Testing the Markov property with ultra high frequency financial data

This paper develops a framework to test whether discrete-valued irregularly-spaced financial transactions data follow a subordinated Markov process. For that purpose, we consider a specific optional sampling in which a continuous-time Markov process is observed only when it crosses some discrete level. This framework is convenient for it accommodates not only the irregular spacing of transactions data, but also price discreteness. Further, it turns out that, under such an observation rule, the current price duration is independent of previous price durations given the current price realization. A simple nonparametric test then follows by examining whether this conditional independence property holds. Finally, we investigate whether or not bid-ask spreads follow Markov processes using transactions data from the New York Stock Exchange. The motivation lies on the fact that asymmetric information models of market microstructures predict that the Markov property does not hold for the bid-ask spread. The results are mixed in the sense that the Markov assumption is rejected for three out of the five stocks we have analyzed.

Analysis of contagion from the constant conditional correlation model with Markov regime switching

Over the last decades, the analysis of the transmissions of international nancial events has become the subject of many academic studies focused on multivariate volatility models volatility. The goal of this study is to evaluate the nancial contagion between stock market returns. The econometric approach employed was originally presented by Pelletier (2006), named Regime Switching Dynamic Correlation (RSDC). This methodology involves the combination of Constant Conditional Correlation Model (CCC) proposed by Bollerslev (1990) with Markov Regime Switching Model suggested by Hamilton and Susmel (1994). A modi cation was made in the original RSDC model, the introduction of the GJR-GARCH model formulated in Glosten, Jagannathan e Runkle (1993), on the equation of the conditional univariate variances to allow asymmetric e ects in volatility be captured. The database was built with the series of daily closing stock market indices in the United States (SP500), United Kingdom (FTSE100), Brazil (IBOVESPA) and South Korea (KOSPI) for the period from 02/01/2003 to 09/20/2012. Throughout the work the methodology was compared with others most widespread in the literature, and the model RSDC with two regimes was de ned as the most appropriate for the selected sample. The set of results provide evidence for the existence of nancial contagion between markets of the four countries considering the de nition of nancial contagion from the World Bank called very restrictive. Such a conclusion should be evaluated carefully considering the wide diversity of de nitions of contagion in the literature.

A (semi-)parametric functional coefficient autoregressive conditional duration model

In this paper, we propose a class of ACD-type models that accommodates overdispersion, intermittent dynamics, multiple regimes, and sign and size asymmetries in financial durations. In particular, our functional coefficient autoregressive conditional duration (FC-ACD) model relies on a smooth-transition autoregressive specification. The motivation lies on the fact that the latter yields a universal approximation if one lets the number of regimes grows without bound. After establishing that the sufficient conditions for strict stationarity do not exclude explosive regimes, we address model identifiability as well as the existence, consistency, and asymptotic normality of the quasi-maximum likelihood (QML) estimator for the FC-ACD model with a fixed number of regimes. In addition, we also discuss how to consistently estimate using a sieve approach a semiparametric variant of the FC-ACD model that takes the number of regimes to infinity. An empirical illustration indicates that our functional coefficient model is flexible enough to model IBM price durations.

The Taylor rule under inquiry: Hidden states

This work empirically evaluates the Taylor rule for the US and Brazil using Markov-Switching Regimes. I find that the inflation parameter of the US Taylor rule is less than one in many periods, contrasting heavily with Clarida, Gal´ı and Gertler (2000), and the same happens with Brazilian data. When the inflation parameter is greater than one, it encompasses periods that these authors considered they should be less than one. Brazil is used for comparative purposes because it experienced a high level inflation until 1994 and then a major stabilization plan reduced the growth in prices to civilized levels. Thus, it is a natural laboratory to test theories designed to work in any environment. The findings point to a theoretical gap that deserves further investigation and show that monetary policy in Brazil has been ineffective, which is coherent with the general attitude of population in relation to this measure.

