Contemporary aspects of dividends: Before and during the financial crisis

The number of dividend paying firms has been on the decline since the popularity of stock repurchases in the 1980s, and the recent financial crisis has brought about a wave of dividend reductions and omissions. This dissertation examined the U.S. firms and American Depository Receipts that are listed on the U.S. equity exchanges according to their dividend paying history in the previous twelve quarters. While accounting for the state of the economy, the firm’s size, profitability, earned equity, and growth opportunities, it determines whether or not the firm will pay a dividend in the next quarter. It also examined the likelihood of a dividend change. Further, returns of firms were examined according to their dividend paying history and the state of the economy using the Fama-French three-factor model. Using forward, backward, and step-wise selection logistic regressions, the results show that firms with a history of regular and uninterrupted dividend payments are likely to continue to pay dividends, while firms that do not have a history of regular dividend payments are not likely to begin to pay dividends or continue to do so. The results of a set of generalized polytomous logistic regressions imply that dividend paying firms are more likely to reduce dividend payments during economic expansions, as opposed to recessions. Also the analysis of returns using the Fama-French three factor model reveals that dividend paying firms are earning significant abnormal positive returns. As a special case, a similar analysis of dividend payment and dividend change was applied to American Depository Receipts that trade on the NYSE, NASDAQ, and AMEX exchanges and are issued by the Bank of New York Mellon. Returns of American Depository Receipts were examined using the Fama-French two-factor model for international firms. The results of the generalized polytomous logistic regression analyses indicate that dividend paying status and economic conditions are also important for dividend level change of American Depository Receipts, and Fama-French two-factor regressions alone do not adequately explain returns for these securities.

A study of stock market linkages between the US and frontier countries

My dissertation investigates the financial linkages and transmission of economic shocks between the US and the smallest emerging markets (frontier markets). The first chapter sets up an empirical model that examines the impact of US market returns and conditional volatility on the returns and conditional volatilities of twenty-one frontier markets. The model is estimated via maximum likelihood; utilizes the GARCH model of errors, and is applied to daily country data from the MSCI Barra. We find limited, but statistically significant exposure of Frontier markets to shocks from the US. Our results suggest that it is not the lagged US market returns that have impact; rather it is the expected US market returns that influence frontier market returns The second chapter sets up an empirical time-varying parameter (TVP) model to explore the time-variation in the impact of mean US returns on mean Frontier market returns. The model utilizes the Kalman filter algorithm as well as the GARCH model of errors and is applied to daily country data from the MSCI Barra. The TVP model detects statistically significant time-variation in the impact of US returns and low, but statistically and quantitatively important impact of US market conditional volatility. The third chapter studies the risk-return relationship in twenty Frontier country stock markets by setting up an international version of the intertemporal capital asset pricing model. The systematic risk in this model comes from covariance of Frontier market stock index returns with world returns. Both the systematic risk and risk premium are time-varying in our model. We also incorporate own country variances as additional determinants of Frontier country returns. Our results suggest statistically significant impact of both world and own country risk in explaining Frontier country returns. Time-variation in the world risk premium is also found to be statistically significant for most Frontier market returns. However, own country risk is found to be quantitatively more important.

