Simulation-Based Finite and Large Sample Tests in Multivariate Regressions.

In the context of multivariate linear regression (MLR) models, it is well known that commonly employed asymptotic test criteria are seriously biased towards overrejection. In this paper, we propose a general method for constructing exact tests of possibly nonlinear hypotheses on the coefficients of MLR systems. For the case of uniform linear hypotheses, we present exact distributional invariance results concerning several standard test criteria. These include Wilks' likelihood ratio (LR) criterion as well as trace and maximum root criteria. The normality assumption is not necessary for most of the results to hold. Implications for inference are two-fold. First, invariance to nuisance parameters entails that the technique of Monte Carlo tests can be applied on all these statistics to obtain exact tests of uniform linear hypotheses. Second, the invariance property of the latter statistic is exploited to derive general nuisance-parameter-free bounds on the distribution of the LR statistic for arbitrary hypotheses. Even though it may be difficult to compute these bounds analytically, they can easily be simulated, hence yielding exact bounds Monte Carlo tests. Illustrative simulation experiments show that the bounds are sufficiently tight to provide conclusive results with a high probability. Our findings illustrate the value of the bounds as a tool to be used in conjunction with more traditional simulation-based test methods (e.g., the parametric bootstrap) which may be applied when the bounds are not conclusive.

Testing Mean-Variance Efficiency in CAPM with Possibly Non-Gaussian Errors : An Exact Simulation-Based Approach

In this paper we propose exact likelihood-based mean-variance efficiency tests of the market portfolio in the context of Capital Asset Pricing Model (CAPM), allowing for a wide class of error distributions which include normality as a special case. These tests are developed in the frame-work of multivariate linear regressions (MLR). It is well known however that despite their simple statistical structure, standard asymptotically justified MLR-based tests are unreliable. In financial econometrics, exact tests have been proposed for a few specific hypotheses [Jobson and Korkie (Journal of Financial Economics, 1982), MacKinlay (Journal of Financial Economics, 1987), Gib-bons, Ross and Shanken (Econometrica, 1989), Zhou (Journal of Finance 1993)], most of which depend on normality. For the gaussian model, our tests correspond to Gibbons, Ross and Shanken’s mean-variance efficiency tests. In non-gaussian contexts, we reconsider mean-variance efficiency tests allowing for multivariate Student-t and gaussian mixture errors. Our framework allows to cast more evidence on whether the normality assumption is too restrictive when testing the CAPM. We also propose exact multivariate diagnostic checks (including tests for multivariate GARCH and mul-tivariate generalization of the well known variance ratio tests) and goodness of fit tests as well as a set estimate for the intervening nuisance parameters. Our results [over five-year subperiods] show the following: (i) multivariate normality is rejected in most subperiods, (ii) residual checks reveal no significant departures from the multivariate i.i.d. assumption, and (iii) mean-variance efficiency tests of the market portfolio is not rejected as frequently once it is allowed for the possibility of non-normal errors.

Finite-Sample Diagnostics for Multivariate Regressions with Applications to Linear Asset Pricing Models

In this paper, we propose several finite-sample specification tests for multivariate linear regressions (MLR) with applications to asset pricing models. We focus on departures from the assumption of i.i.d. errors assumption, at univariate and multivariate levels, with Gaussian and non-Gaussian (including Student t) errors. The univariate tests studied extend existing exact procedures by allowing for unspecified parameters in the error distributions (e.g., the degrees of freedom in the case of the Student t distribution). The multivariate tests are based on properly standardized multivariate residuals to ensure invariance to MLR coefficients and error covariances. We consider tests for serial correlation, tests for multivariate GARCH and sign-type tests against general dependencies and asymmetries. The procedures proposed provide exact versions of those applied in Shanken (1990) which consist in combining univariate specification tests. Specifically, we combine tests across equations using the MC test procedure to avoid Bonferroni-type bounds. Since non-Gaussian based tests are not pivotal, we apply the “maximized MC” (MMC) test method [Dufour (2002)], where the MC p-value for the tested hypothesis (which depends on nuisance parameters) is maximized (with respect to these nuisance parameters) to control the test’s significance level. The tests proposed are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995. Our empirical results reveal the following. Whereas univariate exact tests indicate significant serial correlation, asymmetries and GARCH in some equations, such effects are much less prevalent once error cross-equation covariances are accounted for. In addition, significant departures from the i.i.d. hypothesis are less evident once we allow for non-Gaussian errors.