Taylor rule with hidden states

This work evaluates empirically the Taylor rule for the US and Brazil using Kalman Filter and Markov-Switching Regimes. We show that the parameters of the rule change significantly with variations in both output and output gap proxies, considering hidden variables and states. Such conclusions call naturally for robust optimal monetary rules. We also show that Brazil and US have very contrasting parameters, first because Brazil presents time-varying intercept, second because of the rigidity in the parameters of the Brazilian Taylor rule, regardless the output gap proxy, data frequency or sample data. Finally, we show that the long-run inflation parameter of the US Taylor rule is less than one in many periods, contrasting strongly with Orphanides (forthcoming) and Clarida, Gal´i and Gertler (2000), and the same happens with Brazilian monthly data.

Padrões distintos de congruência climática em duas espécies invasoras de prosopis em zonas semi-áridas da América do Sul

Based on climate data and occurrence records, ecological niche models (ENM) are an important opportunity to identify areas at risk or vulnerable to biological invasion. These models are based on the assumption that there is a match between the climatic characteristic of native and invaded regions predicting the potential distribution of exotic species. Using new methods to measure niche overlap, we chose two exotic species fairly common in semi-arid regions of South America, Prosopis juliflora (Sw.) D.C. and Prosopis pallida (H. ; B. ex. Willd) HBK, to test the climate matching hypothesis. Our results indicate that both species occur with little niche overlap in the native region while the inverse pattern is observed in the invaded region on South America, where both species occur with high climatic overlap. Maybe some non-climate factor act limiting the spread of P. pallida on the native range. We believe that a founder effect can explain these similarities between species niche in the invaded region once the seeds planted in Brazil came from a small region on the Native range (Piura in Peru), where both species occur sympatric. Our hypothesis of a founder effect may be evident when we look at the differences between the predictions of the models built in the native and invaded ranges. Furthermore, our results indicate that P. juliflora shows high levels of climate matching between native and invaded ranges. However, conclusions about climate matching of P. pallida should be taken with caution. Our models based on climatic variables provide multiple locations suitable for occurrence of both species in regions where they still don t have occurrence records, including places of high interest for conservation.

Latent heat loss of dairy cows in an equatorial semi-arid environment

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Algoritmos genéticos: uso de lógica nebulosa e análise de convergência por cadeia de Markov

In this work, the Markov chain will be the tool used in the modeling and analysis of convergence of the genetic algorithm, both the standard version as for the other versions that allows the genetic algorithm. In addition, we intend to compare the performance of the standard version with the fuzzy version, believing that this version gives the genetic algorithm a great ability to find a global optimum, own the global optimization algorithms. The choice of this algorithm is due to the fact that it has become, over the past thirty yares, one of the more importan tool used to find a solution of de optimization problem. This choice is due to its effectiveness in finding a good quality solution to the problem, considering that the knowledge of a good quality solution becomes acceptable given that there may not be another algorithm able to get the optimal solution for many of these problems. However, this algorithm can be set, taking into account, that it is not only dependent on how the problem is represented as but also some of the operators are defined, to the standard version of this, when the parameters are kept fixed, to their versions with variables parameters. Therefore to achieve good performance with the aforementioned algorithm is necessary that it has an adequate criterion in the choice of its parameters, especially the rate of mutation and crossover rate or even the size of the population. It is important to remember that those implementations in which parameters are kept fixed throughout the execution, the modeling algorithm by Markov chain results in a homogeneous chain and when it allows the variation of parameters during the execution, the Markov chain that models becomes be non - homogeneous. Therefore, in an attempt to improve the algorithm performance, few studies have tried to make the setting of the parameters through strategies that capture the intrinsic characteristics of the problem. These characteristics are extracted from the present state of execution, in order to identify and preserve a pattern related to a solution of good quality and at the same time that standard discarding of low quality. Strategies for feature extraction can either use precise techniques as fuzzy techniques, in the latter case being made through a fuzzy controller. A Markov chain is used for modeling and convergence analysis of the algorithm, both in its standard version as for the other. In order to evaluate the performance of a non-homogeneous algorithm tests will be applied to compare the standard fuzzy algorithm with the genetic algorithm, and the rate of change adjusted by a fuzzy controller. To do so, pick up optimization problems whose number of solutions varies exponentially with the number of variables

