Three essays in financial economics: asset pricing, optimal portfolio selection and financial integration

Executive Summary The unifying theme of this thesis is the pursuit of a satisfactory ways to quantify the riskureward trade-off in financial economics. First in the context of a general asset pricing model, then across models and finally across country borders. The guiding principle in that pursuit was to seek innovative solutions by combining ideas from different fields in economics and broad scientific research. For example, in the first part of this thesis we sought a fruitful application of strong existence results in utility theory to topics in asset pricing. In the second part we implement an idea from the field of fuzzy set theory to the optimal portfolio selection problem, while the third part of this thesis is to the best of our knowledge, the first empirical application of some general results in asset pricing in incomplete markets to the important topic of measurement of financial integration. While the first two parts of this thesis effectively combine well-known ways to quantify the risk-reward trade-offs the third one can be viewed as an empirical verification of the usefulness of the so-called "good deal bounds" theory in designing risk-sensitive pricing bounds. Chapter 1 develops a discrete-time asset pricing model, based on a novel ordinally equivalent representation of recursive utility. To the best of our knowledge, we are the first to use a member of a novel class of recursive utility generators to construct a representative agent model to address some long-lasting issues in asset pricing. Applying strong representation results allows us to show that the model features countercyclical risk premia, for both consumption and financial risk, together with low and procyclical risk free rate. As the recursive utility used nests as a special case the well-known time-state separable utility, all results nest the corresponding ones from the standard model and thus shed light on its well-known shortcomings. The empirical investigation to support these theoretical results, however, showed that as long as one resorts to econometric methods based on approximating conditional moments with unconditional ones, it is not possible to distinguish the model we propose from the standard one. Chapter 2 is a join work with Sergei Sontchik. There we provide theoretical and empirical motivation for aggregation of performance measures. The main idea is that as it makes sense to apply several performance measures ex-post, it also makes sense to base optimal portfolio selection on ex-ante maximization of as many possible performance measures as desired. We thus offer a concrete algorithm for optimal portfolio selection via ex-ante optimization over different horizons of several risk-return trade-offs simultaneously. An empirical application of that algorithm, using seven popular performance measures, suggests that realized returns feature better distributional characteristics relative to those of realized returns from portfolio strategies optimal with respect to single performance measures. When comparing the distributions of realized returns we used two partial risk-reward orderings first and second order stochastic dominance. We first used the Kolmogorov Smirnov test to determine if the two distributions are indeed different, which combined with a visual inspection allowed us to demonstrate that the way we propose to aggregate performance measures leads to portfolio realized returns that first order stochastically dominate the ones that result from optimization only with respect to, for example, Treynor ratio and Jensen's alpha. We checked for second order stochastic dominance via point wise comparison of the so-called absolute Lorenz curve, or the sequence of expected shortfalls for a range of quantiles. As soon as the plot of the absolute Lorenz curve for the aggregated performance measures was above the one corresponding to each individual measure, we were tempted to conclude that the algorithm we propose leads to portfolio returns distribution that second order stochastically dominates virtually all performance measures considered. Chapter 3 proposes a measure of financial integration, based on recent advances in asset pricing in incomplete markets. Given a base market (a set of traded assets) and an index of another market, we propose to measure financial integration through time by the size of the spread between the pricing bounds of the market index, relative to the base market. The bigger the spread around country index A, viewed from market B, the less integrated markets A and B are. We investigate the presence of structural breaks in the size of the spread for EMU member country indices before and after the introduction of the Euro. We find evidence that both the level and the volatility of our financial integration measure increased after the introduction of the Euro. That counterintuitive result suggests the presence of an inherent weakness in the attempt to measure financial integration independently of economic fundamentals. Nevertheless, the results about the bounds on the risk free rate appear plausible from the view point of existing economic theory about the impact of integration on interest rates.

