One of the major problem faced by banks is how to manage the risk exposure in large portfolios. According to Basel II regulation banks has to measure the risk using Value-at-Risk with confidence level 99%. However, this regulation does not specify the way to calculate Valueat- Risk. The easiest way to calculate Value-at-Risk is to assume that portfolio returns are normally distributed. Altough, this is the most common way to calculate Value-at-Risk, there exists also other methods. The previous crisis shows that the regular methods are unfortunately not always enough to prevent bankruptcy. This paper is devoted to compare the classical methods of estimating risk with other methods such as Cornish-Fisher Expansion (CFVaR) and assuming generalized hyperbolic distribution. To be able to do this study, we estimate the risk in a large portfolio consisting of ten stocks. These stocks are chosen from the NASDAQ 100-list in order to have highly liquid stocks (bluechips). The stocks are chosen from different sectors to make the portfolio welldiversified. To investigate the impact of dependence between the stocks in the portfolio we remove the two most correlated stocks and consider the resulting eight stock portfolio as well. In both portfolios we put equal weight to the included stocks. The results show that for a well-diversified large portfolio none of the risk measures are violated. However, for a portfolio consisting of only one highly volatile stock we prove that we have a violation in the classical methods but not when we use the modern methods mentioned above.

This paper links two applications of Extreme Value Theory (EVT) to analyze Taiwanese financial markets: 1. computation of Value at Risk (VaR) and Expected Shortfall (ES) 2. estimates of cross-market dependence under extreme events. Daily data from the Taiwan Stock Exchange Capitalization Weight Stock Index (TAIEX) and the foreign exchange rate, USD/NTD, are employed to analyze the behavior of each return and the dependence structure between the foreign exchange market and the equity market. In the univariate case, when computing risk measures, EVT provides us a more accurate way to estimate VaR. In bivariate case, when measuring extremal dependence, the results of whole period data show the extremal dependence between two markets is asymptotically independent, and the analyses of subperiods illustrate that the relation is slightly dependent in specific periods. Therefore, there is no significant evidence that extreme events appeared in one market (the equity market or the foreign exchange market) will affect another in Taiwan.

為探討臺灣民眾退休不足度，本研究不同以往問卷式詢問臺灣民眾準備狀況，使用所得替代率(replacement rate)為工具，建構估算模型，透過宏利人壽委託政大民調中心進行的民調數據，實際估算勞工與軍公教民眾退休不足度，其中發現台灣有24%勞工民眾在退休後無法達到60%所得替代率，且低估死亡時間與高估報酬率都會對勞工退休不足度造成影響。而對軍公教民眾而言，以80%所得替代率進行估算，才會有退休不足的問題，而低估死亡時間與高估報酬率對退休不足影響較小。此外探討退休信心與實際估算不一致的情況，主要發現高所得的勞工民眾，較可能發生有信心但準備不足60%所得替代率的情況，而低所得的勞工民眾，較可能發生沒有信心但可以準備80%所得替代率的情況，本研究認為是因為臺灣現行退休金制度下，高所得的勞工民眾若要達到相同所得替代率，所需儲蓄率高於低所得的勞工民眾。 / The purpose of this paper is to examine the Retirement Shortfall in Taiwan by using replacement rate. Building model with the poll data which is commissioned by Manulife Life Insurance and conducted by Market Survey Research Center of National Chengchi University, we found that the populations of the civil servants can achieve 60% replacement rate after retirement, but 24 percent of labors can’t reach the 60% income replacement rate. Besides, the retirement shortfall of labors become worse after adjusting by the overestimate of rate of return and underestimate of longevity risk. In short, labor people should contribute more to their pension in case they may have inadequate retirement situation. Using logistic regression, we found that people of high-income have tendency to feel overly optimistic of their retirement shortfall, vice versa. Social security and pension benefit provide less replacement rate for people of high-income, so rich people need highly save rate.

