Semiparametric estimation and inference using doubly robust moment conditions

We study semiparametric two-step estimators which have the same structure as parametric doubly robust estimators in their second step. The key difference is that we do not impose any parametric restriction on the nuisance functions that are estimated in a first stage, but retain a fully nonparametric model instead. We call these estimators semiparametric doubly robust estimators (SDREs), and show that they possess superior theoretical and practical properties compared to generic semiparametric two-step estimators. In particular, our estimators have substantially smaller first-order bias, allow for a wider range of nonparametric first-stage estimates, rate-optimal choices of smoothing parameters and data-driven estimates thereof, and their stochastic behavior can be well-approximated by classical first-order asymptotics. SDREs exist for a wide range of parameters of interest, particularly in semiparametric missing data and causal inference models. We illustrate our method with a simulation exercise.

Ensaios em Finanças

Esta tese é composta de três artigos sobre finanças. O primeiro tem o título "Nonparametric Option Pricing with Generalized Entropic Estimators " e estuda um método de apreçamento de derivativos em mercados incompletos. Este método está relacionado com membros da família de funções de Cressie-Read em que cada membro fornece uma medida neutra ao risco. Vários testes são feitos. Os resultados destes testes sugerem um modo de definir um intervalo robusto para preços de opções. Os outros dois artigos são sobre anúncios agendados em diferentes situações. O segundo se chama "Watching the News: Optimal Stopping Time and Scheduled Announcements" e estuda problemas de tempo de parada ótimo na presença de saltos numa data fixa em modelos de difusão com salto. Fornece resultados sobre a otimalidade do tempo de parada um pouco antes do anúncio. O artigo aplica os resultados ao tempo de exercício de Opções Americanas e ao tempo ótimo de venda de um ativo. Finalmente o terceiro artigo estuda um problema de carteira ótima na presença de custo fixo quando os preços podem saltar numa data fixa. Seu título é "Dynamic Portfolio Selection with Transactions Costs and Scheduled Announcement" e o resultado mais interessante é que o comportamento do investidor é consistente com estudos empíricos sobre volume de transações em momentos próximos de anúncios.

A class of improved heteroskedasticity-consistent covariance matrix estimators

The heteroskedasticity-consistent covariance matrix estimator proposed by White (1980), also known as HC0, is commonly used in practical applications and is implemented into a number of statistical software. Cribari–Neto, Ferrari & Cordeiro (2000) have developed a bias-adjustment scheme that delivers bias-corrected White estimators. There are several variants of the original White estimator that also commonly used by practitioners. These include the HC1, HC2 and HC3 estimators, which have proven to have superior small-sample behavior relative to White’s estimator. This paper defines a general bias-correction mechamism that can be applied not only to White’s estimator, but to variants of this estimator as well, such as HC1, HC2 and HC3. Numerical evidence on the usefulness of the proposed corrections is also presented. Overall, the results favor the sequence of improved HC2 estimators.

Efficient semiparametric estimation of quantile treatment effects

This paper presents calculations of semiparametric efficiency bounds for quantile treatment effects parameters when se1ection to treatment is based on observable characteristics. The paper also presents three estimation procedures forthese parameters, alI ofwhich have two steps: a nonparametric estimation and a computation ofthe difference between the solutions of two distinct minimization problems. Root-N consistency, asymptotic normality, and the achievement ofthe semiparametric efficiency bound is shown for one ofthe three estimators. In the final part ofthe paper, an empirical application to a job training program reveals the importance of heterogeneous treatment effects, showing that for this program the effects are concentrated in the upper quantiles ofthe earnings distribution.