Blood corticosterone levels and intersexual selection games: best-of-bad-job strategies of male common lizards

Glucocorticoids affect physiology and behaviour, reproduction and potentially sexual selection as well. Shortterm and moderate glucocorticoid elevations are suggested to be adaptive, and prolonged and high elevations may be extremely harmful. This suggests that optimal reproductive strategies, and thus sexual selection, may be dose dependent. Here, we investigate effects of moderate and high elevations of blood corticosterone levels on intra- and intersexual behaviour and mating success of male common lizards Lacerta vivipara. Females showed less interest and more aggressive behaviour towards high corticosterone males and blood corticosterone levels affected male reproductive strategy. Males of moderate and high corticosterone elevations, compared with Control males, showed increased interest (i.e., higher number of chases, tongue extrusions, and approaches) towards females and high corticosterone males initiated more copulation attempts. However, neither increased male interest nor increased copulation attempts resulted in more copulations. This provides evidence for a best-of-a-bad-job strategy, where males with higher corticosterone levels compensated for reduced female interest and increased aggressive female behaviour directed towards them, by showing higher interest and by conducting more copulation attempts. Blood corticosterone levels affected intrasexual selection as well since moderate corticosterone levels positively affected male dominance, but dominance did not affect mating success. These findings underline the importance of female mate choice and are in line with adaptive compensatory behaviours of males. They further show that glucocorticoid effects on behaviour are dose dependent and that they have important implications for sexual selection and social interactions, and might potentially affect Darwinian fitness.

Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

Male cognitive performance declines in the absence of sexual selection.

Sexual selection is responsible for the evolution of male ornaments and armaments, but its role in the evolution of cognition--the ability to process, retain and use information--is largely unexplored. Because successful courtship is likely to involve processing information in complex, competitive sexual environments, we hypothesized that sexual selection contributes to the evolution and maintenance of cognitive abilities in males. To test this, we removed mate choice and mate competition from experimental populations of Drosophila melanogaster by enforcing monogamy for over 100 generations. Males evolved under monogamy became less proficient than polygamous control males at relatively complex cognitive tasks. When faced with one receptive and several unreceptive females, polygamous males quickly focused on receptive females, whereas monogamous males continued to direct substantial courtship effort towards unreceptive females. As a result, monogamous males were less successful in this complex setting, despite being as quick to mate as their polygamous counterparts with only one receptive female. This diminished ability to use past information was not limited to the courtship context: monogamous males (but not females) also showed reduced aversive olfactory learning ability. Our results provide direct experimental evidence that the intensity of sexual selection is an important factor in the evolution of male cognitive ability.

Magnetoresistance at artificial interfaces in the itinerant SrRuO3 ferromagnet

The magnetoresistance across interfaces in the itinerant ferromagnetic oxide SrRuO3 have been studied. To define appropriately the interfaces, epitaxial thin films have been grown on bicrystalline and laser-patterned SrTiO3 substrates. Comparison is made with results obtained on similar experiments using the double-exchange ferromagnetic oxide La2/3Sr1/3MnO3. It is found that in SrRuO3, interfaces induce a substantial negative magnetoresistance, although no traces of the low-field spin tunneling magnetoresistance are found. We discuss these results on the basis of the distinct degree of spin polarization in ruthenates and manganites and the different nature of the surface magnetic layer formed at interfaces.

Developmentally regulated extinction of Ly-49 receptor expression permits maturation and selection of NK1.1+ T cells.

Clonally distributed inhibitory receptors negatively regulate natural killer (NK) cell function via specific interactions with allelic forms of major histocompatibility complex (MHC) class I molecules. In the mouse, the Ly-49 family of inhibitory receptors is found not only on NK cells but also on a minor (NK1.1+) T cell subset. Using Ly-49 transgenic mice, we show here that the development of NK1.1+ T cells, in contrast to NK or conventional T cells, is impaired when their Ly-49 receptors engage self-MHC class I molecules. Impaired NK1.1+ T cell development in transgenic mice is associated with a failure to select the appropriate CD1-reactive T cell receptor repertoire. In normal mice, NK1.1+ T cell maturation is accompanied by extinction of Ly-49 receptor expression. Collectively, our data imply that developmentally regulated extinction of inhibitory MHC-specific receptors is required for normal NK1.1+ T cell maturation and selection.

Evaluating the Effectiveness of Red Light Running Camera Enforcement in Cedar Rapids and Developing Guidelines For Selection and use of Red Light Running Countermeasures, Midwest Transportation Consortium, Final Report November 2011.