Made available in DSpace on 2010-04-20T21:00:11Z (GMT). No. of bitstreams: 4 Mauricio Mussashi Irie.pdf.jpg: 16022 bytes, checksum: d3dcf1b8020749a12b3baae53334cda5 (MD5) Mauricio Mussashi Irie.pdf.txt: 96735 bytes, checksum: 944036c3b3d1ae823db79daedb65dd6e (MD5) Mauricio Mussashi Irie.pdf: 7355110 bytes, checksum: 880246debd0d864c44768ebd4eaf2e6e (MD5) license.txt: 4886 bytes, checksum: 8fa2d810f5b64e058d76fb4986924cf0 (MD5) Previous issue date: 2009-02-06T00:00:00Z / Este trabalho explora com cuidado o lado específico da implementação de um modelo de alocação de ativos em que o risco é tratado de maneira integrada, não somente através do desvio padrão do portfólio, mas também considerando outras métricas de risco como, por exemplo, o Expected Shortfall. Além disso, utilizamos algumas técnicas de como trabalhar com as variáveis de modo a extrair do mercado os chamados "invariantes de mercado", fenômenos que se repetem e podem ser modelados como variáveis aleatórias independentes e identicamente distribuídas. Utilizamos as distribuições empíricas dos invariantes, juntamente com o método de Cópulas para gerar um conjunto de cenários multivariados simulados de preços. Esses cenários são independentes de distribuição, portanto são não paramétricos. Através dos mesmos, avaliamos a distribuição de retornos simulados de um portfólio através de um índice de satisfação que é baseado em uma função de utilidade quadrática e utiliza o Expected Shortfall como métrica de risco. O índice de satisfação incorpora o trade-off do investidor entre risco e retorno. Finalmente, escolhemos como alocação ótima aquela que maximiza o índice de satisfação ajustado a um parâmetro de aversão ao risco. Perseguindo esses passos, é possível obter um portfólio no qual a alocação em cada ativo, ou classe de ativos, reflete o prêmio esperado ao risco incorrido. / The present work carefully explores the implementation of an asset allocation model in which the risk measure considered is fully integrated, not only through the standard deviation for the portfolio, but also considering other risk metrics, for instance, the Expected Shortfall. Moreover, some statistical tools are used to extract from the market the so called “market invariants”, which are phenomena that tend to repeat themselves and can be modeled as i.i.d. random variables. We use the empirical distribution of the invariants, along with the Method of Copula to generate a set of simulated multivariate price scenarios. These scenarios are independent of distribution, therefore they are non-parametric. With these scenarios we evaluate the simulated return distribution of a portfolio through a satisfaction index which is based on a quadratic utility function and the risk measure considered is the Expected Shortfall. The satisfaction index summarizes the investor trade-off between risk and return. Finally, we choose the optimal allocation that maximizes the satisfaction index adjusted to a risk aversion parameter. In pursuing these steps, it is possible to obtain a portfolio in which the allocation of each asset class or security fully reflects the expected premium to the risk assumed.

Made available in DSpace on 2010-04-20T21:00:37Z (GMT). No. of bitstreams: 3 marceloferreirasantos.pdf.jpg: 18994 bytes, checksum: 6ed4621da38fff28ddcbe493a614c144 (MD5) marceloferreirasantos.pdf: 594325 bytes, checksum: 5a8a7414557d37e5a6d7f21f9a190d47 (MD5) marceloferreirasantos.pdf.txt: 84863 bytes, checksum: 64ea5d2052e93075b4d3e1a6a2ff8b86 (MD5) Previous issue date: 2008-02-08T00:00:00Z / The goal of this work was to show alternatives models to the traditional way of measuring market risk for Brazilian financial assets. In order to cover the maximum possible risk factors in Brazil, we have used the main proxies for Fixed Income products. In times of volatility, market risk management is highly criticized for working in models based on normal distribution. Here it is the best contribution of the VaR and also the greatest criticism of it. In addition, our financial market is characterized by extreme illiquidity in the secondary market in spite of certain governmental bonds. The first stage was to research academic production about the