Nonparametric tail risk, macroeconomics and stock returns: predictability and risk premia

This paper proposes a new novel to calculate tail risks incorporating risk-neutral information without dependence on options data. Proceeding via a non parametric approach we derive a stochastic discount factor that correctly price a chosen panel of stocks returns. With the assumption that states probabilities are homogeneous we back out the risk neutral distribution and calculate five primitive tail risk measures, all extracted from this risk neutral probability. The final measure is than set as the first principal component of the preliminary measures. Using six Fama-French size and book to market portfolios to calculate our tail risk, we find that it has significant predictive power when forecasting market returns one month ahead, aggregate U.S. consumption and GDP one quarter ahead and also macroeconomic activity indexes. Conditional Fama-Macbeth two-pass cross-sectional regressions reveal that our factor present a positive risk premium when controlling for traditional factors.

Elicitation of multivariate prior distributions: A nonparametric Bayesian approach

In the context of Bayesian statistical analysis, elicitation is the process of formulating a prior density f(.) about one or more uncertain quantities to represent a person's knowledge and beliefs. Several different methods of eliciting prior distributions for one unknown parameter have been proposed. However, there are relatively few methods for specifying a multivariate prior distribution and most are just applicable to specific classes of problems and/or based on restrictive conditions, such as independence of variables. Besides, many of these procedures require the elicitation of variances and correlations, and sometimes elicitation of hyperparameters which are difficult for experts to specify in practice. Garthwaite et al. (2005) discuss the different methods proposed in the literature and the difficulties of eliciting multivariate prior distributions. We describe a flexible method of eliciting multivariate prior distributions applicable to a wide class of practical problems. Our approach does not assume a parametric form for the unknown prior density f(.), instead we use nonparametric Bayesian inference, modelling f(.) by a Gaussian process prior distribution. The expert is then asked to specify certain summaries of his/her distribution, such as the mean, mode, marginal quantiles and a small number of joint probabilities. The analyst receives that information, treating it as a data set D with which to update his/her prior beliefs to obtain the posterior distribution for f(.). Theoretical properties of joint and marginal priors are derived and numerical illustrations to demonstrate our approach are given. (C) 2010 Elsevier B.V. All rights reserved.

Constraints implementation for IQML and mode direction-of-arrival estimators

The iterative quadratic maximum likelihood IQML and the method of direction estimation MODE are well known high resolution direction-of-arrival DOA estimation methods. Their solutions lead to an optimization problem with constraints. The usual linear constraint presents a poor performance for certain DOA values. This work proposes a new linear constraint applicable to both DOA methods and compare their performance with two others: unit norm and usual linear constraint. It is shown that the proposed alternative performs better than others constraints. The resulting computational complexity is also investigated.

A Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes

A Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes is introduced. The proposed model may accommodate the original single shift setting to the more realistic situation of gradual quality deterioration and allows the incorporation of an expert's opinion on the production process. Based on the number of inspections to be carried out until a defective item is found, the Bayesian operation for the distribution function that represents the increasing sequence of defective fractions during a cycle considering a mixture of Dirichlet processes as prior distribution is performed. Bayes estimates for relevant quantities are also obtained. © 2012 Elsevier B.V.

Abundância, composição e diversidade de Arctiinae (Lepidoptera, Arctiidae) em um fragmento de floresta na Amazônia Oriental em Altamira, PA, Brasil

Este estudo avaliou a fauna de Arctiinae em um fragmento de floresta primária em Altamira, Pará, na Amazônia Oriental brasileira. As mariposas foram amostradas durante dois anos (de agosto de 2007 a julho de 2009), com auxílio de armadilha luminosa. Foram medidos os seguintes parâmetros: riqueza, abundância, constância, índices de diversidade e uniformidade de Shannon (H' e E') e de Brillouin (H e E) e o índice de dominância de Berger-Parker (BP). As estimativas de riqueza, foram efetuadas através dos procedimentos não paramétricos, "Bootstrap", "Chao 1", "Chao 2", "Jackknife 1", "Jackknife2" e "Michaelis-Mentem". Foram capturados 466 exemplares pertencentes a 78 espécies de Arctiinae, das quais 12 são novos registros para o Estado. Os valores dos parâmetros analisados para todo o período foram: H'= 3,08, E'= 0,708, H= 2,86, E= 0,705 e BP= 0,294. As comunidades dos meses menos chuvosos foram mais diversas. Os estimadores previram o encontro de 17 a 253 espécies a mais.

