Measuring fund performance using multi-factor models: evidence for the Portuguese market

This paper examines the performance of Portuguese equity funds investing in the domestic and in the European Union market, using several unconditional and conditional multi-factor models. In terms of overall performance, we find that National funds are neutral performers, while European Union funds under-perform the market significantly. These results do not seem to be a consequence of management fees. Overall, our findings are supportive of the robustness of conditional multi-factor models. In fact, Portuguese equity funds seem to be relatively more exposed to smallcaps and more value-oriented. Also, they present strong evidence of time-varying betas and, in the case of the European Union funds, of time-varying alphas too. Finally, in terms of market timing, our tests suggest that mutual fund managers in our sample do not exhibit any market timing abilities. Nevertheless, we find some evidence of timevarying conditional market timing abilities but only at the individual fund level.

Aspectes metodològics i aplicacions de la modelització del temps de supervivència multivariant mitjançant models mixtes

Els estudis de supervivència s'interessen pel temps que passa des de l'inici de l'estudi (diagnòstic de la malaltia, inici del tractament,...) fins que es produeix l'esdeveniment d'interès (mort, curació, millora,...). No obstant això, moltes vegades aquest esdeveniment s'observa més d'una vegada en un mateix individu durant el període de seguiment (dades de supervivència multivariant). En aquest cas, és necessari utilitzar una metodologia diferent a la utilitzada en l'anàlisi de supervivència estàndard. El principal problema que l'estudi d'aquest tipus de dades comporta és que les observacions poden no ser independents. Fins ara, aquest problema s'ha solucionat de dues maneres diferents en funció de la variable dependent. Si aquesta variable segueix una distribució de la família exponencial s'utilitzen els models lineals generalitzats mixtes (GLMM); i si aquesta variable és el temps, variable amb una distribució de probabilitat no pertanyent a aquesta família, s'utilitza l'anàlisi de supervivència multivariant. El que es pretén en aquesta tesis és unificar aquests dos enfocs, és a dir, utilitzar una variable dependent que sigui el temps amb agrupacions d'individus o d'observacions, a partir d'un GLMM, amb la finalitat d'introduir nous mètodes pel tractament d'aquest tipus de dades.

The conditional performance of euro bond funds: evidence from Portugal during the debt crisis

This paper evaluates the performance of a survivorship bias-free data set of Portuguese funds investing in Euro-denominated bonds by using conditional models that consider the public information available to investors when the returns are generated. We find that bond funds underperform the market significantly and by an economically relevant magnitude. This underperformance cannot be explained by the expenses they charge. Our findings support the use of conditional performance evaluation models, since we find strong evidence of both time-varying risk and performance, dependent on the slope of the term structure and the inverse relative wealth variables. We also show that survivorship bias has a significant impact on performance estimates. Furthermore, during the European debt crisis, bond fund managers performed significantly better than in non-crisis periods and were able to achieve neutral performance. This improved performance throughout the crisis seems to be related to changes in funds’ investment styles.

Conditioning information in mutual fund performance evaluation: Portuguese evidence

We estimate and compare the performance of Portuguese-based mutual funds that invest in the domestic market and in the European market using unconditional and conditional models of performance evaluation. Besides applying both partial and full conditional models, we use European information variables, instead of the most common local ones, and consider stochastically detrended conditional variables in order to avoid spurious regressions. The results suggest that mutual fund managers are not able to outperform the market, presenting negative or neutral performance. The incorporation of conditioning information in performance evaluation models is supported by our findings, as it improves the explanatory power of the models and there is evidence of both time-varying betas and alphas related to the public information variables. It is also shown that the number of lags to be used in the stochastic detrending procedure is a critical choice, as it will impact the significance of the conditioning information. In addition, we observe a distance effect, since managers who invest locally seem to outperform those who invest in the European market. However, after controlling for public information, this effect is slightly reduced. Furthermore, the results suggest that survivorship bias has a small impact on performance estimates.