theme in Brazil or worldwide. To our surprise, little has been said in country about stable distribution applied to financial market, whether in risk management, options pricing, or portfolio management. After this step, we selected a set of variables to be used aiming to cover a large part of Brazilian financial assets. Thus, we were able to identify or not a presence of normality condition so that we could model risk measure, VaR and ES, for chosen assets. The theoretical and practical conditions were created: market demand (heavy criticisms of Gausian approach), ample selection of assets (in spite of eventual doubts about liquidity), academic experience, and international knowledge (by means of detailed and meticulous study of the production about the theme in the main circles). In this way, four principal approaches have been analyzed in order to calculate risk measures whether they be coherent or not. It is important to mention that this work might be useful for large initiatives, for example, those which incorporate several assets within linear risk portfolios or, even, for non-linear portfolios. / O objetivo deste trabalho foi mostrar modelagens alternativas à tradicional maneira de se apurar o risco de mercado para ativos financeiros brasileiros. Procurou-se cobrir o máximo possível de fatores de risco existentes no Brasil; para tanto utilizamos as principais proxies para instrumentos de Renda Fixa. Em momentos de volatilidade, o gerenciamento de risco de mercado é bastante criticado por trabalhar dentro de modelagens fundamentadas na distribuição normal. Aqui reside a maior contribuição do VaR e também a maior crítica a ele. Adicionado a isso, temos um mercado caracterizado pela extrema iliquidez no mercado secundário até mesmo em certos tipos de títulos públicos federais. O primeiro passo foi fazer um levantamento da produção acadêmica sobre o tema, seja no Brasil ou no mundo. Para a nossa surpresa, pouco, no nosso país, tem se falado em distribuições estáveis aplicadas ao mercado financeiro, seja em gerenciamento de risco, precificação de opções ou administração de carteiras. Após essa etapa, passamos a seleção das variáveis a serem utilizadas buscando cobrir uma grande parte dos ativos financeiros brasileiros. Assim, deveríamos identificar a presença ou não da condição de normalidade para, aí sim, realizarmos as modelagens das medidas de risco, VaR e ES, para os ativos escolhidos, As condições teóricas e práticas estavam criadas: demanda de mercado (crítica ao método gausiano bastante difundido), ampla cobertura de ativos (apesar do eventual questionamento da liquidez), experiência acadêmica e conhecimento internacional (por meio de detalhado e criterioso estudo da produção sobre o tema nos principais meios). Analisou-se, desta forma, quatro principais abordagens para o cálculo de medidas de risco sendo elas coerentes (ES) ou não (VaR). É importante mencionar que se trata de um trabalho que poderá servir de insumo inicial para trabalhos mais grandiosos, por exemplo, aqueles que incorporarem vários ativos dentro de uma carteira de riscos lineares ou, até mesmo, para ativos que apresentem risco não-direcionais.

The biodiversity is distributed heterogeneously across the Earth. Although the discussion about which factors determine the spatial patterns of species diversity remains controversial, to know the components of biodiversity themselves is a challenge even bigger in certain regions. So, to know how much still remains to be studied or discovered is fundamental to the science, and the lack of knowledge about the species geographical distribution is known as one of the main problems faced in biodiversity research, especially in “Megadiverse” countries like Brazil. Historically, the Caatinga biome has been recognized as one of the most unknown and less valued according to its biodiversity, because the erroneous idea that the biome would have low diversity and endemism rates, and high degrees of degradation. Considering the dominance of the Family Fabaceae in the Caatinga, in both richness and abundance, we investigated the spatial pattern of Fabaceae species richness on the biome looking for determine which are the factors responsible