Arctiinae (Lepidoptera, Arctiidae) ocorrentes em uma área de pastagem na Amazônia Oriental em Altamira, Pará, Brasil

O presente estudo avaliou a fauna de Arctiinae numa área de pastagem na Amazônia Oriental em Altamira-Pará, por meio de armadilha luminosa, com duas capturas mensais noturnas a cada fase da lua nova, no período de dezembro de 2008 a novembro de 2010. Foram avaliados os seguintes parâmetros: riqueza, abundância, dominância, constância, índices de diversidade e uniformidade de Shannon (H' e E') e Brillouin (H e E), dominância de Berger-Parker (BP). As estimativas de riqueza foram feitas através dos procedimentos não paramétricos, "Bootstrap", "Chao1", "Chao2", "Jackknife1", "Jackknife2", e "Michaelis-Mentem". Foram capturados 910 exemplares pertencentes a 85 espécies de Arctiinae. Os valores dos parâmetros analisados para o período total foram: H'= 2,58, E'= 0,581, H= 2,45, E= 0,576 e BP= 0,433. Para os anos, tanto a riqueza quanto a abundância foi maior em 2009-2010. A diversidade e uniformidade de Shannon e Brillouin foram maiores para o ano de 2008-2009. Os estimadores previram um aumento entre 18,8% e 85,9 % na riqueza de espécies.

Evaluating Measurement Invariance with Censored Ordinal Data: A Monte Carlo Comparison of Alternative Model Estimators and Scales of Measurement

Evaluations of measurement invariance provide essential construct validity evidence. However, the quality of such evidence is partly dependent upon the validity of the resulting statistical conclusions. The presence of Type I or Type II errors can render measurement invariance conclusions meaningless. The purpose of this study was to determine the effects of categorization and censoring on the behavior of the chi-square/likelihood ratio test statistic and two alternative fit indices (CFI and RMSEA) under the context of evaluating measurement invariance. Monte Carlo simulation was used to examine Type I error and power rates for the (a) overall test statistic/fit indices, and (b) change in test statistic/fit indices. Data were generated according to a multiple-group single-factor CFA model across 40 conditions that varied by sample size, strength of item factor loadings, and categorization thresholds. Seven different combinations of model estimators (ML, Yuan-Bentler scaled ML, and WLSMV) and specified measurement scales (continuous, censored, and categorical) were used to analyze each of the simulation conditions. As hypothesized, non-normality increased Type I error rates for the continuous scale of measurement and did not affect error rates for the categorical scale of measurement. Maximum likelihood estimation combined with a categorical scale of measurement resulted in more correct statistical conclusions than the other analysis combinations. For the continuous and censored scales of measurement, the Yuan-Bentler scaled ML resulted in more correct conclusions than normal-theory ML. The censored measurement scale did not offer any advantages over the continuous measurement scale. Comparing across fit statistics and indices, the chi-square-based test statistics were preferred over the alternative fit indices, and ΔRMSEA was preferred over ΔCFI. Results from this study should be used to inform the modeling decisions of applied researchers. However, no single analysis combination can be recommended for all situations. Therefore, it is essential that researchers consider the context and purpose of their analyses.

A Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes

A Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes is introduced. The proposed model may accommodate the original single shift setting to the more realistic situation of gradual quality deterioration and allows the incorporation of an expert's opinion on the production process. Based on the number of inspections to be carried out until a defective item is found, the Bayesian operation for the distribution function that represents the increasing sequence of defective fractions during a cycle considering a mixture of Dirichlet processes as prior distribution is performed. Bayes estimates for relevant quantities are also obtained. (C) 2012 Elsevier B.V. All rights reserved.