Three Essays on Asset Pricing

In this dissertation, I investigate three related topics on asset pricing: the consumption-based asset pricing under long-run risks and fat tails, the pricing of VIX (CBOE Volatility Index) options and the market price of risk embedded in stock returns and stock options. These three topics are fully explored in Chapter II through IV. Chapter V summarizes the main conclusions. In Chapter II, I explore the effects of fat tails on the equilibrium implications of the long run risks model of asset pricing by introducing innovations with dampened power law to consumption and dividends growth processes. I estimate the structural parameters of the proposed model by maximum likelihood. I find that the stochastic volatility model with fat tails can, without resorting to high risk aversion, generate implied risk premium, expected risk free rate and their volatilities comparable to the magnitudes observed in data. In Chapter III, I examine the pricing performance of VIX option models. The contention that simpler-is-better is supported by the empirical evidence using actual VIX option market data. I find that no model has small pricing errors over the entire range of strike prices and times to expiration. In general, Whaley’s Black-like option model produces the best overall results, supporting the simpler-is-better contention. However, the Whaley model does under/overprice out-of-the-money call/put VIX options, which is contrary to the behavior of stock index option pricing models. In Chapter IV, I explore risk pricing through a model of time-changed Lévy processes based on the joint evidence from individual stock options and underlying stocks. I specify a pricing kernel that prices idiosyncratic and systematic risks. This approach to examining risk premia on stocks deviates from existing studies. The empirical results show that the market pays positive premia for idiosyncratic and market jump-diffusion risk, and idiosyncratic volatility risk. However, there is no consensus on the premium for market volatility risk. It can be positive or negative. The positive premium on idiosyncratic risk runs contrary to the implications of traditional capital asset pricing theory.

Filogenia molecular das enzimas isocitrato liase e malato sintase e sua evolução em Viridiplanta

The plant metabolism consists of a complex network of physical and chemical events resulting in photosynthesis, respiration, synthesis and degradation of organic compounds. This is only possible due to the different kinds of responses to many environmental variations that a plant could be subject through evolution, leading also to conquering new surroundings. The glyoxylate cycle is a metabolic pathway found in glyoxysomes plant, which has unique role in the seedling establishment. Considered as a variation of the citric acid cycle, it uses an acetyl coenzyme A molecule, derived from lipids beta-oxidation to synthesize compounds which are used in carbohydrate synthesis. The Malate synthase (MLS) and Isocitrate lyase (ICL) enzyme of this cycle are unique and essential in regulating the biosynthesis of carbohydrates. Because of the absence of decarboxylation steps as rate-limiting steps, detailed studies of molecular phylogeny and evolution of these proteins enables the elucidation of the effects of this route presence in the evolutionary processes involved in their distribution across the genome from different plant species. Therefore, the aim of this study was to establish a relationship between the molecular evolution of the characteristics of enzymes from the glyoxylate cycle (isocitrate lyase and malate synthase) and their molecular phylogeny, among green plants (Viridiplantae). For this, amino acid and nucleotide sequences were used, from online repositories as UniProt and Genbank. Sequences were aligned and then subjected to an analysis of the best-fit substitution models. The phylogeny was rebuilt by distance methods (neighbor-joining) and discrete methods (maximum likelihood, maximum parsimony and Bayesian analysis). The identification of structural patterns in the evolution of the enzymes was made through homology modeling and structure prediction from protein sequences. Based on comparative analyzes of in silico models and from the results of phylogenetic inferences, both enzymes show significant structure conservation and their topologies in agreement with two processes of selection and specialization of the genes. Thus, confirming the relevance of new studies to elucidate the plant metabolism from an evolutionary perspective

Gato-do-mato-pequeno (Leopardus tigrinus) na Caatinga: ocupação e padrão de atividade de um felídeo ameaçado e pouco conhecido na floresta tropical seca do nordeste do Brasil

While the carnivores are considered regulators and structuring of natural communities are also extremely threatened by human activities. Endangered little-spotted-cat (Leopardus tigrinus) is one of the lesser known species from the Neotropical cats. In this work we investigate the occupancy and the activity pattern of L. tigrinus in Caatinga of Rio Grande do Norte testing: 1) how environmental and anthropogenic factors influence their occupation and 2) how biotic and abiotic factors influence their activity pattern. For this we raised occurrence data of species in 10 priority areas for conservation. We built hierarchical models of occupancy based on maximum likelihood to represent biological hypotheses which were ranked using the Akaike Information Criterion (AIC). According to the results the feline occupancy is more likely away from rural settlements and in areas with a higher proportion of woody vegetation. The opportunistic killing of L. tigrinus and in retaliation for poultry predation close to residential areas can explain this result; as well as more complex vegetation structure can better serve as refuge and ensure more food. Analyzing the records of the species through circular statistics we conclude that the activity pattern is mostly nocturnal, although considerable crepuscular and a small diurnal activity. L. tigrinus activity was directly affected by the availability of small terrestrial mammals, which are essentially nocturnal. In addition, the temperatures recorded in the environment directly and indirectly affect the activity of the little-spotted-cat, as also influence the activity of their potential prey. Generally, the cats were more active when possible prey were active, and this happened at night when lower temperatures are recorded. Moreover, the different lunar phases did not affect the activity pattern. The results improve the understanding of an endangered feline inhabiting the Caatinga biome, and thus can help develop conservation and management strategies, as well as in planning future research in this semi-arid ecosystem.