for the spatial variation on its species richness. Moreover, we elaborated a spatial statistical model for the diversity of Fabaceae in the Caatinga, utilizing the spatial structure of the know assemblages and their environmental determinants, in order to estimate the shortfall of knowledge about the distribution (Wallacean shortfall) of the family in the Caatinga. We obtained 220,781 registers, less than 25% were valid. From these registers, we found 1,310 species in 198 genera. The predict richness vary from 92 to 283 species across the space and was better described by the sampling effort, the soil properties and the topography. With the measure of discrepancy between predicted and the observed values of species richness, we estimated the Wallacean shortfall, reaching 192 species in one single locality. The total number of species found in this work represents an expressive improvement on the know species richness of the family in the Caatinga. The selection of non-climatic factors as the main predictors of richness indicate the major influence of topography and soil on regional scale. The importance of substrate on the establishment of plant communities on the semiarid, as well. The estimated Wallacean shortfall evidences a chronical and spatially heterogeneous deficiency on knowledge of the regional flora. The persistence of such expressive gaps on the knowledge, plus the reduced coverage of protected areas on the biome shows a currently risk of significantly losses of biological diversity, with serious implications for the conservation of the biome. / A biodiversidade é distribuída de forma heterogênea através do planeta Terra. Embora a discussão sobre quais fatores determinam os padrões espaciais da biodiversidade continue controversa, o simples conhecimento dos seus componentes é um desafio ainda maior em algumas regiões. Assim, conhecer o quanto ainda há para ser estudado ou descoberto é fundamental para a ciência, e a falta de conhecimento sobre a distribuição geográfica das espécies é considerado um dos principais problemas enfrentados em estudos sobre a biodiversidade, especialmente em países “megadiversos” como o Brasil. O Bioma Caatinga tem sido historicamente reconhecido com um dos menos conhecidos e valorizados quanto a diversidade biológica, devido à ideia equivocada de sua baixa diversidade e endemismo e elevado grau de antropização. Considerando a dominância da família Fabaceae na Caatinga, quanto à riqueza e abundância regional, investigamos o padrão espacial da riqueza de espécies de Fabaceae no bioma, buscando determinar quais os fatores ambientais responsáveis pela variação espacial da sua riqueza de espécies. Além disso, elaboramos um modelo estatístico espacial de diversidade de Fabaceae na Caatinga a partir da estrutura espacial das assembleias conhecidas e dos seus determinantes ambientais, a fim de estimar o déficit de conhecimento sobre a distribuição (déficit wallaceano) da Família na Caatinga. Obtivemos 220.781 registros, dos quais menos de 25% foram válidos. A partir desses registros, encontramos o total de 1.310 espécies de 198 gêneros. A riqueza predita pelo modelo espacial variou de 92 a 283 espécies ao longo do espaço e foi melhor descrita pelo esforço amostral, aspectos do solo e topografia. A partir da medida de discrepância entre valores preditos e observados de riqueza de espécies, estimamos valores de déficit Wallaceano, chegando a 192 espécies em uma única localidade. O número total de espécies encontrado neste trabalho representa um incremento expressivo na riqueza conhecida de espécies da família na Caatinga. A seleção de fatores não climático como principais preditores de riqueza indica maior influência da topografia e do solo na escala regional. E também a importância do substrato no estabelecimento de comunidades vegetais no semiárido. O déficit Wallaceano estimado evidencia uma deficiência crônica e espacialmente heterogênea no conhecimento da flora regional. A persistência de lacunas tão expressivas no conhecimento, somada a cobertura reduzida de áreas protegidas no Bioma evidencia um risco corrente de perdas significativas de diversidade biológica com sérias implicações para a conservação do Bioma.