Avaliação do desempenho de fundos de investimento de obrigações: evidência para o mercado Brasileiro

Dissertação de mestrado em Finanças

Avaliação do desempenho de fundos de investimento de ouro nos EUA: influência dos diferentes regimes de mercado na seletividade e market-timing

Dissertação de mestrado em Finanças

Os fatores de risco da rendibilidade das ações: análise e evidência empírica em países da Zona Euro

Tese de Doutoramento em Ciências Empresariais.

Modelling structural zeros in compositional data

This analysis was stimulated by the real data analysis problem of householdexpenditure data. The full dataset contains expenditure data for a sample of 1224 households. The expenditure is broken down at 2 hierarchical levels: 9 major levels (e.g. housing, food, utilities etc.) and 92 minor levels. There are also 5 factors and 5 covariates at the household level. Not surprisingly, there are a small number of zeros at the major level, but many zeros at the minor level. The question is how best to model the zeros. Clearly, models that tryto add a small amount to the zero terms are not appropriate in general as at least some of the zeros are clearly structural, e.g. alcohol/tobacco for households that are teetotal. The key question then is how to build suitable conditional models. For example, is the sub-composition of spendingexcluding alcohol/tobacco similar for teetotal and non-teetotal households?In other words, we are looking for sub-compositional independence. Also, what determines whether a household is teetotal? Can we assume that it is independent of the composition? In general, whether teetotal will clearly depend on the household level variables, so we need to be able to model this dependence. The other tricky question is that with zeros on more than onecomponent, we need to be able to model dependence and independence of zeros on the different components. Lastly, while some zeros are structural, others may not be, for example, for expenditure on durables, it may be chance as to whether a particular household spends money on durableswithin the sample period. This would clearly be distinguishable if we had longitudinal data, but may still be distinguishable by looking at the distribution, on the assumption that random zeros will usually be for situations where any non-zero expenditure is not small.While this analysis is based on around economic data, the ideas carry over tomany other situations, including geological data, where minerals may be missing for structural reasons (similar to alcohol), or missing because they occur only in random regions which may be missed in a sample (similar to the durables)

Identification of renin progenitors in the mouse bone marrow that give rise to B-cell leukaemia

cell of origin and triggering events for leukaemia are mostly unknown. Here we show that the bone marrow contains a progenitor that expresses renin throughout development and possesses a B-lymphocyte pedigree. This cell requires RBP-J to differentiate. Deletion of RBP-J in these renin-expressing progenitors enriches the precursor B-cell gene programme and constrains lymphocyte differentiation, facilitated by H3K4me3 activating marks in genes that control the pre-B stage. Mutant cells undergo neoplastic transformation, and mice develop a highly penetrant B-cell leukaemia with multi-organ infiltration and early death. These reninexpressing cells appear uniquely vulnerable as other conditional models of RBP-J deletion do not result in leukaemia. The discovery of these unique renin progenitors in the bone marrow and the model of leukaemia described herein may enhance our understanding of normal and neoplastic haematopoiesis.

Maximum Entropy Discrimination

We present a general framework for discriminative estimation based on the maximum entropy principle and its extensions. All calculations involve distributions over structures and/or parameters rather than specific settings and reduce to relative entropy projections. This holds even when the data is not separable within the chosen parametric class, in the context of anomaly detection rather than classification, or when the labels in the training set are uncertain or incomplete. Support vector machines are naturally subsumed under this class and we provide several extensions. We are also able to estimate exactly and efficiently discriminative distributions over tree structures of class-conditional models within this framework. Preliminary experimental results are indicative of the potential in these techniques.