Construção de quadrados mágicos pelo método do passo uniforme

Lehmer (1929) analisa matematicamente o método do passo uniforme para construção de quadrados mágicos de ordem impar. Ele divide sua análise em várias etapas. Na primeira delas, envolvendo a discussão de condições necessárias e suficientes para o preenchimento do quadrado pelo método, o autor afirma que se dois números guardarem entre si uma certa relação, eles serão designados a ocupar a mesma célula do quadrado causando seu não preenchimento. A análise do preenchimento pelo método do passo uniforme envolve a resolução de um sistema linear módulo n. Nesse trabalho, discutimos o comportamento das soluções desse sistema quando o método falha no preenchimento. Como consequência, concluímos que números que guardam a relação mencionada nunca ocupam a mesma célula. A análise das condições necessárias e suficientes para obter quadrados mágicos segundo a definição de Lehmer (1929) envolve a resolução de equações de congruências lineares a duas variáveis. Nesse trabalho, detalhamos os resultados de Lehmer (1929). A análise das condições necessárias e suficientes para obtenção de quadrados mágicos, como são reconhecidos usualmente, também envolve a resolução de equações de congruências lineares a duas variáveis. Discutimos o comportamento das soluções dessas equações para obter diagonais principais mágicas. Como consequência, mostramos que diagonais principais mágicas são obtidas se e somente se as coordenadas iniciais guardarem certas relações

Riesgo de pérdida de nitratos por lixiviación en fertilizaciones nitrogenadas según manejo uniforme y sitio-específico del cultivo de maíz (Zea mays L.)

Cuando los suelos presentan variabilidad edáfica pronunciada a escala de lote y se fertiliza en forma uniforme en base a una dosis promedio de nitrógeno (N), existirán sectores sub-fertilizados y otros sobre-fertilizados que se asocian a un alto riesgo de pérdidas de N por lixiviación. El manejo sitio-específico (MSE) de la fertilización nitrogenada se sustenta en la capacidad de reconocer zonas de manejo para adecuar la aplicación de N a cada unidad reconocida. El objetivo general de esta Tesis fue evaluar la eficacia del MSE en minimizar el contenido de N residual y potencialmente lixiviable, y mejorar la eficiencia en el uso del N del maíz según zonas de manejo. Se determinó el contenido de agua y nitratos del suelo (2-3 m) en tratamientos de fertilización nitrogenada según manejo uniforme (MU) y MSE, previo a la fertilización y a poscosecha del maíz, durante dos años experimentales. La lixiviación de N fue estimada con el modelo NLEAP (Nitrate Leaching and Economic Analysis Package) mediante experimentos de simulación bajo distintos escenarios climáticos. Se observó una reducción del 32 por ciento del N residual en zonas de baja productividad de maíz con MSE de N, respecto del MU, únicamente en el segundo año experimental. Al ponderar el contenido de N residual por la proporción de las zonas de manejo a nivel lote, el MSE logró reducir un 18 por ciento el N residual en promedio en ambos años experimentales. En términos generales, se detectaron diferencias a favor del MSE, respecto del MU, en las eficiencias de uso de agua y N del maíz. Los experimentos de simulación evidenciaron una mayor lixiviación de nitratos con MU que con MSE a nivel lote en todos los escenarios climáticos estudiados del primer año experimental. El MSE de N puede ser considerado como una práctica conservacionista que optimice la eficiencia de uso del agua y N, a la vez de maximizar los rendimientos. Además, puede facilitar la identificación de aquellas áreas dentro del lote con mayor susceptibilidad a las pérdidas de N por lixiviación. La proporción de las zonas de manejo resulta un factor espacial imprescindible para determinar el riesgo potencial de lixiviación de nitratos a nivel lote

O Sistema uniforme de contas para a indústria hoteleira

Dissertação de Mestrado apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Contabilidade e Finanças, sob orientação de Professor Doutor Filipe Ambrósio e co-orientação do Mestre António Melo

[Portrait de garçon en uniforme de collégien à mi-jambes, debout portant un brassard de communiant] : [photographie] / Pierre Eugène Fixon

Ancien possesseur : Gilles, Albert (1873-1959)

[Léon Cugnet de Montarlot en uniforme] : [photographie] / Non identifié

Ancien possesseur : Gilles, Albert (1873-1959)