Variabilidade genética de Leishmania spp. circulantes entre seres humanos e cães e infecção de flebotomíneos em áreas endêmicas para as leishmanioses no Rio Grande do Norte

Leishmania infantum is the main etiologic agent of visceral leishmaniasis in the New World. The pattern of distribution of leishmaniasis has changed substantially and has presented an emerging profile within the periphery of the Large Urban Centers. Leishmania infection can compromise skin, mucosa and viscera. Only 10% of the individuals infected develop the disease and 90% of human infection is asymptomatic. The main factors involved in the development of the disease are the host immune response, the vector’s species and the parasite’s genetic content. The sequencing of Leishmania isolated seeks to increase the understanding of the symptoms of individuals. The aim of this study was to evaluate the genetic diversity of circulating Leishmania strains among humans, and symptomatic and asymptomatic, and dogs from endemic areas of Rio Grande do Norte State and analyze sandflies from endemic areas for cutaneous and visceral disease. The genetic variability was evaluated by the use of markers hsp70 , ITS1 and a whole genome sequencing was also carried out. The amplified hsp70 and ITS1 of samples were analyzed and assembled using a Phred / Phrap package. The dendograms were constructed using the same methodology, but adding 500 bootstraps, followed by inferences on the relationships between Leishmania variants. The sequences of the 20 Brazilian isolates were mapped to the reference genome L. infantum JPCM5, using the Bowtie2 program and the identification of 36 contigs. The information of the valid SNPs were used in the PCA. SNPs were visualized by Geneious 7.1 and IGV. The genome annotations were transferred to their respective chromosomes and displayed on Geneious. The matching sequences of all chromosomes were aligned using Mauve. The phylogenetic trees were calculated according to maximum likelihood and JTT models. Sandflies were analyzed by PCR for the identification of Leishmania infection, a blood meal source and GAPDH sand fly. As a result, hsp70 and ITS1 were not capable of identifying genetic variability among human isolates from symptomatic and asymptomatic, and dogs. The complete sequencing of the 20 Brazilian isolates revealed a strong similarity between the circulating Leishmania strains in Rio Grande do Norte. The isolates collected in the city of Natal from humans and canines remained grouped in all analyzes, suggesting that there is genotypic and geographic proximity among the isolates. The isolated samples in the 1990s had a higher genotypic diversity when compared to freshly isolated samples. All isolates presented 36 chromosomes with variable ploidy among them, no correlation was found between the number of amastina genes copies, gp63, A2 and SSG with such clinic forms. In general, we did not find correlation between symptomatic and asymptomatic clinical forms and the gene content of the Brazilian isolates of Leishmania. 34,28% of the sandflies collected in the upper west region were L. longipalpis and the main sources of blood meal were humans, dogs and chickens.

Variabilidade genética de Leishmania spp. circulantes entre seres humanos e cães e infecção de flebotomíneos em áreas endêmicas para as leishmanioses no Rio Grande do Norte