Modelling structural zeros in compositional data

This analysis was stimulated by the real data analysis problem of household expenditure data. The full dataset contains expenditure data for a sample of 1224 households. The expenditure is broken down at 2 hierarchical levels: 9 major levels (e.g. housing, food, utilities etc.) and 92 minor levels. There are also 5 factors and 5 covariates at the household level. Not surprisingly, there are a small number of zeros at the major level, but many zeros at the minor level. The question is how best to model the zeros. Clearly, models that try to add a small amount to the zero terms are not appropriate in general as at least some of the zeros are clearly structural, e.g. alcohol/tobacco for households that are teetotal. The key question then is how to build suitable conditional models. For example, is the sub-composition of spending excluding alcohol/tobacco similar for teetotal and non-teetotal households? In other words, we are looking for sub-compositional independence. Also, what determines whether a household is teetotal? Can we assume that it is independent of the composition? In general, whether teetotal will clearly depend on the household level variables, so we need to be able to model this dependence. The other tricky question is that with zeros on more than one component, we need to be able to model dependence and independence of zeros on the different components. Lastly, while some zeros are structural, others may not be, for example, for expenditure on durables, it may be chance as to whether a particular household spends money on durables within the sample period. This would clearly be distinguishable if we had longitudinal data, but may still be distinguishable by looking at the distribution, on the assumption that random zeros will usually be for situations where any non-zero expenditure is not small. While this analysis is based on around economic data, the ideas carry over to many other situations, including geological data, where minerals may be missing for structural reasons (similar to alcohol), or missing because they occur only in random regions which may be missed in a sample (similar to the durables)

Discrete and continuous compositions

This paper examines a dataset which is modeled well by the Poisson-Log Normal process and by this process mixed with Log Normal data, which are both turned into compositions. This generates compositional data that has zeros without any need for conditional models or assuming that there is missing or censored data that needs adjustment. It also enables us to model dependence on covariates and within the composition

Análise à volatilidade do mercado da arte

Um olhar breve para a história financeira internacional denota que, em períodos de crise ou até mesmo de depressão das principais economias mundiais, os investidores tendem a proteger os seus investimentos, muito para além dos usuais activos financeiros, como o caso das acções, obrigações, entre outros. A principal razão para tal é que, em termos empíricos, verifica-se que estes activos referidos apresentam uma elevada volatilidade, especialmente em momentos de grande turbulência nos mercados financeiros, em virtude da incerteza quanto ao futuro das economias mundiais. Assim sendo, a presente investigação realiza uma análise em torno da previsão de volatilidade dos activos associados a arte e, assim, pretende comparar com a volatilidade existente em torno dos índices ou mercados financeiros. Para tal, serão adoptados os modelos de heterocedasticidade condicional, com a finalidade de previsão de volatilidade marginal ou incondicional. A análise efectuada baseou-se na comparação da volatilidade marginal dos índices S&P 500 e DJ Euro Stoxx 50, representativos dos activos financeiros, face à volatilidade marginal das principais empresas (Christie´s e Sotheby´s) e do principal índice de arte (ArtPrice Global Index), representativos dos activos associados à arte. Os resultados evidenciam uma diferença significativa entre as volatilidades marginais ou incondicionais previstas, resultando numa menor volatilidade prevista incondicional dos activos de arte face aos activos financeiros.

Modelagem em análise de sobrevivencia com eventos recorrentes aplicada a dados da área médica

