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.

A cautionary note on the use of Ornstein Uhlenbeck models in macroevolutionary studies

Phylogenetic comparative methods are increasingly used to give new insights into the dynamics of trait evolution in deep time. For continuous traits the core of these methods is a suite of models that attempt to capture evolutionary patterns by extending the Brownian constant variance model. However, the properties of these models are often poorly understood, which can lead to the misinterpretation of results. Here we focus on one of these models – the Ornstein Uhlenbeck (OU) model. We show that the OU model is frequently incorrectly favoured over simpler models when using Likelihood ratio tests, and that many studies fitting this model use datasets that are small and prone to this problem. We also show that very small amounts of error in datasets can have profound effects on the inferences derived from OU models. Our results suggest that simulating fitted models and comparing with empirical results is critical when fitting OU and other extensions of the Brownian model. We conclude by making recommendations for best practice in fitting OU models in phylogenetic comparative analyses, and for interpreting the parameters of the OU model.

Regulatory Change v's volume of trade effects in HSIF and HSI volatility

In an earlier paper we adopted a BEKK-GARCH framework and employed a systematic approach to examine structural breaks in the HSIF and HSI volatility. Switching dummy variables were included and tested in the variance equations to check for any structural changes in the autoregressive volatility structure due to the events that have taken place in the Hong Kong market. A Bi-variate GARCH model with 3 switching points was found to be superior as it captured the potential structural changes in return volatilities. Abolishment of the uptick rule, increase of initial margins for the HSIF and electronic trading of HSIF were found to have significant impact on the volatility structure of HSIF and HSI. In this paper we include measures of daily trading volume from both markets in the estimation. Likelihood ratio tests indicate the switching dummy variables become insignificant and the GARCH effects diminish but remain significant.

Modelling regulatory change V's volume of trading effects in HSIF and HSI volatility

In an earlier paper, we adopted a bi-variate BEKK–GARCH framework and employed a systematic approach to examine structural breaks in the Hang Seng Index and Index Futures market volatility. Switching dummy variables were included and tested in the variance equations to check for any structural changes in the autoregressive volatility structure due to the events that have taken place in the Hong Kong market surrounding the Asian markets crisis. In this paper, we include measures of daily trading volume from both markets in the estimation. Likelihood ratio tests indicate the switching dummy variables become insignificant and the GARCH effects diminish but remain significant. There is some evidence that the Sequential Arrival of Information Model (SIM) provides a platform to explain these market induced effects when volume of trade is accounted for.

Componentes de (co)variância e parâmetros genéticos de características de crescimento da raça Simental no Brasil

Informações de genealogia e produção, cedidas pela Associação Brasileira de Criadores da Raça Simental (ABCRS), relativas aos pesos desde o nascimento até um ano de idade, foram utilizadas para estimar, sob modelos alternativos, os componentes de variância e os parâmetros genéticos em animais da raça Simental no Brasil. A matriz de parentesco incluiu 25.812 animais dos quais 7587 com dados de produção. O modelo 1 contém, além do erro, o efeito genético direto. Os modelos seguintes contêm os componentes do modelo 1, mais o efeito permanente de ambiente materno (modelo 2), ou o componente genético materno (modelo 3), ambos os componentes (modelo 5), os componentes do modelo 3 mais a covariância entre os efeitos genéticos direto e materno (modelo 4) e todos os componentes citados (modelo 6). Os modelos foram comparados pelo teste de razão de verossimilhança pelo chi² (P<0,01). Os componentes de variância e os valores de herdabilidades, estimados para os efeitos direto e materno, foram decrescentes, desde o modelo 1 até o modelo 6, na razão direta em que o modelo incorpora mais efeitos aleatórios. Para a fase de aleitamento foi encontrada variância genética nula, entretanto, alto valor para a variância de ambiente permanente. Os efeitos maternos, genético e de ambiente permanente são importantes para a raça Simental no Brasil e devem ser considerados em programas de seleção. Entretanto, os valores mais elevados de herdabilidade materna, encontrados com modelos sem efeito de ambiente permanente, sugerem que o método utilizado não discrimina apropriadamente esses efeitos, oriundos de mesma fonte de variação.

Tracking of plasma lipids and lipoproteins, within-person and year-to-year variability in plasma cholesterol levels among participants from age 8 to 18 in Project HeartBeat!