Submitted by Camila Corrêa Moraes (camila.cmoraes@gmail.com) on 2013-02-24T03:00:19Z No. of bitstreams: 1 DISSERTAÇÃO CAMILA MORAES.pdf: 4708711 bytes, checksum: 3c2acb024f3dbcde7627bb8afea462fd (MD5) / Rejected by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br), reason: Prezada Camila, Seu titulo não confere com a Ata, não podemos aprovar o trabalho, pois não temos informação do orientador (verso da Ata) da mudança do título. Aguardo email do seu orientador informando a alteração e posteriormente o professor deve assinar o verso da ata. Att. Suzi 3799-7876 on 2013-02-25T15:26:27Z (GMT) / Submitted by Camila Corrêa Moraes (camila.cmoraes@gmail.com) on 2013-02-26T17:46:32Z No. of bitstreams: 1 DISSERTAÇÃO CAMILA MORAES.pdf: 4708711 bytes, checksum: 3c2acb024f3dbcde7627bb8afea462fd (MD5) / Approved for entry into archive by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br) on 2013-02-26T17:50:59Z (GMT) No. of bitstreams: 1 DISSERTAÇÃO CAMILA MORAES.pdf: 4708711 bytes, checksum: 3c2acb024f3dbcde7627bb8afea462fd (MD5) / Made available in DSpace on 2013-02-26T18:41:00Z (GMT). No. of bitstreams: 1 DISSERTAÇÃO CAMILA MORAES.pdf: 4708711 bytes, checksum: 3c2acb024f3dbcde7627bb8afea462fd (MD5) Previous issue date: 2013-01-29 / Value at Risk (VaR) and Expected Shortfall (ES) are quantitative models to measure market risk of financial assets portfolios. The purpose of this study is to evaluate the results of these models for a portfolio traded in the Brazilian market through four backtesting methods - Basel Traffic Light Test, Kupiec Test, Christoffersen Test and McNeil and Frey Test - covering periods of domestic (2002) and international (2008) financial crisis. The VaR model described here presents two approaches - Parametric, where it is assumed that the distribution of asset returns follow a Normal, and Historical Simulation, where there are no assumption about the distribution of asset returns, but it is assumed that they are independent and identically distributed. The results of VaR were also evaluated with the Cornish-Fisher expansion, which tries to approximate the empirical distribution to a Normal distribution using the values of skewness and kurtosis. Another feature observed was the property of coherence, which evaluates if the risk measure follows four basic axioms - monotonicity, translation invariance, homogeneity and subadditivity. VaR is not considered a coherent risk measure because it doesn´t follow the subadditivity feature in all cases. On the other hand the ES follows the four axioms, thus considered a coherent risk measure. The ES model was evaluated according to the Parametric Normal approach. This work also verified through backtests, if the property of coherency improves the accuracy of the analyzed risk measures / Value at Risk (VaR) e Expected Shortfall (ES) são modelos quantitativos para mensuração do risco de mercado em carteiras de ativos financeiros. O propósito deste trabalho é avaliar os resultados de tais modelos para ativos negociados no mercado brasileiro através de quatro metodologias de backtesting - Basel Traffic Light Test, Teste de Kupiec, Teste de Christoffersen e Teste de McNeil e Frey – abrangendo períodos de crise financeira doméstica (2002) e internacional (2008). O modelo de VaR aqui apresentado utilizou duas abordagens – Paramétrica Normal, onde se assume que a distribuição dos retornos dos ativos segue uma Normal, e Simulação Histórica, onde não há hipótese a respeito da distribuição dos retornos dos ativos, porém assume-se que os mesmos são independentes e identicamente distribuídos. Também foram avaliados os resultados do VaR com a expansão de Cornish-Fisher, a qual visa aproximar a distribuição empírica a uma distribuição Normal utilizando os valores de curtose e assimetria para tal. Outra característica observada foi a propriedade de coerência, a qual avalia se a medida de risco obedece a quatro axiomas básicos – monotonicidade, invariância sob translações, homogeneidade e subaditividade. O VaR não é considerado uma medida de risco coerente, pois não apresenta a característica de subaditividade em todos os casos. Por outro lado o ES obedece aos quatro axiomas, considerado assim uma medida coerente. O modelo de ES foi avaliado segundo a abordagem Paramétrica Normal. Neste trabalho também se verificou através dos backtests, o quanto a propriedade de coerência de uma medida de risco melhora sua precisão.

