Flexible multivariate GARCH modeling with an application to international stock markets

This paper offers a new approach to estimating time-varying covariance matrices in the framework of the diagonal-vech version of the multivariate GARCH(1,1) model. Our method is numerically feasible for large-scale problems, produces positive semidefinite conditional covariance matrices, and does not impose unrealistic a priori restrictions. We provide an empirical application in the context of international stock markets, comparing the nev^ estimator with a number of existing ones.

Quantitative genetic modeling and inference in the presence of nonignorable missing data.

Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.

Flexible multivariate GARCH modeling with an application to international stock markets

The goal of this paper is to estimate time-varying covariance matrices.Since the covariance matrix of financial returns is known to changethrough time and is an essential ingredient in risk measurement, portfolioselection, and tests of asset pricing models, this is a very importantproblem in practice. Our model of choice is the Diagonal-Vech version ofthe Multivariate GARCH(1,1) model. The problem is that the estimation ofthe general Diagonal-Vech model model is numerically infeasible indimensions higher than 5. The common approach is to estimate more restrictive models which are tractable but may not conform to the data. Our contributionis to propose an alternative estimation method that is numerically feasible,produces positive semi-definite conditional covariance matrices, and doesnot impose unrealistic a priori restrictions. We provide an empiricalapplication in the context of international stock markets, comparing thenew estimator to a number of existing ones.

Multivariate genetic divergence and hybrid performance of cacao (Theobroma cacao L.)

Genetic distances among cacao cultivars were calculated through multivariate analysis, using the D2 statistic, to examine racial group classification and to assess heterotic hybrids. A 5 x 5 complete diallel was evaluated. Over a five-year period (1986-1990), five cultivars of the S1 generation, pertaining to the Lower Amazon Forastero and Trinitario racial groups and 20 crosses between the corresponding S0 parents were analyzed, based upon five yield components - number of healthy and collected fruits per plant (NHFP and NCFP), wet seed weight per plant and per fruit (WSWP and WSWF), and percentage of diseased fruits per plant (PDFP). The diversity analysis suggested a close relationship between the Trinitario and Lower Amazon Forastero groups. A correlation coefficient (r) was calculated to determine the association between genetic diversity and heterosis. Genetic distance of parents by D2 was found to be linearly related to average performance of hybrids for WSWP and WSWF (r = 0.68, P < 0.05 and r = 0.76, P < 0.05, respectively). The heterotic performance for the same components was also correlated with D2, both with r = 0.66 (P < 0.05). A relationship between genetic divergence and combining ability effects was suggested because the most divergent cultivar exhibited a high general combining ability, generating the best performing hybrids. Results indicated that genetic diversity estimates can be useful in selecting parents for crosses and in assessing relationships among cacao racial groups.

Experimental evolution for generalists and specialists reveals multivariate genetic constraints on thermal reaction norms

Theory predicts the emergence of generalists in variable environments and antagonistic pleiotropy to favour specialists in constant environments, but empirical data seldom support such generalist–specialist trade-offs. We selected for generalists and specialists in the dung fly Sepsis punctum (Diptera: Sepsidae) under conditions that we predicted would reveal antagonistic pleiotropy and multivariate trade-offs underlying thermal reaction norms for juvenile development. We performed replicated laboratory evolution using four treatments: adaptation at a hot (31 °C) or a cold (15 °C) temperature, or under regimes fluctuating between these temperatures, either within or between generations. After 20 generations, we assessed parental effects and genetic responses of thermal reaction norms for three correlated life-history traits: size at maturity, juvenile growth rate and juvenile survival. We find evidence for antagonistic pleiotropy for performance at hot and cold temperatures, and a temperature-mediated trade-off between juvenile survival and size at maturity, suggesting that trade-offs associated with environmental tolerance can arise via intensified evolutionary compromises between genetically correlated traits. However, despite this antagonistic pleiotropy, we found no support for the evolution of increased thermal tolerance breadth at the expense of reduced maximal performance, suggesting low genetic variance in the generalist–specialist dimension.

A genetic investigation of the covariation among Inspection Time, Choice Reaction Time, and IQ subtest scores

Information processing speed, as measured by elementary cognitive tasks, is correlated with higher order cognitive ability so that increased speed relates to improved cognitive performance. The question of whether the genetic variation in Inspection Time (IT) and Choice Reaction Time (CRT) is associated with IQ through a unitary factor was addressed in this multivariate genetic study of IT, CRT, and IQ subtest scores. The sample included 184 MZ and 206 DZ twin pairs with a mean age of 16.2 years (range 15-18 years). They were administered a visual (pi-figure) IT task, a two-choice RT task, five computerized subtests of the Multidimensional Aptitude Battery, and the digit symbol substitution subtest from the WAIS-R. The data supported a factor model comprising a general, three group (verbal ability, visuospatial ability, broad speediness), and specific genetic factor structure, a shared environmental factor influencing all tests but IT, plus unique environmental factors that were largely specific to individual measures. The general genetic factor displayed factor loadings ranging between 0.35 and 0.66 for the IQ subtests, with IT and CRT loadings of -0.47 and -0.24, respectively. Results indicate that a unitary factor is insufficient to describe the entire relationship between cognitive speed measures and all IQ subtests, with independent genetic effects explaining further covariation between processing speed (especially CRT) and Digit Symbol.

