Essays in higher moment asset pricing and liquidity risk

This thesis focuses on theoretical asset pricing models and their empirical applications. I aim to investigate the following noteworthy problems: i) if the relationship between asset prices and investors' propensities to gamble and to fear disaster is time varying, ii) if the conflicting evidence for the firm and market level skewness can be explained by downside risk, Hi) if costly learning drives liquidity risk. Moreover, empirical tests support the above assumptions and provide novel findings in asset pricing, investment decisions, and firms' funding liquidity. The first chapter considers a partial equilibrium model where investors have heterogeneous propensities to gamble and fear disaster. Skewness preference represents the desire to gamble, while kurtosis aversion represents fear of extreme returns. Using US data from 1988 to 2012, my model demonstrates that in bad times, risk aversion is higher, more people fear disaster, and fewer people gamble, in contrast to good times. This leads to a new empirical finding: gambling preference has a greater impact on asset prices during market downturns than during booms. The second chapter consists of two essays. The first essay introduces a foramula based on conditional CAPM for decomposing the market skewness. We find that the major market upward and downward movements can be well preadicted by the asymmetric comovement of betas, which is characterized by an indicator called "Systematic Downside Risk" (SDR). We find that SDR can efafectively forecast future stock market movements and we obtain out-of-sample R-squares (compared with a strategy using historical mean) of more than 2.27% with monthly data. The second essay reconciles a well-known empirical fact: aggregating positively skewed firm returns leads to negatively skewed market return. We reconcile this fact through firms' greater response to negative maraket news than positive market news. We also propose several market return predictors, such as downside idiosyncratic skewness. The third chapter studies the funding liquidity risk based on a general equialibrium model which features two agents: one entrepreneur and one external investor. Only the investor needs to acquire information to estimate the unobservable fundamentals driving the economic outputs. The novelty is that information acquisition is more costly in bad times than in good times, i.e. counter-cyclical information cost, as supported by previous empirical evidence. Later we show that liquidity risks are principally driven by costly learning. Résumé Cette thèse présente des modèles théoriques dévaluation des actifs et leurs applications empiriques. Mon objectif est d'étudier les problèmes suivants: la relation entre l'évaluation des actifs et les tendances des investisseurs à parier et à crainadre le désastre varie selon le temps ; les indications contraires pour l'entreprise et l'asymétrie des niveaux de marché peuvent être expliquées par les risques de perte en cas de baisse; l'apprentissage coûteux augmente le risque de liquidité. En outre, des tests empiriques confirment les suppositions ci-dessus et fournissent de nouvelles découvertes en ce qui concerne l'évaluation des actifs, les décisions relatives aux investissements et la liquidité de financement des entreprises. Le premier chapitre examine un modèle d'équilibre où les investisseurs ont des tendances hétérogènes à parier et à craindre le désastre. La préférence asymétrique représente le désir de parier, alors que le kurtosis d'aversion représente la crainte du désastre. En utilisant les données des Etats-Unis de 1988 à 2012, mon modèle démontre que dans les mauvaises périodes, l'aversion du risque est plus grande, plus de gens craignent le désastre et moins de gens parient, conatrairement aux bonnes périodes. Ceci mène à une nouvelle découverte empirique: la préférence relative au pari a un plus grand impact sur les évaluations des actifs durant les ralentissements de marché que durant les booms économiques. Exploitant uniquement cette relation générera un revenu excédentaire annuel de 7,74% qui n'est pas expliqué par les modèles factoriels populaires. Le second chapitre comprend deux essais. Le premier essai introduit une foramule base sur le CAPM conditionnel pour décomposer l'asymétrie du marché. Nous avons découvert que les mouvements de hausses et de baisses majeures du marché peuvent être prédits par les mouvements communs des bêtas. Un inadicateur appelé Systematic Downside Risk, SDR (risque de ralentissement systématique) est créé pour caractériser cette asymétrie dans les mouvements communs des bêtas. Nous avons découvert que le risque de ralentissement systématique peut prévoir les prochains mouvements des marchés boursiers de manière efficace, et nous obtenons des carrés R hors échantillon (comparés avec une stratégie utilisant des moyens historiques) de plus de 2,272% avec des données mensuelles. Un investisseur qui évalue le marché en utilisant le risque de ralentissement systématique aurait obtenu une forte hausse du ratio de 0,206. Le second essai fait cadrer un fait empirique bien connu dans l'asymétrie des niveaux de march et d'entreprise, le total des revenus des entreprises positiveament asymétriques conduit à un revenu de marché négativement asymétrique. Nous décomposons l'asymétrie des revenus du marché au niveau de l'entreprise et faisons cadrer ce fait par une plus grande réaction des entreprises aux nouvelles négatives du marché qu'aux nouvelles positives du marché. Cette décomposition révélé plusieurs variables de revenus de marché efficaces tels que l'asymétrie caractéristique pondérée par la volatilité ainsi que l'asymétrie caractéristique de ralentissement. Le troisième chapitre fournit une nouvelle base théorique pour les problèmes de liquidité qui varient selon le temps au sein d'un environnement de marché incomplet. Nous proposons un modèle d'équilibre général avec deux agents: un entrepreneur et un investisseur externe. Seul l'investisseur a besoin de connaitre le véritable état de l'entreprise, par conséquent, les informations de paiement coutent de l'argent. La nouveauté est que l'acquisition de l'information coute plus cher durant les mauvaises périodes que durant les bonnes périodes, comme cela a été confirmé par de précédentes expériences. Lorsque la récession comamence, l'apprentissage coûteux fait augmenter les primes de liquidité causant un problème d'évaporation de liquidité, comme cela a été aussi confirmé par de précédentes expériences.