Leishmania infantum is the main etiologic agent of visceral leishmaniasis in the New World. The pattern of distribution of leishmaniasis has changed substantially and has presented an emerging profile within the periphery of the Large Urban Centers. Leishmania infection can compromise skin, mucosa and viscera. Only 10% of the individuals infected develop the disease and 90% of human infection is asymptomatic. The main factors involved in the development of the disease are the host immune response, the vector’s species and the parasite’s genetic content. The sequencing of Leishmania isolated seeks to increase the understanding of the symptoms of individuals. The aim of this study was to evaluate the genetic diversity of circulating Leishmania strains among humans, and symptomatic and asymptomatic, and dogs from endemic areas of Rio Grande do Norte State and analyze sandflies from endemic areas for cutaneous and visceral disease. The genetic variability was evaluated by the use of markers hsp70 , ITS1 and a whole genome sequencing was also carried out. The amplified hsp70 and ITS1 of samples were analyzed and assembled using a Phred / Phrap package. The dendograms were constructed using the same methodology, but adding 500 bootstraps, followed by inferences on the relationships between Leishmania variants. The sequences of the 20 Brazilian isolates were mapped to the reference genome L. infantum JPCM5, using the Bowtie2 program and the identification of 36 contigs. The information of the valid SNPs were used in the PCA. SNPs were visualized by Geneious 7.1 and IGV. The genome annotations were transferred to their respective chromosomes and displayed on Geneious. The matching sequences of all chromosomes were aligned using Mauve. The phylogenetic trees were calculated according to maximum likelihood and JTT models. Sandflies were analyzed by PCR for the identification of Leishmania infection, a blood meal source and GAPDH sand fly. As a result, hsp70 and ITS1 were not capable of identifying genetic variability among human isolates from symptomatic and asymptomatic, and dogs. The complete sequencing of the 20 Brazilian isolates revealed a strong similarity between the circulating Leishmania strains in Rio Grande do Norte. The isolates collected in the city of Natal from humans and canines remained grouped in all analyzes, suggesting that there is genotypic and geographic proximity among the isolates. The isolated samples in the 1990s had a higher genotypic diversity when compared to freshly isolated samples. All isolates presented 36 chromosomes with variable ploidy among them, no correlation was found between the number of amastina genes copies, gp63, A2 and SSG with such clinic forms. In general, we did not find correlation between symptomatic and asymptomatic clinical forms and the gene content of the Brazilian isolates of Leishmania. 34,28% of the sandflies collected in the upper west region were L. longipalpis and the main sources of blood meal were humans, dogs and chickens.

Fixed vs. variable noise in 2AFC contrast discrimination: lessons from psychometric functions.

Recent discussion regarding whether the noise that limits 2AFC discrimination performance is fixed or variable has focused either on describing experimental methods that presumably dissociate the effects of response mean and variance or on reanalyzing a published data set with the aim of determining how to solve the question through goodness-of-fit statistics. This paper illustrates that the question cannot be solved by fitting models to data and assessing goodness-of-fit because data on detection and discrimination performance can be indistinguishably fitted by models that assume either type of noise when each is coupled with a convenient form for the transducer function. Thus, success or failure at fitting a transducer model merely illustrates the capability (or lack thereof) of some particular combination of transducer function and variance function to account for the data, but it cannot disclose the nature of the noise. We also comment on some of the issues that have been raised in recent exchange on the topic, namely, the existence of additional constraints for the models, the presence of asymmetric asymptotes, the likelihood of history-dependent noise, and the potential of certain experimental methods to dissociate the effects of response mean and variance.

Asymptotic Theory for Extended Asymmetric Multivariate GARCH Processes

The paper considers various extended asymmetric multivariate conditional volatility models, and derives appropriate regularity conditions and associated asymptotic theory. This enables checking of internal consistency and allows valid statistical inferences to be drawn based on empirical estimation. For this purpose, we use an underlying vector random coefficient autoregressive process, for which we show the equivalent representation for the asymmetric multivariate conditional volatility model, to derive asymptotic theory for the quasi-maximum likelihood estimator. As an extension, we develop a new multivariate asymmetric long memory volatility model, and discuss the associated asymptotic properties.