Multivariate genetic analysis of cognitive abilities in an adolescent twin sample

The sources of covariation among cognitive measures of Inspection Time, Choice Reaction Time, Delayed Response Speed and Accuracy, and IQ were examined in a classical twin design that included 245 monozygotic (MZ) and 298 dizygotic (DZ) twin pairs. Results indicated that a factor model comprising additive genetic and unique environmental effects was the most parsimonious. In this model, a general genetic cognitive factor emerged with factor loadings ranging from 0.28 to 0.64. Three other genetic factors explained the remaining genetic covariation between various speed and Delayed Response measures with IQ. However, a large proportion of the genetic variation in verbal (54%) and performance (25%) IQ was unrelated to these lower order cognitive measures. The independent genetic IQ variation may reflect information processes not captured by the elementary cognitive tasks, Inspection Time and Choice Reaction Time, nor our working memory task, Delayed Response. Unique environmental effects were mostly nonoverlapping, and partly represented test measurement error.

Multivariate genetic analysis of academic skills of the Queensland Core Skills Test and IQ highlight the importance of genetic g

This study examined the genetic and environmental relationships among 5 academic achievement skills of a standardized test of academic achievement, the Queensland Core Skills Test (QCST; Queensland Studies Authority, 2003a). QCST participants included 182 monozygotic pairs and 208 dizygotic pairs (mean 17 years +/- 0.4 standard deviation). IQ data were included in the analysis to correct for ascertainment bias. A genetic general factor explained virtually all genetic variance in the component academic skills scores, and accounted for 32% to 73% of their phenotypic variances. It also explained 56% and 42% of variation in Verbal IQ and Performance IQ respectively, suggesting that this factor is genetic g. Modest specific genetic effects were evident for achievement in mathematical problem solving and written expression. A single common factor adequately explained common environmental effects, which were also modest, and possibly due to assortative mating. The results suggest that general academic ability, derived from genetic influences and to a lesser extent common environmental influences, is the primary source of variation in component skills of the QCST.

Multivariate statistical modeling of an anode backing furnace - Modélisation statistique multivariée du four à cuisson des anodes utilisées dans la fabrication d'aluminium primaire

La stratégie actuelle de contrôle de la qualité de l’anode est inadéquate pour détecter les anodes défectueuses avant qu’elles ne soient installées dans les cuves d’électrolyse. Des travaux antérieurs ont porté sur la modélisation du procédé de fabrication des anodes afin de prédire leurs propriétés directement après la cuisson en utilisant des méthodes statistiques multivariées. La stratégie de carottage des anodes utilisée à l’usine partenaire fait en sorte que ce modèle ne peut être utilisé que pour prédire les propriétés des anodes cuites aux positions les plus chaudes et les plus froides du four à cuire. Le travail actuel propose une stratégie pour considérer l’histoire thermique des anodes cuites à n’importe quelle position et permettre de prédire leurs propriétés. Il est montré qu’en combinant des variables binaires pour définir l’alvéole et la position de cuisson avec les données routinières mesurées sur le four à cuire, les profils de température des anodes cuites à différentes positions peuvent être prédits. Également, ces données ont été incluses dans le modèle pour la prédiction des propriétés des anodes. Les résultats de prédiction ont été validés en effectuant du carottage supplémentaire et les performances du modèle sont concluantes pour la densité apparente et réelle, la force de compression, la réactivité à l’air et le Lc et ce peu importe la position de cuisson.

A genetic two-factor model of the covariation among a subset of Multidimensional Aptitude Battery and Wechsler Adult Intelligence Scale - Revised subtests

The phenotypic and genetic factor structure of performance on five Multidimensional Aptitude Battery (MAB) subtests and one Wechsler Adult Intelligence Scale-Revised (WAIS-R) subtest was explored in 390 adolescent twin pairs (184 monozygotic [MZ]; 206 dizygotic (DZ)). The temporal stability of these measures was derived from a subsample of 49 twin pairs, with test-retest correlations ranging from .67 to .85. A phenotypic factor model, in which performance and verbal factors were correlated, provided a good fit to the data. Genetic modeling was based on the phenotypic factor structure, but also took into account the additive genetic (A), common environmental (C), and unique environmental (E) parameters derived from a fully saturated ACE model. The best fitting model was characterized by a genetic correlated two-factor structure with specific effects, a general common environmental factor, and overlapping unique environmental effects. Results are compared to multivariate genetic models reported in children and adults, with the most notable difference being the growing importance of common genes influencing diverse abilities in adolescence. (C) 2003 Elsevier Inc. All rights reserved.