The effect of retirement on cognitive functioning

Cognitive impairment has emerged as a major driver of disability in old age, with profound effects on individual well-being and decision making at older ages. In the light of policies aimed at postponing retirement ages, an important question is whether continued labour supply helps to maintain high levels of cognition at older ages. We use data of older men from the US Health and Retirement Study to estimate the effect of continued labour market participation at older ages on later-life cognition. As retirement itself is likely to depend on cognitive functioning and may thus be endogenous, we use offers of early retirement windows as instruments for retirement in econometric models for later-life cognitive functioning. These offers of early retirement are legally required to be nondiscriminatory and thus, inter alia, unrelated to cognitive functioning. At the same time, these offers of early retirement options are significant predictors of retirement. Although the simple ordinary least squares estimates show a negative relationship between retirement duration and various measures of cognitive functioning, instrumental variable estimates suggest that these associations may not be causal effects. Specifically, we find no clear relationship between retirement duration and later-life cognition for white-collar workers and, if anything, a positive relationship for blue-collar workers. Copyright © 2011 John Wiley & Sons, Ltd.

Instrumental leadership: Measurement and extension of transformational-transactional leadership theory.

Leaders must scan the internal and external environment, chart strategic and task objectives, and provide performance feedback. These instrumental leadership (IL) functions go beyond the motivational and quid-pro quo leader behaviors that comprise the full-range-transformational, transactional, and laissez faire-leadership model. In four studies we examined the construct validity of IL. We found evidence for a four-factor IL model that was highly prototypical of good leadership. IL predicted top-level leader emergence controlling for the full-range factors, initiating structure, and consideration. It also explained unique variance in outcomes beyond the full-range factors; the effects of transformational leadership were vastly overstated when IL was omitted from the model. We discuss the importance of a "fuller full-range" leadership theory for theory and practice. We also showcase our methodological contributions regarding corrections for common method variance (i.e., endogeneity) bias using two-stage least squares (2SLS) regression and Monte Carlo split-sample designs.

Serum uric acid and adiposity: deciphering causality using a bidirectional Mendelian randomization approach.