Pós-graduação em Biometria - IBB

Konditionale Modellsysteme zur Untersuchung der ERBB2-induzierten Tumorgenese

Konditionale Modellsysteme zur Untersuchung der ERBB2-induzierten Tumorgenese Die Rezeptor-Tyrosinkinase ERBB2 ist in einer Vielzahl epithelialer Tumore, wie Mamma- und Ovarialkarzinomen, überexprimiert. Diese erhöhte Expression korreliert mit aggressivem Tumorwachstum, verstärkter Metastasierung und schlechter Prognose für den Patienten. Zur genaueren Untersuchung molekularer Mechanismen, die zur Tumorentstehung infolge der ERBB2-Überexpression führen, wurden im Rahmen dieser Arbeit mit Hilfe des Tet-Systems induzierbare MCF-7 Zelllinien generiert. Diese exprimieren bei Gabe von Doxyzyklin ERBB2 bzw. die zum humanen ERBB2 homologe und durch Punktmutation onkogen aktivierte Rattenvariante NeuT. Nachdem die stringente Regulierbarkeit durch Doxyzyklin für die untersuchten Zellklone gezeigt werden konnte, stellte sich bei der Charakterisierung der Zelllinien heraus, dass die Induktion von ERBB2 erstaunlicherweise nicht zur Proliferation der Zellen, sondern zum Wachstumsarrest führt. Bei der Untersuchung verschiedener Zellzyklusregulatoren konnte dieser Zellzyklusarrest dem CDK-Inhibitor P21 zugeordnet werden, dessen Expression durch ERBB2 induziert wird. In P21-Antisense-Experimenten konnte nachgewiesen werden, dass P21 eine Schlüsselrolle beim ERBB2-induzierten Zellzyklusarrest spielt. Neben der Induktion von P21 und der daraus resultierenden Wachstumsinhibition zeigten die Zellen starke morphologische Veränderungen und waren positiv beim Nachweis der Seneszenz-assoziierten -Galaktosidase. Erstmals konnte gezeigt werden, dass die Induktion des Onkogens ERBB2 nicht zur Proliferation, sondern zur Aktivierung eines verfrühten Seneszenz-Programms führt, welches der Zelle Schutz gegen die Onkogeneinwirkung bietet. Bei der Untersuchung verschiedener Signaltransduktionskaskaden mit Inhibitormolekülen konnte die Aktivierung dieses Seneszenz-Programms der Stress-aktivierten Proteinkinase P38 zugeordnet werden. Zur Identifizierung von Genen, die für die ERBB2-induzierte Tumorgenese relevant sind, wurde die differenzielle Genexpression eines NeuT-Klons nach 8- bzw. 48-stündiger Induktion mit Doxyzyklin in einem cDNA-Array untersucht. Dabei zeigte sich eine besonders starke Induktion von Integrin 5 und Integrin 1, die zusammen den Fibronektinrezeptor bilden. Der funktionale Nachweis des Rezeptors in einem Adhäsionsassay demonstrierte ein stark erhöhtes Adhäsionsverhalten ERBB2-überexprimierender Zellen an Fibronektin. Bei der Untersuchung von Mamma-, Ovarial- und Endometriumkarzinomen konnte die Expression von ERBB2 mit der von Integrin 5 korreliert werden. Diese Ergebnisse machen Integrin 5 zu einem potenziellen neuen Tumormarker und Therapieziel in ERBB2-überexprimierenden Tumoren. Ein weiteres interessantes Gen, das sich im Array durch ERBB2 überexprimiert zeigte, war die Matrix-Metalloproteinase MMP-9. In einem Zymografieassay konnte die erhöhte Gelatinaseaktivität von MMP-9 in Dox-induzierten Zellen nachgewiesen werden. Der Einsatz verschiedener Signaltransduktionsinhibitoren ergab, dass auch die ERBB2-induzierte Expression von MMP-9 über die Aktivierung von P38 läuft. Bei der Suche nach weiteren MMPs, die für die ERBB2-induzierte Tumorgenese relevant sein könnten, wurde MMP-13 untersucht. Erstmals konnte gezeigt werden, dass diese Matrix-Metalloproteinase von ERBB2 induziert wird. Dieser interessante Befund wurde auch in einem anderen Zellmodell in NIH3T3 Mausfibroblasten verifiziert. Durch ihre Matrix-degradierenden Eigenschaften sind MMPs potente „Werkzeuge“ für Tumorzellen und stellen ein wichtiges Ziel zur Unterbindung der Invasion und Metastasierung dieser Zellen dar. Neben den Zellkulturarbeiten wurden im Rahmen dieser Dissertation transgene Responder-Mäuse generiert, die NeuT unter Kontrolle eines Tet-responsiven Promotors exprimieren. Von vier transgenen Gründerlinien zeigten zwei eine unerwünschte, basale NeuT-Expression, für die beiden anderen Linien konnte sowohl in MEF-Assays, als auch nach Kreuzung mit rtTA- bzw. tTA-Effektor-Mäusen eine Dox-abhängige Regulation des Transgens gezeigt werden. Die Tiere dieser Linien sollen in Zukunft mit Effektor-Mäusen gepaart werden, die den rtTA bzw. tTA spezifisch in für die ERBB2-Tumorgenese relevanten Geweben, wie Ovarial- oder Lungenepithelzellen, exprimieren. So können individuelle Tumormodelle für die verschiedenen epithelialen Tumore, bei denen die Überexpression von ERBB2 von Bedeutung ist, entwickelt und untersucht werden.