Use of Poisson spatiotemporal regression models for the Brazilian Amazon Forest: malaria count data

INTRODUÇÃO: A malaria é uma doença endêmica na região da Amazônia Brasileira, e a detecção de possíveis fatores de risco pode ser de grande interesse às autoridades em saúde pública. O objetivo deste artigo é investigar a associação entre variáveis ambientais e os registros anuais de malária na região amazônica usando métodos bayesianos espaço-temporais. MÉTODOS: Utilizaram-se modelos de regressão espaço-temporais de Poisson para analisar os dados anuais de contagem de casos de malária entre os anos de 1999 a 2008, considerando a presença de alguns fatores como a taxa de desflorestamento. em uma abordagem bayesiana, as inferências foram obtidas por métodos Monte Carlo em cadeias de Markov (MCMC) que simularam amostras para a distribuição conjunta a posteriori de interesse. A discriminação de diferentes modelos também foi discutida. RESULTADOS: O modelo aqui proposto sugeriu que a taxa de desflorestamento, o número de habitants por km² e o índice de desenvolvimento humano (IDH) são importantes para a predição de casos de malária. CONCLUSÕES: É possível concluir que o desenvolvimento humano, o crescimento populacional, o desflorestamento e as alterações ecológicas associadas a estes fatores estão associados ao aumento do risco de malária. Pode-se ainda concluir que o uso de modelos de regressão de Poisson que capturam o efeito temporal e espacial em um enfoque bayesiano é uma boa estratégia para modelar dados de contagem de malária.

Experimental poisoning by Senecio brasiliensis in calves: quantitative and semi-quantitative study on changes in the hepatic extracellular matrix and sinusoidal cells

A matriz extracelular (MEC) desempenha um papel importante em lesões hepáticas crônicas e tem sido estudada em modelos de intoxicação experimental. em bovinos, no entanto, não há estudos específicos sobre a MEC hepática normal ou com lesões crônicas. Por isso, foi desenvolvido um modelo de intoxicação experimental hepático usando Senecio brasilliensis, uma planta que contém alcalóides pirrolizidínicos e causa lesão hepática dependente da dose. Cinco bezerros receberam por via oral, 0.38g/kg de folhas secas por 24 dias. Biópsias hepáticas foram obtidas a cada 15 dias durante 60 dias. Sinais clínicos de complicações digestivas surgiram da terceira semana do experimento. Um bezerro morreu aos 45 dias e os outros quatro foram avaliados até os 60 dias. As biópsias hepáticas foram processadas para microscopia óptica, imuno-histoquímica e microscopia eletrônica de transmissão. No trigésimo dia, as lesões hepáticas eram progessivas caracterizadas por vacuolização hepatocelular, necrose, apoptose, megalocitose, e fibrose centrolobular, pericelular e portal. Foram realizadas avaliações quantitativas e semi-quantitativas de componentes da MEC hepática antes e após o aparecimento das lesões. Foi realizada morfometria do colágeno total e do sistema de fibras elásticas. Colágeno total e colágenos tipos I e III aumentaram progressivamente em todos os locais do fígado. Mudanças na localização, quantidade e disposição do sistema de fibras elásticas foram também observadas. Houve um aumento significativo de células de Kupffer aos 30 dias e de células sinusoidais totais aos 45 e 60 dias. As lesões hepáticas neste experimento foram progressivas mesmo após a remoção da planta. Lesões de fibrose severa foram localizadas principalmente nos espaços porta, seguido por fibrose veno-oclusiva e pericelular. Os colágenos tipo I e tipo III foram observados no fígado normal e no fígado dos bezerros afetados, com predomínio do tipo I. Nos bezerros afetados o aumento do colágeno total e do sistema de fibras elásticas foi paralelo ao aumento no número das células sinusoidais.

Antiulcerogenic effect and cytotoxic activity of semi-synthetic crotonin obtained from Croton cajucara Benth.