Although the relationship between serum uric acid (SUA) and adiposity is well established, the direction of the causality is still unclear in the presence of conflicting evidences. We used a bidirectional Mendelian randomization approach to explore the nature and direction of causality between SUA and adiposity in a population-based study of Caucasians aged 35 to 75 years. We used, as instrumental variables, rs6855911 within the SUA gene SLC2A9 in one direction, and combinations of SNPs within the adiposity genes FTO, MC4R and TMEM18 in the other direction. Adiposity markers included weight, body mass index, waist circumference and fat mass. We applied a two-stage least squares regression: a regression of SUA/adiposity markers on our instruments in the first stage and a regression of the response of interest on the fitted values from the first stage regression in the second stage. SUA explained by the SLC2A9 instrument was not associated to fat mass (regression coefficient [95% confidence interval]: 0.05 [-0.10, 0.19] for fat mass) contrasting with the ordinary least square estimate (0.37 [0.34, 0.40]). By contrast, fat mass explained by genetic variants of the FTO, MC4R and TMEM18 genes was positively and significantly associated to SUA (0.31 [0.01, 0.62]), similar to the ordinary least square estimate (0.27 [0.25, 0.29]). Results were similar for the other adiposity markers. Using a bidirectional Mendelian randomization approach in adult Caucasians, our findings suggest that elevated SUA is a consequence rather than a cause of adiposity.

Dynamic responses of oxygen uptake at the onset and end of moderate and heavy exercise in trained subjects.

Inconsistencies about dynamic asymmetry between the on- and off-transient responses in VO2 are found in the literature. Therefore the purpose of this study was to examine VO2 on- and off-transients during moderate- and heavy-intensity cycling exercise in trained subjects. Ten men underwent an initial incremental test for the estimation of ventilatory threshold (VT) and, on different days, two bouts of square-wave exercise at moderate (<VT) and heavy (>VT) intensities. VO2 kinetics in exercise and recovery were better described by a single exponential model (<VT), or by a double exponential with two time delays (>VT). For moderate exercise, we found a symmetry of VO2 kinetics between the on- and off-transients (i.e., fundamental component), consistent with a system manifesting linear control dynamics. For heavy exercise, a slow component superimposed on the fundamental phase was expressed in both the exercise and recovery, with similar parameter estimates. But the on-transient values of the time constant were appreciably faster than the associated off-transient, and independent of the work rate imposed (<VT and >VT). Our results do not support a dynamically linear system model of VO2 during cycling exercise in the heavy-intensity domain.

Correcting Measurement Error Bias in Interaction Models with Small Samples

Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression

Interpretation of wind components as compositional variables

The classical statistical study of the wind speed in the atmospheric surface layer is madegenerally from the analysis of the three habitual components that perform the wind data,that is, the component W-E, the component S-N and the vertical component,considering these components independent.When the goal of the study of these data is the Aeolian energy, so is when wind isstudied from an energetic point of view and the squares of wind components can beconsidered as compositional variables. To do so, each component has to be divided bythe module of the corresponding vector.In this work the theoretical analysis of the components of the wind as compositionaldata is presented and also the conclusions that can be obtained from the point of view ofthe practical applications as well as those that can be derived from the application ofthis technique in different conditions of weather

Moderating effects of management control systems and innovation on performance. Simple methods for correcting the effects of measurement error for interaction effects in small samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

Long-term efficacy and tolerability of flutamide combined with oral contraception in moderate to severe hirsutism: A 12-month, double-blind, parallel clinical trial

OBJECTIVE Our objective was to test the efficacy and tolerability of three doses of flutamide (125, 250, and 375 mg) combined with a triphasic oral contraceptive (ethynylestradiol/levonorgestrel) during 12 months to treat moderate to severe hirsutism in patients with polycystic ovary syndrome or idiopathic hirsutism. DESIGN We conducted a randomized, double-blind, placebo-controlled, parallel clinical trial. PATIENTS A total of 131 premenopausal women, suffering from moderate to severe hirsutism, were randomized to placebo or 125, 250, or 375 mg flutamide daily associated with a triphasic oral contraceptive pill. Hirsutism (Ferriman-Gallwey), acne and seborrhea (Cremoncini), and hormone serum levels were monitored at baseline and at 3 (except hormone serum levels), 6, and 12 months. Side effects and biochemical, hematological, and hepatic parameters were assessed. METHODS We used three-way ANOVA (subject, dose, and visit) with Scheffé adjustment for multiple comparisons or nonparametrical Friedman test and least-squares mean (paired data) and Kruskall-Wallis test for unpaired data analyses. We used chi(2) or Fisher's test for categorical data. RESULTS A total of 119 patients were included in the intention-to-treat analysis. All flutamide doses induced a significant decrease in hirsutism, acne, and seborrhea scores after 12 months compared with placebo without differences among dose levels. Similar related side effects were observed with placebo and 125 mg flutamide (12.5%), and slightly higher with 250 mg (17.3%) and 375 mg (21.2%). No statistically significant differences were observed either among doses or compared with placebo. CONCLUSIONS Flutamide at 125 mg daily during 12 months was the minimum effective dose to diminish hirsutism in patients with polycystic ovary syndrome or with idiopathic hirsutism.