Red light running (RLR) is a problem in the US that has resulted in 165,000 injuries and 907 fatalities annually. In Iowa, RLR-related crashes make up 24.5 percent of all crashes and account for 31.7 percent of fatal and major injury crashes at signalized intersections. RLR crashes are a safety concern due to the increased likelihood of injury compared to other types of crashes. One tool used to combat red light running is automated enforcement in the form of RLR cameras. Automated enforcement, while effective, is often controversial. Cedar Rapids, Iowa installed RLR and speeding cameras at seven intersections across the city. The intersections were chosen based on crash rates and whether cameras could feasibly be placed at the intersection approaches. The cameras were placed starting in February 2010 with the last one becoming operational in December 2010. An analysis of the effect of the cameras on safety at these intersections was determined prudent in helping to justify the installation and effectiveness of the cameras. The objective of this research was to assess the safety effectiveness of the RLR program that has been implemented in Cedar Rapids. This was accomplished by analyzing data to determine changes in the following metrics:  Reductions in red light violation rates based on overall changes, time of day changes, and changes by lane  Effectiveness of the cameras over time  Time in which those running the red light enter the intersection  Changes in the average headway between vehicles entering the intersection

Self-selection and risk selection on the Swiss health insurance market

Abstract This thesis presents three empirical studies in the field of health insurance in Switzerland. First we investigate the link between health insurance coverage and health care expenditures. We use claims data for over 60 000 adult individuals covered by a major Swiss Health Insurance Fund, followed for four years; the data show a strong positive correlation between coverage and expenditures. Two methods are developed and estimated in order to separate selection effects (due to individual choice of coverage) and incentive effects ("ex post moral hazard"). The first method uses the comparison between inpatient and outpatient expenditures to identify both effects and we conclude that both selection and incentive effects are significantly present in our data. The second method is based on a structural model of joint demand of health care and health insurance and makes the most of the change in the marginal cost of health care to identify selection and incentive effects. We conclude that the correlation between insurance coverage and health care expenditures may be decomposed into the two effects: 75% may be attributed to selection, and 25 % to incentive effects. Moreover, we estimate that a decrease in the coinsurance rate from 100% to 10% increases the marginal demand for health care by about 90% and from 100% to 0% by about 150%. Secondly, having shown that selection and incentive effects exist in the Swiss health insurance market, we present the consequence of this result in the context of risk adjustment. We show that if individuals choose their insurance coverage in function of their health status (selection effect), the optimal compensations should be function of the se- lection and incentive effects. Therefore, a risk adjustment mechanism which ignores these effects, as it is the case presently in Switzerland, will miss his main goal to eliminate incentives for sickness funds to select risks. Using a simplified model, we show that the optimal compensations have to take into account the distribution of risks through the insurance plans in case of self-selection in order to avoid incentives to select risks.Then, we apply our propositions to Swiss data and propose a simple econometric procedure to control for self-selection in the estimation of the risk adjustment formula in order to compute the optimal compensations.

Artificial zinc finger fusions targeting Sp1-binding sites and the trans-activator-responsive element potently repress transcription and replication of HIV-1.

Tat activates transcription by interacting with Sp1, NF-kappaB, positive transcription elongation factor b, and trans-activator-responsive element (TAR). Tat and Sp1 play major roles in transcription by protein-protein interactions at human immunodeficiency virus, type 1 (HIV-1) long terminal repeat. Sp1 activates transcription by interacting with cyclin T1 in the absence of Tat. To disrupt the transcription activation by Tat and Sp1, we fused Sp1-inhibiting polypeptides, zinc finger polypeptide, and the TAR-binding mutant Tat (TatdMt) together. A designed or natural zinc finger and Tat mutant fusion was used to target the fusion to the key regulatory sites (GC box and TAR) on the long terminal repeat and nascent short transcripts to disrupt the molecular interaction that normally result in robust transcription. The designed zinc finger and TatdMt fusions were targeted to the TAR, and they potently repressed both transcription and replication of HIV-1. The Sp1-inhibiting POZ domain, TatdMt, and zinc fingers are key functional domains important in repression of transcription and replication. The designed artificial zinc fingers were targeted to the high affinity Sp1-binding site, and by being fused with TatdMt and POZ domain, they strongly block both Sp1-cyclin T1-dependent transcription and Tat-dependent transcription, even in the presence of excess expressed Tat.

Dark energy equation of state and anthropic selection

We explore the possibility that the dark energy is due to a potential of a scalar field and that the magnitude and the slope of this potential in our part of the Universe are largely determined by anthropic selection effects. We find that, in some models, the most probable values of the slope are very small, implying that the dark energy density stays constant to very high accuracy throughout cosmological evolution. In other models, however, the most probable values of the slope are such that the slow roll condition is only marginally satisfied, leading to a recollapse of the local universe on a time scale comparable to the lifetime of the Sun. In the latter case, the effective equation of state varies appreciably with the redshift, leading to a number of testable predictions.

