Nesta dissertação estudou-se o modelo GARMA para modelar séries temporais de dados de contagem com as distribuições condicionais de Poisson, binomial e binomial negativa. A principal finalidade foi analisar no contexto clássico e bayesiano, o desempenho e a qualidade do ajuste dos modelos de interesse, bem como o desempenho dos percentis de cobertura dos intervalos de confiança dos parâmetros para os modelos adotados. Para atingir tal finalidade considerou-se a análise dos estimadores pontuais bayesianos e foram analisados intervalos de credibilidade. Neste estudo é proposta uma distribuição a priori conjugada para os parâmetros dos modelos e busca-se a distribuição a posteriori, a qual associada a certas funções de perda permite encontrar estimativas bayesianas para os parâmetros. Na abordagem clássica foram calculados estimadores de máxima verossimilhança, usandose o método de score de Fisher e verificou-se por meio de simulação a consistência dos mesmos. Com os estudos desenvolvidos pode-se observar que, tanto a inferência clássica quanto a inferência bayesiana para os parâmetros dos modelos em questão, apresentou boas propriedades analisadas por meio das propriedades dos estimadores pontuais. A última etapa do trabalho consiste na análise de um conjunto de dados reais, sendo uma série real correspondente ao número de internações por causa da dengue em Campina Grande. Estes resultados mostram que tanto o estudo clássico, quanto o bayesiano, são capazes de descrever bem o comportamento da série / In this work, it was studied the GARMA model to model time series count data with Poisson, binomial and negative binomial discrete conditional distributions. The main goal is to analyze, in the bayesian and classic context, the performance and the quality of fit of the corresponding models, as well as the coverage percentages performance to these models. To achieve this purpose we considered the analysis of Bayesian estimators and credible intervals were analyzed. To the Bayesian study it was proposed a priori distribution joined to the models parameters and sought a posteriori distribution, which one associate with to certain loss functions allows finding out Bayesian estimates to the parameters. In the classical approach, it was calculated the maximum likelihood estimators using the method of Fisher scoring, whose interest was to verify, by simulation, the consistence. With the studies developed we can notice that, both classical and inference Bayesian inference for the parameters of those models, presented good properties analysed through the properties of the punctual estimators. The last stage of the work consisted of the analysis of one real data set, being a real serie corresponding to the admission number because of dengue in the city of Campina Grande. These results show that both the classic and the Bayesian studies are able to describe well the behavior of the serie

Credit risk of derivative securities includes the risk of underlying company and the risk of seller's nonfulfilment of contracts. Take bonds for example, we regard Treasury bills as default-free bonds, and corporate bonds as risky bonds. When the liability of property of derivative securities underlying company is less than 1, we regard the company is of bankruptcy. And then the seller of derivative securities will break the contract. The essay extends two period risky bonds pricing valuation of Jarrow and Turnbull(1995) to multiperiod situation, and derive arbitrage-free condition. Furthermore, we derive formulae of risky bonds prices by assuming the logarithm of the odds ratio of an underlying company's bankruptcy probability satisfies an AR(1) or MA(1) processes. Empirical data of Rebar, Chinarebar, Ceon are studied, time series models are established for logarithm of odds ratios. In most cases, we find that the log odds ratios can be well fitted by AR(1) models.

This thesis studies binomial and trinomial lattice approximations in Black-Scholes type option pricing models. Also, it covers the basics of these models, derivations of model parameters by several methods under different kinds of distributions. Furthermore, the convergence of the binomial model to normal distribution, Geometric Brownian Motion and Black-Scholes model is discussed. Finally, the connections and interrelations between discrete random variables under the Lattice approach and continuous random variables under models which follow Geometric Brownian Motion are discussed, compared and contrasted.

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Thesis (Ph. D.)--Oregon State University, 1995. / Typescript (photocopy). Includes bibliographical references (leaves 61-62). Also available on the World Wide Web.

A new technique is evolved to give operator representation of certain polynomials.

The statistical inferences about the parameters of Binomial-Poisson hierarchy model are discussed. Based on the estimators of paired observations we consider the other two cases with extra observations on both the first and second layer of the model. The MLEs of lambda and p are derived and it is also proved the MLE lambda is also the UMVUE of lambda. By using multivariate central limit theory and large sample theory, both the estimators based on extra observations on the first and second layer are obtained respectively. The performances of the estimators are compared numerically based on extensive Monte Carlo simulation. Simulation studies indicate that the performance of the estimators is more efficient than those only based on paired observations. Inference about the confidence interval for p is presented for both cases. The efficiency of the estimators is compared with condition given that same number of extra observations is provided.

Nesta dissertação estudou-se o modelo GARMA para modelar séries temporais de dados de contagem com as distribuições condicionais de Poisson, binomial e binomial negativa. A principal finalidade foi analisar no contexto clássico e bayesiano, o desempenho e a qualidade do ajuste dos modelos de interesse, bem como o desempenho dos percentis de cobertura dos intervalos de confiança dos parâmetros para os modelos adotados. Para atingir tal finalidade considerou-se a análise dos estimadores pontuais bayesianos e foram analisados intervalos de credibilidade. Neste estudo é proposta uma distribuição a priori conjugada para os parâmetros dos modelos e busca-se a distribuição a posteriori, a qual associada a certas funções de perda permite encontrar estimativas bayesianas para os parâmetros. Na abordagem clássica foram calculados estimadores de máxima verossimilhança, usandose o método de score de Fisher e verificou-se por meio de simulação a consistência dos mesmos. Com os estudos desenvolvidos pode-se observar que, tanto a inferência clássica quanto a inferência bayesiana para os parâmetros dos modelos em questão, apresentou boas propriedades analisadas por meio das propriedades dos estimadores pontuais. A última etapa do trabalho consiste na análise de um conjunto de dados reais, sendo uma série real correspondente ao número de internações por causa da dengue em Campina Grande. Estes resultados mostram que tanto o estudo clássico, quanto o bayesiano, são capazes de descrever bem o comportamento da série / In this work, it was studied the GARMA model to model time series count data with Poisson, binomial and negative binomial discrete conditional distributions. The main goal is to analyze, in the bayesian and classic context, the performance and the quality of fit of the corresponding models, as well as the coverage percentages performance to these models. To achieve this purpose we considered the analysis of Bayesian estimators and credible intervals were analyzed. To the Bayesian study it was proposed a priori distribution joined to the models parameters and sought a posteriori distribution, which one associate with to certain loss functions allows finding out Bayesian estimates to the parameters. In the classical approach, it was calculated the maximum likelihood estimators using the method of Fisher scoring, whose interest was to verify, by simulation, the consistence. With the studies developed we can notice that, both classical and inference Bayesian inference for the parameters of those models, presented good properties analysed through the properties of the punctual estimators. The last stage of the work consisted of the analysis of one real data set, being a real serie corresponding to the admission number because of dengue in the city of Campina Grande. These results show that both the classic and the Bayesian studies are able to describe well the behavior of the serie

No description available.

No description available.