Trans-dehydrocrotonin, the major diterpene isolated from the bark of Croton cajucara, has good antiulcerogenic activity which, however, is accompanied by toxic effects. on the basis of these results, a semi-synthetic crotonin, named 4SRC, was prepared to determine whether this substance has similar antiulcerogenic activity with lower or no toxicity. The natural crotonin was also isolated from the bark of C. cajucara but was not used due to the small amount obtained. The cytotoxic effect of semi-synthetic crotonin, expressed as cell viability, was assessed in (a) lung fibroblast cell line (V79) derived from Chinese hamsters, a system commonly used for cytotoxicity studies, and (b) rat hepatocytes isolated from male Wistar rats. After treatment, cell viability was determined by 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide reduction (MTT reduction), total acid content and neutral red uptake assays. To evaluate V79 cell viability, different concentrations of semi-synthetic crotonin were incubated with the cells. To evaluate the antiulcerogenic effects of semi-synthetic crotonin (50, 100 and 200 mg/kg), we used the models of gastric ulcer induced by ethanol/HCl, stress, indomethacin/bethanechol, and ethanol in male Swiss mice and male Wistar rats. The substance had an IC50 = 500 muM in the neutral red uptake and MTT reduction tests and an IC50 = 200 muM in the nucleic acid content test. With regard to hepatocyte viability after treatment with semi-synthetic crotonin at different concentrations, semi-synthetic crotonin had an IC50 = 10-500 muM in the nucleic acid content and MTT reduction tests and an IC50 = 120 muM in the neutral red uptake test. In another experiment, V79 cells were incubated with the metabolites produced by hepatocytes treated with different concentrations of semi-synthetic crotonin. After a 4-h incubation, semi-synthetic crotonin had an IC50 = 500 muM in the MTT reduction and neutral red uptake tests and an IC50 = 370 muM in nucleic acid content test. The substance had significant antiulcerogenic activity in all models studied, suggesting the presence of a possible antisecretory effect combined with a cytoprotective effect. For this reason, the effect of semi-synthetic crotonin was also evaluated on biochemical parameters of gastric juice and gastric wall mucus, both obtained from pylorus-ligated mice. No significant differences were observed in these parameters between semi-synthetic crotonin-treated and control animals. The results obtained with semi-synthetic crotonin are promising, with a significant preventive effect against gastric ulcer induced by different agents. Our data also show that semi-synthetic crotonin was less toxic than dehydrocrotonin and that the cytotoxic effects decreases with the time that isolated hepatocytes were in culture. (C) 2003 Elsevier B.V. B.V. All rights reserved.

Comparison between the complete Bayesian method and empirical Bayesian method for ARCH models using Brazilian financial time series

In this work we compared the estimates of the parameters of ARCH models using a complete Bayesian method and an empirical Bayesian method in which we adopted a non-informative prior distribution and informative prior distribution, respectively. We also considered a reparameterization of those models in order to map the space of the parameters into real space. This procedure permits choosing prior normal distributions for the transformed parameters. The posterior summaries were obtained using Monte Carlo Markov chain methods (MCMC). The methodology was evaluated by considering the Telebras series from the Brazilian financial market. The results show that the two methods are able to adjust ARCH models with different numbers of parameters. The empirical Bayesian method provided a more parsimonious model to the data and better adjustment than the complete Bayesian method.

Robust Bayesian analysis of heavy-tailed stochastic volatility models using scale mixtures of normal distributions

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Probability distribution models for daily rainfall data for an interior station of Brazil

Two stochastic models have been fitted to daily rainfall data for an interior station of Brazil. Of these two models, the results show a better fit to describe the data, by truncated negative probability model in comparison with Markov chain probability model. Kolmogorov-Smirnov test is applied for significance for these models. © 1983 Springer-Verlag.

Further on the current algebra of WZNW models at and away from criticality

We comment on the off-critical perturbations of WZNW models by a mass term as well as by another descendent operator, when we can compare the results with further algebra obtained from the Dirac quantization of the model, in such a way that a more general class of models be included. We discover, in both cases, hidden Kac-Moody algebras obeyed by some currents in the off-critical case, which in several cases are enough to completely fix the correlation functions.