Habitat selection in zones of parapatric contact between the Common shrew Sorex araneus and Millet's shrew S. coronatus

(1) The common shrew Sorex araneus and Millet's shrew S. coronatus are sibling species.They are morphologically and genetically very similar but do not hybridize. Their parapatric distribution throughout south-western Europe, with a few narrow zones of distributional overlap, suggests that they are in competitive parapatry. (2) Two of these contact zones were studied; there was evidence of coexistence over periods of 2 years as well as habitat segregation. In both zones, the species segregated on litter thickness and humidity variables. (3) A simple analysis of spatial distribution showed that habitats visible in the field corresponded to the habitats selected by the species. Habitat selection was found throughout the annual life-cycle of the shrews. (4) In one contact zone, a removal experiment was performed to test whether habitat segregation is induced by interspecific interactions. The experiment showed that the species select habitats differentially when both are present and abandon habitat selection when their competitor is removed. (5) These results confirm the role of resource partitioning in promoting narrow rangesof distributional overlap between such parapatric species and qualitatively support the prediction of habitat selection theory that, in a two-species system, coexistence may be achieved by differential habitat selection to avoid competition. The results also support the view that the common shrew and Millet's shrew are in competitive parapatry.

Bioinformatic study of selection in animal genomes

Les gènes orthologues divergent sur plusieurs aspects durant l'évolution. Après une revue de la littérature cherchant à montrer de la divergence entre les orthologues de l'humain et de la souris, j'ai souligné les différentes causes de cette divergence. En comparant les gènes qui divergent en fonction, je n'ai pas trouvé de lien avec la divergence des séquences, pour cette raison je me suis penché sur l'étude de l'expression. Notamment, j'ai étudié le niveau, la spécificité ainsi que la présence/absence d'expression des orthologues humain-souris liés aux maladies Mendéliennes. Malgré les similarités trouvées entre l'humain et la souris, j'ai détecté une différence d'expression spécifique à une des deux espèces liée a un phénotype précis (gène essentiel/non-essentiel). Cela m'a permis de conclure que la différence sur le plan phénotypique entre l'humain et la souris est mieux expliquée par les patrons d'expression plutôt que le niveau d'expression ou la sélection. J'ai été également intéressé par l'évolution des séquences d'ADN codantes pour des protéines, en particulier sur le rôle de la sélection. J'ai commencé par une étude sur la fiabilité de détection de la sélection positive en comparant des séquences divergentes. J'ai trouvé, en utilisant le model de branche-site que la sélection peut être détectée sur des séquences qui ont divergé il y a plus de 500 millions d'années. J'ai analysé le biais de GC entres les séquences sans trouver une influence sur l'estimation de la sélection positive. Finalement, Je crois que ce travail est une première étape dans l'établissement d'un lien entre la sélection et les patrons d'expression des gènes chez les vertébrés.

Urinary Sphincter Based on Electronics and Artificial Muscles

Objectives: The AMS 800 is the current artifi cial urinary sphincter (AUS) forincontinence due to intrinsic sphincter defi ciency. Despite good clinical results,technical failures inherent to the hydraulic mechanism or urethral ischemicinjury contribute to revisions up to 60%. We are developing an electronic AUS,called ARTUS to overcome the rigors of AMS. The objective of this study wasto evaluate the technical effi cacy and tissue tolerance of the ARTUS systemin an animal model.Methods: The ARTUS is composed by three parts: thecontractile unit, a series of rings and an integrated microprocessor. The contractileunit is made of Nitinol fi bers. The rings are placed around the urethrato control the fl ow of urine by squeezing the urethra. They work in a sequentialalternative mode and are controlled by a microprocessor. In the fi rst phase athree-rings device was used while in the second phase a two-rings ARTUS wasused. The device was implanted in 14 sheep divided in two groups of six andeight animals for study purpose. The fi rst group aimed at bladder leak pointpressure (BLPP) measurement and validation of the animal model; the secondgroup aimed at verifying midterm tissue tolerance by explants at twelve weeks.General animal tolerance was also evaluated.Results: The ARTUS systemimplantation was uneventful. When the system was activated, the BLPP wasmeasured at 1.038 ± 0.044 bar (mean ± SD). Urethral tissue analysis did notshow signifi cant morphological changes. No infection and no sign of discomfortwere noted in animals at 12 weeks.Conclusions: The ARTUS proved to beeffective in continence achievement in this study. Histological results supportour idea that a sequential alternative mode can avoid urethral atrophy andischemia. Further technical developments are needed to verify long-termoutcome and permit human use.

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.