Phenotypic and genetic analyses of a short measure of psychosis-proneness in a large-scale Australian twin study

Previous genetic analyses of psychosis proneness have been limited by their small sample size. For the purposes of large-scale screening, a 12-item questionnaire was developed through a two-stage process of reduction from the full Chapman and Chapman scales. 3685 individuals (including 1438 complete twin pairs) aged 18–25 years and enrolled in the volunteer Australian Twin Registry returned a mail questionnaire which included this psychosis proneness scale and the Eysenck Personality Questionnaire. Despite the brevity of the questionnaire, item and factor analysis identified four unambiguous and essentially uncorrelated scales. There were (1) Perceptual Aberration – Magical Ideation; (2) Hypomania – Impulsivity/Nonconformity; (3) Social Anhedonia and (4) Physical Anhedonia. Model-fitting analyses showed additive genetic and specific environmental factors were sufficient for three of the four scales, with the Social Anhedonia scale requiring also a parameter for genetic dominance. There was no evidence for the previously hypothesised sex differences in the genetic determination of psychosis-proneness. The potential value of multivariate genetic analysis to examine the relationship between these four scales and dimensions of personality is discussed. The growing body of longitudinal evidence on psychosis-proneness suggests the value of incorporating this brief measure into developmental twin studies.

Genetic sources of covariation among P3(00) and online performance variables in a delayed-response working memory task

Genetic and environmental sources of covariation among the P3(00) and online performance elicited in a delayed-response working memory task, and psychometric IQ assessed by the multidimensional aptitude battery, were examined in an adolescent twin sample. An association between frontal P3 latency and task performance (phenotypic r = -0.33; genotypic r = -0.49) was indicated, with genes (i.e. twin status) accounting for a large part of the covariation ( > 70%). In contrast, genes influencing P3 amplitude mediated only a small part (2%) of the total genetic variation in task performance. While task performance mediated 15% of the total genetic variation in IQ (phenotypic r = 0.22; genotypic r = 0.39) there was no association between P3 latency and IQ or P3 amplitude with IQ. The findings provide some insight into the inter-relationships among psychophysiological, performance and psychometric measures of cognitive ability, and provide support for a levels-of-processing genetic model of cognition where genes act on specific sub-components of cognitive processes.

Genetic and environmental influences on blood pressure and physical activity: a study of nuclear families from Muzambinho, Brazil

Blood pressure (BP) and physical activity (PA) levels are inversely associated. Since genetic factors account for the observed variation in each of these traits, it is possible that part of their association may be related to common genetic and/or environmental influences. Thus, this study was designed to estimate the genetic and environmental correlations of BP and PA phenotypes in nuclear families from Muzambinho, Brazil. Families including 236 offspring (6 to 24 years) and their 82 fathers and 122 mothers (24 to 65 years) were evaluated. BP was measured, and total PA (TPA) was assessed by an interview (commuting, occupational, leisure time, and school time PA). Quantitative genetic modeling was used to estimate maximal heritability (h²), and genetic and environmental correlations. Heritability was significant for all phenotypes (systolic BP: h² = 0.37 ± 0.10, P < 0.05; diastolic BP: h² = 0.39 ± 0.09, P < 0.05; TPA: h² = 0.24 ± 0.09, P < 0.05). Significant genetic (r g) and environmental (r e) correlations were detected between systolic and diastolic BP (r g = 0.67 ± 0.12 and r e = 0.48 ± 0.08, P < 0.05). Genetic correlations between BP and TPA were not significant, while a tendency to an environmental cross-trait correlation was found between diastolic BP and TPA (r e = -0.18 ± 0.09, P = 0.057). In conclusion, BP and PA are under genetic influences. Systolic and diastolic BP share common genes and environmental influences. Diastolic BP and TPA are probably under similar environmental influences.

Geochemical characterization of heavy metal contaminated area using multivariate factorial kriging

This paper describes a geostatistical method, known as factorial kriging analysis, which is well suited for analyzing multivariate spatial information. The method involves multivariate variogram modeling, principal component analysis, and cokriging. It uses several separate correlation structures, each corresponding to a specific spatial scale, and yields a set of regionalized factors summarizing the main features of the data for each spatial scale. This method is applied to an area of high manganese-ore mining activity in Amapa State, North Brazil. Two scales of spatial variation (0.33 and 2.0 km) are identified and interpreted. The results indicate that, for the short-range structure, manganese, arsenic, iron, and cadmium are associated with human activities due to the mining work, while for the long-range structure, the high aluminum, selenium, copper, and lead concentrations, seem to be related to the natural environment. At each scale, the correlation structure is analyzed, and regionalized factors are estimated by cokriging and then mapped.