Coronary heart disease remains the leading cause of death in the United States and increased blood cholesterol level has been found to be a major risk factor with roots in childhood. Tracking of cholesterol, i.e., the tendency to maintain a particular cholesterol level relative to the rest of the population, and variability in blood lipid levels with increase in age have implications for cholesterol screening and assessment of lipid levels in children for possible prevention of further rise to prevent adulthood heart disease. In this study the pattern of change in plasma lipids, over time, and their tracking were investigated. Also, within-person variance and retest reliability defined as the square root of within-person variance for plasma total cholesterol, HDL-cholesterol, LDL-cholesterol, and triglycerides and their relation to age, sex and body mass index among participants from age 8 to 18 years were investigated. ^ In Project HeartBeat!, 678 healthy children aged 8, 11 and 14 years at baseline were enrolled and examined at 4-monthly intervals for up to 4 years. We examined the relationship between repeated observations by Pearson's correlations. Age- and sex-specific quintiles were calculated and the probability of participants to remain in the uppermost quintile of their respective distribution was evaluated with life table methods. Plasma total cholesterol, HDL-C and LDL-C at baseline were strongly and significantly correlated with measurements at subsequent visits across the sex and age groups. Plasma triglyceride at baseline was also significantly correlated with subsequent measurements but less strongly than was the case for other plasma lipids. The probability to remain in the upper quintile was also high (60 to 70%) for plasma total cholesterol, HDL-C and LDL-C. ^ We used a mixed longitudinal, or synthetic cohort design with continuous observations from age 8 to 18 years to estimate within person variance of plasma total cholesterol, HDL-C, LDL-C and triglycerides. A total of 5809 measurements were available for both cholesterol and triglycerides. A multilevel linear model was used. Within-person variance among repeated measures over up to four years of follow-up was estimated for total cholesterol, HDL-C, LDL-C and triglycerides separately. The relationship of within-person and inter-individual variance with age, sex, and body mass index was evaluated. Likelihood ratio tests were conducted by calculating the deviation of −2log (likelihood) within the basic model and alternative models. The square root of within-person variance provided the retest reliability (within person standard deviation) for plasma total cholesterol, HDL-C, LDL-C and triglycerides. We found 13.6 percent retest reliability for plasma cholesterol, 6.1 percent for HDL-cholesterol, 11.9 percent for LDL-cholesterol and 32.4 percent for triglycerides. Retest reliability of plasma lipids was significantly related with age and body mass index. It increased with increase in body mass index and age. These findings have implications for screening guidelines, as participants in the uppermost quintile tended to maintain their status in each of the age groups during a four-year follow-up. The magnitude of within-person variability of plasma lipids influences the ability to classify children into risk categories recommended by the National Cholesterol Education Program. ^

Statnote 5: Is one set of data more variable than another?

There may be circumstances where it is necessary for microbiologists to compare variances rather than means, e,g., in analysing data from experiments to determine whether a particular treatment alters the degree of variability or testing the assumption of homogeneity of variance prior to other statistical tests. All of the tests described in this Statnote have their limitations. Bartlett’s test may be too sensitive but Levene’s and the Brown-Forsythe tests also have problems. We would recommend the use of the variance-ratio test to compare two variances and the careful application of Bartlett’s test if there are more than two groups. Considering that these tests are not particularly robust, it should be remembered that the homogeneity of variance assumption is usually the least important of those considered when carrying out an ANOVA. If there is concern about this assumption and especially if the other assumptions of the analysis are also not likely to be met, e.g., lack of normality or non additivity of treatment effects then it may be better either to transform the data or to carry out a non-parametric test on the data.

Informational efficiency of the European Union emission allowance market

This thesis studies the informational efficiency of the European Union emission allowance (EUA) market. In an efficient market, the market price is unpredictable and profits above average are impossible in the long run. The main research problem is does the EUA price follow a random walk. The method is an econometric analysis of the price series, which includes an autocorrelation coefficient test and a variance ratio test. The results reveal that the price series is autocorrelated and therefore a nonrandom walk. In order to find out the extent of predictability, the price series is modelled with an autoregressive model. The conclusion is that the EUA price is autocorrelated only to a small degree and that the predictability cannot be used to make extra profits. The EUA market is therefore considered informationally efficient, although the price series does not fulfill the requirements of a random walk. A market review supports the conclusion, but it is clear that the maturing of the market is still in process.