Realized Matrix-Exponential Stochastic Volatility with Asymmetry, Long Memory and Spillovers

The paper develops a novel realized matrix-exponential stochastic volatility model of multivariate returns and realized covariances that incorporates asymmetry and long memory (hereafter the RMESV-ALM model). The matrix exponential transformation guarantees the positivedefiniteness of the dynamic covariance matrix. The contribution of the paper ties in with Robert Basmann’s seminal work in terms of the estimation of highly non-linear model specifications (“Causality tests and observationally equivalent representations of econometric models”, Journal of Econometrics, 1988, 39(1-2), 69–104), especially for developing tests for leverage and spillover effects in the covariance dynamics. Efficient importance sampling is used to maximize the likelihood function of RMESV-ALM, and the finite sample properties of the quasi-maximum likelihood estimator of the parameters are analysed. Using high frequency data for three US financial assets, the new model is estimated and evaluated. The forecasting performance of the new model is compared with a novel dynamic realized matrix-exponential conditional covariance model. The volatility and co-volatility spillovers are examined via the news impact curves and the impulse response functions from returns to volatility and co-volatility.

Cervical cancer precursors and hormonal contraceptive use in HIV-positive women: application of a causal model and semi-parametric estimation methods.

OBJECTIVE: To demonstrate the application of causal inference methods to observational data in the obstetrics and gynecology field, particularly causal modeling and semi-parametric estimation. BACKGROUND: Human immunodeficiency virus (HIV)-positive women are at increased risk for cervical cancer and its treatable precursors. Determining whether potential risk factors such as hormonal contraception are true causes is critical for informing public health strategies as longevity increases among HIV-positive women in developing countries. METHODS: We developed a causal model of the factors related to combined oral contraceptive (COC) use and cervical intraepithelial neoplasia 2 or greater (CIN2+) and modified the model to fit the observed data, drawn from women in a cervical cancer screening program at HIV clinics in Kenya. Assumptions required for substantiation of a causal relationship were assessed. We estimated the population-level association using semi-parametric methods: g-computation, inverse probability of treatment weighting, and targeted maximum likelihood estimation. RESULTS: We identified 2 plausible causal paths from COC use to CIN2+: via HPV infection and via increased disease progression. Study data enabled estimation of the latter only with strong assumptions of no unmeasured confounding. Of 2,519 women under 50 screened per protocol, 219 (8.7%) were diagnosed with CIN2+. Marginal modeling suggested a 2.9% (95% confidence interval 0.1%, 6.9%) increase in prevalence of CIN2+ if all women under 50 were exposed to COC; the significance of this association was sensitive to method of estimation and exposure misclassification. CONCLUSION: Use of causal modeling enabled clear representation of the causal relationship of interest and the assumptions required to estimate that relationship from the observed data. Semi-parametric estimation methods provided flexibility and reduced reliance on correct model form. Although selected results suggest an increased prevalence of CIN2+ associated with COC, evidence is insufficient to conclude causality. Priority areas for future studies to better satisfy causal criteria are identified.

Posterior Probability Modeling and Image Classification for Archaeological Site Prospection: Building a Survey Efficacy Model for Identifying Neolithic Felsite Workshops in the Shetland Islands

The application of custom classification techniques and posterior probability modeling (PPM) using Worldview-2 multispectral imagery to archaeological field survey is presented in this paper. Research is focused on the identification of Neolithic felsite stone tool workshops in the North Mavine region of the Shetland Islands in Northern Scotland. Sample data from known workshops surveyed using differential GPS are used alongside known non-sites to train a linear discriminant analysis (LDA) classifier based on a combination of datasets including Worldview-2 bands, band difference ratios (BDR) and topographical derivatives. Principal components analysis is further used to test and reduce dimensionality caused by redundant datasets. Probability models were generated by LDA using principal components and tested with sites identified through geological field survey. Testing shows the prospective ability of this technique and significance between 0.05 and 0.01, and gain statistics between 0.90 and 0.94, higher than those obtained using maximum likelihood and random forest classifiers. Results suggest that this approach is best suited to relatively homogenous site types, and performs better with correlated data sources. Finally, by combining posterior probability models and least-cost analysis, a survey least-cost efficacy model is generated showing the utility of such approaches to archaeological field survey.