In der Dissertation wurde ein innovatives Portfoliomodell entwickelt, welches den Präferenzen einer großen Gruppe von Investoren entspricht, die mit der traditionellen Portfolio Selektion auf Basis von Mittelwertrendite und Varianz nicht zufrieden sind. Vor allem bezieht sich die Unzufriedenheit auf eine sehr spezifische Definition der Risiko- und Wertmaße, die angenommene Nutzenfunktion, die Risikodiversifizierung sowie die Beschränkung des Assetuniversums. Dies erschwert vor allem die Optimierung der modernen Finanzprodukte. Das im Modell verwendete Risikomaß-Ausfallrisiko drückt die Präferenzen der Investoren im Bereich unterhalb der Renditebenchmark aus. Die Renditenabweichung von der Benchmark nach oben werden nicht, wie im Falle des Mittelwertrendite-Varianz-Portfoliomodells, minimiert oder als risikoneutral, wie bei dem Mittelwertrendite-Ausfallrisiko-Portfoliomodell, betrachtet. Stattdessen wird ein Wertmaß, das Chance-Potenzial (Upper Partial Moment), verwendet, mit welchem verschiedene Investorenwünsche in diesem Bereich darstellbar sind. Die Eliminierung der Annahme der normalverteilten Renditen in diesem Chance-Potenzial-Ausfallrisiko-Portfoliomodell erlaubt eine korrekte Asset Allokation auch im Falle der nicht normalverteilten Renditen, die z. B. Finanzderivate, Aktien, Renten und Immobilien zu finden sind. Bei diesen tendiert das traditionelle Mittelwertrendite-Varianz-Portfoliomodell zu suboptimalen Entscheidungen. Die praktische Anwendung des Chance-Potenzial-Ausfallrisiko-Portfoliomodells wurde am Assetuniversum von Covered Calls, Protective Puts und Aktien gezeigt. / This thesis presents an innovative portfolio model appropriate for a large group of investors which are not content with the asset allocation with the traditional, mean return-variance based portfolio model above all in term of its rather specific definition of the risk and value decision parameters, risk diversification, related utility function and its restrictions imposed on the asset universe. Its modifiable risk measure ─ shortfall risk ─ expresses variable risk preferences below the return benchmark. The upside return deviations from the benchmark are not minimized as in case of the mean return-variance portfolio model or considered risk neutral as in the mean return-shortfall risk portfolio model, but employs variable degrees of the chance potential (upper partial moments) in order to provide investors with broader range of utility choices and so reflect arbitrary preferences. The elimination of the assumption of normally distributed returns in the chance potential-shortfall risk model allows correct allocation of assets with non-normally distributed returns as e.g. financial derivatives, equities, real estates, fixed return assets, commodities where the mean-variance portfolio model tends to inferior asset allocation decisions. The computational issues of the optimization algorithm developed for the mean-variance, mean-shortfall risk and chance potential-shortfall risk portfolio selection are described to ease their practical application. Additionally, the application of the chance potential-shortfall risk model is shown on the asset universe containing stocks, covered calls and protective puts.

In der Dissertation wurde ein innovatives Portfoliomodell entwickelt, welches den Präferenzen einer großen Gruppe von Investoren entspricht, die mit der traditionellen Portfolio Selektion auf Basis von Mittelwertrendite und Varianz nicht zufrieden sind. Vor allem bezieht sich die Unzufriedenheit auf eine sehr spezifische Definition der Risiko- und Wertmaße, die angenommene Nutzenfunktion, die Risikodiversifizierung sowie die Beschränkung des Assetuniversums. Das im Modell verwendete Risikomaß-Ausfallrisiko drückt die Präferenzen der Investoren im Bereich unterhalb der Renditebenchmark aus. Die Renditenabweichung von der Benchmark nach oben werden nicht, wie im Falle des Mittelwertrendite-Varianz-Portfoliomodells, minimiert oder als risikoneutral, wie bei dem Mittelwertrendite-Ausfallrisiko-Portfoliomodell, betrachtet. Stattdessen wird ein Wertmaß, das Chance-Potenzial (Upper Partial Moment), verwendet, mit welchem verschiedene Investorenwünsche in diesem Bereich darstellbar sind. Die Eliminierung der Annahme der normalverteilten Renditen in diesem Chance-Potenzial-Ausfallrisiko-Portfoliomodell erlaubt eine korrekte Asset Allokation auch im Falle der nicht normalverteilten Renditen, die z. B. Finanzderivate, Aktien, Renten und Immobilien zu finden sind. Bei diesen tendiert das traditionelle Mittelwertrendite-Varianz-Portfoliomodell zu suboptimalen Entscheidungen. Die praktische Anwendung des Chance-Potenzial-Ausfallrisiko-Portfoliomodells wurde am Assetuniversum von Covered Calls, Protective Puts und Aktien gezeigt. / This thesis presents an innovative portfolio model appropriate for a large group of investors which are not content with the asset allocation with the traditional, mean return-variance based portfolio model above all in term of its rather specific definition of the risk and value decision parameters, risk diversification, related utility function and its restrictions imposed on the asset universe. Its modifiable risk measure – shortfall risk – expresses variable risk preferences below the return benchmark. The upside return deviations from the benchmark are not minimized as in case of the mean return-variance portfolio model or considered risk neutral as in the mean return-shortfall risk portfolio model, but employs variable degrees of the chance potential (upper partial moments) in order to provide investors with broader range of utility choices and so reflect arbitrary preferences. The elimination of the assumption of normally distributed returns in the chance potential-shortfall risk model allows correct allocation of assets with non-normally distributed returns as e.g. financial derivatives, equities, real estates, fixed return assets, commodities where the mean-variance portfolio model tends to inferior asset allocation decisions. The computational issues of the optimization algorithm developed for the mean-variance, mean-shortfall risk and chance potential-shortfall risk portfolio selection are described to ease their practical application. Additionally, the application of the chance potential-shortfall risk model is shown on the asset universe containing stocks, covered calls and protective puts.