Robust and High-resolution Voiced/Unvoiced Classification in Noisy Speech Using A Signal Smoothness Criterion

We propose a novel technique for robust voiced/unvoiced segment detection in noisy speech, based on local polynomial regression. The local polynomial model is well-suited for voiced segments in speech. The unvoiced segments are noise-like and do not exhibit any smooth structure. This property of smoothness is used for devising a new metric called the variance ratio metric, which, after thresholding, indicates the voiced/unvoiced boundaries with 75% accuracy for 0dB global signal-to-noise ratio (SNR). A novelty of our algorithm is that it processes the signal continuously, sample-by-sample rather than frame-by-frame. Simulation results on TIMIT speech database (downsampled to 8kHz) for various SNRs are presented to illustrate the performance of the new algorithm. Results indicate that the algorithm is robust even in high noise levels.

Conditional Moments in Asset Pricing

A better understanding of stock price changes is important in guiding many economic activities. Since prices often do not change without good reasons, searching for related explanatory variables has involved many enthusiasts. This book seeks answers from prices per se by relating price changes to their conditional moments. This is based on the belief that prices are the products of a complex psychological and economic process and their conditional moments derive ultimately from these psychological and economic shocks. Utilizing information about conditional moments hence makes it an attractive alternative to using other selective financial variables in explaining price changes. The first paper examines the relation between the conditional mean and the conditional variance using information about moments in three types of conditional distributions; it finds that the significance of the estimated mean and variance ratio can be affected by the assumed distributions and the time variations in skewness. The second paper decomposes the conditional industry volatility into a concurrent market component and an industry specific component; it finds that market volatility is on average responsible for a rather small share of total industry volatility — 6 to 9 percent in UK and 2 to 3 percent in Germany. The third paper looks at the heteroskedasticity in stock returns through an ARCH process supplemented with a set of conditioning information variables; it finds that the heteroskedasticity in stock returns allows for several forms of heteroskedasticity that include deterministic changes in variances due to seasonal factors, random adjustments in variances due to market and macro factors, and ARCH processes with past information. The fourth paper examines the role of higher moments — especially skewness and kurtosis — in determining the expected returns; it finds that total skewness and total kurtosis are more relevant non-beta risk measures and that they are costly to be diversified due either to the possible eliminations of their desirable parts or to the unsustainability of diversification strategies based on them.

Strength and Deformation Characteristics of Fly Ash Mixed with Randomly Distributed Plastic Waste

In order to explore the potential use of fly ash and plastic waste in bulk quantities in civil engineering applications, it is necessary to understand the behavior of fly ash and fly ash mixed with plastic waste. These materials are considered as wastes and in this study, it is shown that combination of fly ash and plastic waste is very useful. In this regard, various tests such as classification tests, unconfined compressive strength and compressibility tests, consolidated undrained tests, and California bearing ratio tests were conducted. The results indicated that the inclusion of plastic waste in fly ash is effective in improving the engineering properties of fly ash in terms of compressive strength, shear strength parameters, and CBR values. In order to understand the effect of sample size on the shear strength parameters of fly ash and fly ash mixed with plastic waste, consolidated undrained tests were conducted with sample sizes of 38x76mm and 50x100mm. The results of the tests indicate that the shear strength increases with the increase in sample size. The implication of the use of fly ash mixed with plastic waste in unpaved roads is presented in terms of reduction of carbon print.

Preparação e caracterização de microesferas poliméricas à base de poli(ácido metacrílico-co-divinilbenzeno) obtidas por polimerização por precipitação

Neste trabalho foi feito um estudo sobre a preparação e caracterização de microesferas poliméricas à base de poli(ácido metacrílico-co-divinilbenzeno) por polimerização por precipitação. As partículas foram sintetizadas e analisadas em diferentes condições de reação. Partículas esféricas políméricas foram sintetizadas na faixa de 1,66 - 8,41 m, assim como partículas no estado de microgel. As partículas foram caracterizadas pelas técnicas de espalhamento de luz dinâmica (DLS), análise termogravimétrica (TGA), espectroscopia na região do infravermelho (FTIR), adsorção de nitrogênio pelos métodos BET (Brunauer, Emmett e Teller) e BJH (Barret, Joyner e Halenda), microscopia ótica, microscopia eletrônica de varredura, e testes de razão de inchamento. A análise das partículas foi feita para verificar a influência da mudança na composição de comonômeros, grau de reticulação, relação de monômeros totais/diluentes em massa/volume (g/100 mL), e quanto à relação volumétrica de diluentes. Verificou-se que houve um aumento no tamanho das partículas e da resistência térmica com a diminuição da fração molar de MAA (ácido metacrílico). Na preparação de partículas com fração molar de 50% de MAA, e relação volumétrica acetonitrila/tolueno de 75/25, quanto maior a relação de monômeros totais/diluentes (g/100 mL), maior o tamanho e o rendimento das partículas. Com a mudança da relação volumétrica de diluentes, houve mudança nas características de porosidade, tamanho das partículas, e grau de inchamento das partículas, sendo que na relação volumétrica acetonitrila/tolueno de 50/50, houve formação de microgel