Directional genetic differentiation and relative migration

Understanding the population structure and patterns of gene flow within species is of fundamental importance to the study of evolution. In the fields of population and evolutionary genetics, measures of genetic differentiation are commonly used to gather this information. One potential caveat is that these measures assume gene flow to be symmetric. However, asymmetric gene flow is common in nature, especially in systems driven by physical processes such as wind or water currents. As information about levels of asymmetric gene flow among populations is essential for the correct interpretation of the distribution of contemporary genetic diversity within species, this should not be overlooked. To obtain information on asymmetric migration patterns from genetic data, complex models based on maximum-likelihood or Bayesian approaches generally need to be employed, often at great computational cost. Here, a new simpler and more efficient approach for understanding gene flow patterns is presented. This approach allows the estimation of directional components of genetic divergence between pairs of populations at low computational effort, using any of the classical or modern measures of genetic differentiation. These directional measures of genetic differentiation can further be used to calculate directional relative migration and to detect asymmetries in gene flow patterns. This can be done in a user-friendly web application called divMigrate-online introduced in this study. Using simulated data sets with known gene flow regimes, we demonstrate that the method is capable of resolving complex migration patterns under a range of study designs.

Testing the psychometric properties of Kidscreen-27 with Irish children of low socio-economic status

Background

Kidscreen-27 was developed as part of a cross-cultural European Union-funded project to standardise the measurement of children’s health-related quality of life. Yet, research has reported mixed evidence for the hypothesised 5-factor model, and no confirmatory factor analysis (CFA) has been conducted on the instrument with children of low socio-economic status (SES) across Ireland (Northern and Republic).

Method

The data for this study were collected as part of a clustered randomised controlled trial. A total of 663 (347 male, 315 female) 8–9-year-old children (M = 8.74, SD = .50) of low SES took part. A 5- and modified 7-factor CFA models were specified using the maximum likelihood estimation. A nested Chi-square difference test was conducted to compare the fit of the models. Internal consistency and floor and ceiling effects were also examined.

Results

CFA found that the hypothesised 5-factor model was an unacceptable fit. However, the modified 7-factor model was supported. A nested Chi-square difference test confirmed that the fit of the 7-factor model was significantly better than that of the 5-factor model. Internal consistency was unacceptable for just one scale. Ceiling effects were present in all but one of the factors.

Conclusions

Future research should apply the 7-factor model with children of low socio-economic status. Such efforts would help monitor the health status of the population.

Modelos autorregressivos com valores inteiros não negativos : aplicação em séries económicas de Cabo Verde

No estudo de séries temporais, os processos estocásticos usuais assumem que as distribuições marginais são contínuas e, em geral, não são adequados para modelar séries de contagem, pois as suas características não lineares colocam alguns problemas estatísticos, principalmente na estimação dos parâmetros. Assim, investigou-se metodologias apropriadas de análise e modelação de séries com distribuições marginais discretas. Neste contexto, Al-Osh and Alzaid (1987) e McKenzie (1988) introduziram na literatura a classe dos modelos autorregressivos com valores inteiros não negativos, os processos INAR. Estes modelos têm sido frequentemente tratados em artigos científicos ao longo das últimas décadas, pois a sua importância nas aplicações em diversas áreas do conhecimento tem despertado um grande interesse no seu estudo. Neste trabalho, após uma breve revisão sobre séries temporais e os métodos clássicos para a sua análise, apresentamos os modelos autorregressivos de valores inteiros não negativos de primeira ordem INAR (1) e a sua extensão para uma ordem p, as suas propriedades e alguns métodos de estimação dos parâmetros nomeadamente, o método de Yule-Walker, o método de Mínimos Quadrados Condicionais (MQC), o método de Máxima Verosimilhança Condicional (MVC) e o método de Quase Máxima Verosimilhança (QMV). Apresentamos também um critério automático de seleção de ordem para modelos INAR, baseado no Critério de Informação de Akaike Corrigido, AICC, um dos critérios usados para determinar a ordem em modelos autorregressivos, AR. Finalmente, apresenta-se uma aplicação da metodologia dos modelos INAR em dados reais de contagem relativos aos setores dos transportes marítimos e atividades de seguros de Cabo Verde.