In der Dissertation wurde ein innovatives Portfoliomodell entwickelt, welches den Präferenzen einer großen Gruppe von Investoren entspricht, die mit der traditionellen Portfolio Selektion auf Basis von Mittelwertrendite und Varianz nicht zufrieden sind. Vor allem bezieht sich die Unzufriedenheit auf eine sehr spezifische Definition der Risiko- und Wertmaße, die angenommene Nutzenfunktion, die Risikodiversifizierung sowie die Beschränkung des Assetuniversums. Dies erschwert vor allem die Optimierung der modernen Finanzprodukte. Das im Modell verwendete Risikomaß-Ausfallrisiko drückt die Präferenzen der Investoren im Bereich unterhalb der Renditebenchmark aus. Die Renditenabweichung von der Benchmark nach oben werden nicht, wie im Falle des Mittelwertrendite-Varianz-Portfoliomodells, minimiert oder als risikoneutral, wie bei dem Mittelwertrendite-Ausfallrisiko-Portfoliomodell, betrachtet. Stattdessen wird ein Wertmaß, das Chance-Potenzial (Upper Partial Moment), verwendet, mit welchem verschiedene Investorenwünsche in diesem Bereich darstellbar sind. Die Eliminierung der Annahme der normalverteilten Renditen in diesem Chance-Potenzial-Ausfallrisiko-Portfoliomodell erlaubt eine korrekte Asset Allokation auch im Falle der nicht normalverteilten Renditen, die z. B. Finanzderivate, Aktien, Renten und Immobilien zu finden sind. Bei diesen tendiert das traditionelle Mittelwertrendite-Varianz-Portfoliomodell zu suboptimalen Entscheidungen. Die praktische Anwendung des Chance-Potenzial-Ausfallrisiko-Portfoliomodells wurde am Assetuniversum von Covered Calls, Protective Puts und Aktien gezeigt. / This thesis presents an innovative portfolio model appropriate for a large group of investors which are not content with the asset allocation with the traditional, mean return-variance based portfolio model above all in term of its rather specific definition of the risk and value decision parameters, risk diversification, related utility function and its restrictions imposed on the asset universe. Its modifiable risk measure – shortfall risk – expresses variable risk preferences below the return benchmark. The upside return deviations from the benchmark are not minimized as in case of the mean return-variance portfolio model or considered risk neutral as in the mean return-shortfall risk portfolio model, but employs variable degrees of the chance potential (upper partial moments) in order to provide investors with broader range of utility choices and so reflect arbitrary preferences. The elimination of the assumption of normally distributed returns in the chance potential-shortfall risk model allows correct allocation of assets with non-normally distributed returns as e.g. financial derivatives, equities, real estates, fixed return assets, commodities where the mean-variance portfolio model tends to inferior asset allocation decisions. The computational issues of the optimization algorithm developed for the mean-variance, mean-shortfall risk and chance potential-shortfall risk portfolio selection are described to ease their practical application. Additionally, the application of the chance potential-shortfall risk model is shown on the asset universe containing stocks, covered calls and protective puts.