Integrating methods for determining length-at-age to improve growth estimates for two large scombrids

Fish growth is commonly estimated from length-at-age data obtained from otoliths. There are several techniques for estimating length-at-age from otoliths including 1) direct observed counts of annual increments; 2) age adjustment based on a categorization of otolith margins; 3) age adjustment based on known periods of spawning and annuli formation; 4) back-calculation to all annuli, and 5) back-calculation to the last annulus only. In this study we compared growth estimates (von Bertalanffy growth functions) obtained from the above five methods for estimating length-at-age from otoliths for two large scombrids: narrow-barred Spanish mackerel (Scomberomorus commerson) and broad-barred king mackerel (Scomberomorus semifasciatus). Likelihood ratio tests revealed that the largest differences in growth occurred between the back-calculation methods and the observed and adjusted methods for both species of mackerel. The pattern, however, was more pronounced for S. commerson than for S. semifasciatus, because of the pronounced effect of gear selectivity demonstrated for S. commerson. We propose a method of substituting length-at-age data from observed or adjusted methods with back-calculated length-at-age data to provide more appropriate estimates of population growth than those obtained with the individual methods alone, particularly when faster growing young fish are disproportionately selected for. Substitution of observed or adjusted length-at-age data with back-calculated length-at-age data provided more realistic estimates of length for younger ages than observed or adjusted methods as well as more realistic estimates of mean maximum length than those derived from backcalculation methods alone.

Estimates of growth and comparisons of growth rates determined from length- and age-based models for populations of purple wrasse (Notolabrus fucicola)

Growth of a temperate reefa-ssociated fish, the purple wrasse (Notolabrus fucicola), was examined from two sites on the east coast of Tasmania by using age- and length-based models. Models based on the von Bertalanffy growth function, in the standard and a reparameterized form, were constructed by using otolith-derived age estimates. Growth trajectories from tag-recaptures were used to construct length-based growth models derived from the GROTAG model, in turn a reparameterization of the Fabens model. Likelihood ratio tests (LRTs) determined the optimal parameterization of the GROTAG model, including estimators of individual growth variability, seasonal growth, measurement error, and outliers for each data set. Growth models and parameter estimates were compared by bootstrap confidence intervals, LRTs, and randomization tests and plots of bootstrap parameter estimates. The relative merit of these methods for comparing models and parameters was evaluated; LRTs combined with bootstrapping and randomization tests provided the most insight into the relationships between parameter estimates. Significant differences in growth of purple wrasse were found between sites in both length- and age-based models. A significant difference in the peak growth season was found between sites, and a large difference in growth rate between sexes was found at one site with the use of length-based models.

A general framework for integrating environmental time series into stock assessment models: model description, simulation testing, and example

We present a method to integrate environmental time series into stock assessment models and to test the significance of correlations between population processes and the environmental time series. Parameters that relate the environmental time series to population processes are included in the stock assessment model, and likelihood ratio tests are used to determine if the parameters improve the fit to the data significantly. Two approaches are considered to integrate the environmental relationship. In the environmental model, the population dynamics process (e.g. recruitment) is proportional to the environmental variable, whereas in the environmental model with process error it is proportional to the environmental variable, but the model allows an additional temporal variation (process error) constrained by a log-normal distribution. The methods are tested by using simulation analysis and compared to the traditional method of correlating model estimates with environmental variables outside the estimation procedure. In the traditional method, the estimates of recruitment were provided by a model that allowed the recruitment only to have a temporal variation constrained by a log-normal distribution. We illustrate the methods by applying them to test the statistical significance of the correlation between sea-surface temperature (SST) and recruitment to the snapper (Pagrus auratus) stock in the Hauraki Gulf–Bay of Plenty, New Zealand. Simulation analyses indicated that the integrated approach with additional process error is superior to the traditional method of correlating model estimates with environmental variables outside the estimation procedure. The results suggest that, for the snapper stock, recruitment is positively correlated with SST at the time of spawning.