentales du modèle de base de Gordy-Vasicek utilisé pour évaluer le capital réglementaire des banques en méthodes internes (IRB) dans le cadre du risque de crédit (portefeuille de crédit asymptotiquement granulaire et présence d’une seule source de risque systématique qui est la conjoncture macro-économique), ne sont pas respectées. Premièrement, ils existent des portefeuilles concentrés pour lesquels les macro-stress tests ne sont pas suffisants pour mesurer les pertes potentielles, voire inefficaces si ces portefeuilles impliquent des contreparties non cycliques. Deuxièmement, le risque systématique peut provenir de plusieurs sources ; le modèle actuel à un facteur empêche la répercussion propre des chocs « macro ».Nous proposons un stress test spécifique de crédit qui permet d’appréhender le risque spécifique de crédit d’un portefeuille concentré, et un stress test spécifique de liquidité qui permet de mesurer l’impact des chocs spécifiques de liquidité sur la solvabilité de la banque. Nous proposons aussi une généralisation multifactorielle de la fonction d’évaluation du capital réglementaire en IRB, qui permet d’appliquer les chocs des macro-stress tests sur chaque portefeuille sectoriel, en stressant de façon claire, précise et transparente les facteurs de risque systématique l’impactant. Cette méthodologie permet une répercussion propre de ces chocs sur la probabilité de défaut conditionnelle des contreparties de ces portefeuilles et donc une meilleure évaluation de la charge en capital de la banque. / Our thesis consists in explaining, by bringing some theoretical elements, the imperfections of EBA / BCE macro-prudential stress tests, and proposing a new methodology of their application as well as two specific stress tests in addition. We show that macro-prudential stress tests may be irrelevant when the two basic assumptions of the Gordy-Vasicek core model used to assess banks regulatory capital in internal methods (IRB) in the context of credit risk (asymptotically granular credit portfolio and presence of a single source of systematic risk which is the macroeconomic conjuncture), are not respected. Firstly, they exist concentrated portfolios for which macro-stress tests are not sufficient to measure potential losses or even ineffective in the case where these portfolios involve non-cyclical counterparties. Secondly, systematic risk can come from several sources; the actual one-factor model doesn’t allow a proper repercussion of the “macro” shocks. We propose a specific credit stress test which makes possible to apprehend the specific credit risk of a concentrated portfolio, as well as a specific liquidity stress test which makes possible to measure the impact of liquidity shocks on the bank’s solvency. We also propose a multifactorial generalization of the regulatory capital valuation model in IRB, which allows applying macro-stress tests shocks on each sectorial portfolio, stressing in a clear, precise and transparent way the systematic risk factors impacting it. This methodology allows a proper impact of these shocks on the conditional probability of default of the counterparties of these portfolios and therefore a better evaluation of the capital charge of the bank.