Histology-driven data mining of lipid signatures from multiple imaging mass spectrometry analyses: application to human colorectal cancer liver metastasis biopsies.

Imaging mass spectrometry (IMS) represents an innovative tool in the cancer research pipeline, which is increasingly being used in clinical and pharmaceutical applications. The unique properties of the technique, especially the amount of data generated, make the handling of data from multiple IMS acquisitions challenging. This work presents a histology-driven IMS approach aiming to identify discriminant lipid signatures from the simultaneous mining of IMS data sets from multiple samples. The feasibility of the developed workflow is evaluated on a set of three human colorectal cancer liver metastasis (CRCLM) tissue sections. Lipid IMS on tissue sections was performed using MALDI-TOF/TOF MS in both negative and positive ionization modes after 1,5-diaminonaphthalene matrix deposition by sublimation. The combination of both positive and negative acquisition results was performed during data mining to simplify the process and interrogate a larger lipidome into a single analysis. To reduce the complexity of the IMS data sets, a sub data set was generated by randomly selecting a fixed number of spectra from a histologically defined region of interest, resulting in a 10-fold data reduction. Principal component analysis confirmed that the molecular selectivity of the regions of interest is maintained after data reduction. Partial least-squares and heat map analyses demonstrated a selective signature of the CRCLM, revealing lipids that are significantly up- and down-regulated in the tumor region. This comprehensive approach is thus of interest for defining disease signatures directly from IMS data sets by the use of combinatory data mining, opening novel routes of investigation for addressing the demands of the clinical setting.

Effective diagnosis of Alzheimer's disease by means of large margin-based methodology.

BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

Body girth as an alternative to body mass for establishing condition indexes in field studies: a validation in the king penguin.

Body mass and body condition are often tightly linked to animal health and fitness in the wild and thus are key measures for ecophysiologists and behavioral ecologists. In some animals, such as large seabird species, obtaining indexes of structural size is relatively easy, whereas measuring body mass under specific field circumstances may be more of a challenge. Here, we suggest an alternative, easily measurable, and reliable surrogate of body mass in field studies, that is, body girth. Using 234 free-living king penguins (Aptenodytes patagonicus) at various stages of molt and breeding, we measured body girth under the flippers, body mass, and bill and flipper length. We found that body girth was strongly and positively related to body mass in both molting (R(2) = 0.91) and breeding (R(2) = 0.73) birds, with the mean error around our predictions being 6.4%. Body girth appeared to be a reliable proxy measure of body mass because the relationship did not vary according to year and experimenter, bird sex, or stage within breeding groups. Body girth was, however, a weak proxy of body mass in birds at the end of molt, probably because most of those birds had reached a critical depletion of energy stores. Body condition indexes established from ordinary least squares regressions of either body girth or body mass on structural size were highly correlated (r(s) = 0.91), suggesting that body girth was as good as body mass in establishing body condition indexes in king penguins. Body girth may prove a useful proxy to body mass for estimating body condition in field investigations and could likely provide similar information in other penguins and large animals that may be complicated to weigh in the wild.

Efficacy of lisdexamfetamine dimesylate throughout the day in children and adolescents with attention-deficit/hyperactivity disorder: results from a randomized, controlled trial.

Lisdexamfetamine dimesylate (LDX) is a long-acting, prodrug stimulant therapy for patients with attention-deficit/hyperactivity disorder (ADHD). This randomized placebo-controlled trial of an optimized daily dose of LDX (30, 50 or 70 mg) was conducted in children and adolescents (aged 6-17 years) with ADHD. To evaluate the efficacy of LDX throughout the day, symptoms and behaviors of ADHD were evaluated using an abbreviated version of the Conners' Parent Rating Scale-Revised (CPRS-R) at 1000, 1400 and 1800 hours following early morning dosing (0700 hours). Osmotic-release oral system methylphenidate (OROS-MPH) was included as a reference treatment, but the study was not designed to support a statistical comparison between LDX and OROS-MPH. The full analysis set comprised 317 patients (LDX, n = 104; placebo, n = 106; OROS-MPH, n = 107). At baseline, CPRS-R total scores were similar across treatment groups. At endpoint, differences (active treatment - placebo) in least squares (LS) mean change from baseline CPRS-R total scores were statistically significant (P < 0.001) throughout the day for LDX (effect sizes: 1000 hours, 1.42; 1400 hours, 1.41; 1800 hours, 1.30) and OROS-MPH (effect sizes: 1000 hours, 1.04; 1400 hours, 0.98; 1800 hours, 0.92). Differences in LS mean change from baseline to endpoint were statistically significant (P < 0.001) for both active treatments in all four subscales of the CPRS-R (ADHD index, oppositional, hyperactivity and cognitive). In conclusion, improvements relative to placebo in ADHD-related symptoms and behaviors in children and adolescents receiving a single morning dose of LDX or OROS-MPH were maintained throughout the day and were ongoing at the last measurement in the evening (1800 hours).

Innovación, frontera tecnológica y capacidad absortiva: un estudio a nivel de países

La principal aportación de este trabajo es poner de manifiesto que la capacidad absortiva de las economías cambia en función de si el país es el líder o es un seguidor. Aunque tampoco olvidamos otras variables como son la I+D interna, la I+D externa, el desarrollo del sistema financiero y las instituciones. Para ello, primero se prueba la presencia de una raíz unitaria y después se asegura una relación de cointegración entre las variables implicadas en el modelo para poder sacar conclusiones a largo plazo. Y por último, para estimar el modelo, se utilizará una técnica econométrica que combina el tratamiento tradicional de los datos de panel con las técnicas de cointegración: los Dynamics Ordinary Least Squares (DOLS). Esta técnica soluciona las limitaciones de los OLS, ya que su distribución no suele ser estándar por la presencia de un sesgo de muestras finitas (causado bien por la endogeneidad de las variables explicativas bien por la correlación serial de la perturbación). Utilizando un panel de datos que comprende 8 países de la OECD entre 1973-2004 y para el Business Sector, se encuentran diversos resultados, entre los que destacamos que la I+D interna, la I+D externa, la frontera tecnológica, la capacidad absortiva y el desarrollo de las instituciones tienen un impacto positivo sobre el nivel de la PTF. En cambio, el desarrollo del sistema financiero tiene un impacto negativo. Palabras claves: fuentes de la I+D, frontera tecnológica, capacidad absortiva, raíces unitarias, cointegración, DOLS.

CODAMAT: a modern analogue techinque for compositional data

The quantitative estimation of Sea Surface Temperatures from fossils assemblages is afundamental issue in palaeoclimatic and paleooceanographic investigations. TheModern Analogue Technique, a widely adopted method based on direct comparison offossil assemblages with modern coretop samples, was revised with the aim ofconforming it to compositional data analysis. The new CODAMAT method wasdeveloped by adopting the Aitchison metric as distance measure. Modern coretopdatasets are characterised by a large amount of zeros. The zero replacement was carriedout by adopting a Bayesian approach to the zero replacement, based on a posteriorestimation of the parameter of the multinomial distribution. The number of modernanalogues from which reconstructing the SST was determined by means of a multipleapproach by considering the Proxies correlation matrix, Standardized Residual Sum ofSquares and Mean Squared Distance. This new CODAMAT method was applied to theplanktonic foraminiferal assemblages of a core recovered in the Tyrrhenian Sea.Kew words: Modern analogues, Aitchison distance, Proxies correlation matrix,Standardized Residual Sum of Squares