Variance reduction properties of dynamic hedging models - empirical evidence from BRICS countries

This Master’s Thesis analyses the effectiveness of different hedging models on BRICS (Brazil, Russia, India, China, and South Africa) countries. Hedging performance is examined by comparing two different dynamic hedging models to conventional OLS regression based model. The dynamic hedging models being employed are Constant Conditional Correlation (CCC) GARCH(1,1) and Dynamic Conditional Correlation (DCC) GARCH(1,1) with Student’s t-distribution. In order to capture the period of both Great Moderation and the latest financial crisis, the sample period extends from 2003 to 2014. To determine whether dynamic models outperform the conventional one, the reduction of portfolio variance for in-sample data with contemporaneous hedge ratios is first determined and then the holding period of the portfolios is extended to one and two days. In addition, the accuracy of hedge ratio forecasts is examined on the basis of out-of-sample variance reduction. The results are mixed and suggest that dynamic hedging models may not provide enough benefits to justify harder estimation and daily portfolio adjustment. In this sense, the results are consistent with the existing literature.

A control chart based on sample ranges for monitoring the covariance matrix of the multivariate processes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A new chart based on sample variances for monitoring the covariance matrix of multivariate processes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Improved estimation of the covariance matrix of stock returns with an application to portofolio selection

This paper proposes to estimate the covariance matrix of stock returnsby an optimally weighted average of two existing estimators: the samplecovariance matrix and single-index covariance matrix. This method isgenerally known as shrinkage, and it is standard in decision theory andin empirical Bayesian statistics. Our shrinkage estimator can be seenas a way to account for extra-market covariance without having to specifyan arbitrary multi-factor structure. For NYSE and AMEX stock returns from1972 to 1995, it can be used to select portfolios with significantly lowerout-of-sample variance than a set of existing estimators, includingmulti-factor models.

Verkkovaihtosuuntaajan vektorisäädön toteutus FPGA-piirillä

Verkkovaihtosuuntaajalla pystytään muuntamaan tasajännite vaihtojännitteeksi ja päinvastoin. Verkkovaihtosuuntaajan toiminta perustuu tehokytkinten ohjaukseen ja sopivan modulointimenetelmän käyttöön. Vektorisäädössä vaihtosuuntaajanvirrat ja jännitteet esitetään kompleksitasossa, jolloin virta- ja jännitekomponentit voidaan esittää vektoreina. Vektorisäädössä verkkovaihtosuuntaajan ohjaustoteutetaan laskemalla kompleksitasossa vektoreille arvot, jotka tuottavat vaihtosuuntaajan lähtöön halutun vektorin. Koska FPGA-piirit mahdollistavat nopean rinnakkaisen laskennan, soveltuvat ne hyvin vektorisäädön toteuttamiseen. FPGA-piirien rakenteesta johtuen on säätöjärjestelmän suunnittelussa huomioitava kiinteän pilkun lukujen riittävä bittileveys ja järjestelmän diskretointiaika. Työssä suunnitellaan verkkovaihtosuuntaajan vektorisäätö ja tutkitaan bittileveyden vaikutusta säädön toteuttamiseen FPGA-piirillä. Bittileveyden tarkasteluun esitetään käytettäväksi tilastollisia menetelmiä. Työssä tarkastellaan kiinteän pilkun järjestelmän ja liukulukujärjestelmän erosuureen tilastollisia tunnusmerkkejä sekä histogrammia. Tarkasteluissa huomattiin, että maksimivirhe itsessään ei tarjoa riittävästi tietoa erosuureen jakautumisesta. Näin ollen maksimivirhe ei ole kaikissa tilanteissa sovelias menetelmä riittävän bittitarkkuuden määrittämiseen. Työssä esitetään riittävän bittitarkkuuden määrittelemiseen käytettäväksi otossuureista otosvarianssia, keskipoikkeamaa ja vaihteluväliä.

Climate trends in the municipality of Pelotas, state of Rio Grande do Sul, Brazil

ABSTRACTChanges in the frequency of occurrence of extreme weather events have been pointed out as a likely impact of global warming. In this context, this study aimed to detect climate change in series of extreme minimum and maximum air temperature of Pelotas, State of Rio Grande do Sul, (1896 - 2011) and its influence on the probability of occurrence of these variables. We used the general extreme value distribution (GEV) in its stationary and non-stationary forms. In the latter case, GEV parameters are variable over time. On the basis of goodness-of-fit tests and of the maximum likelihood method, the GEV model in which the location parameter increases over time presents the best fit of the daily minimum air temperature series. Such result describes a significant increase in the mean values of this variable, which indicates a potential reduction in the frequency of frosts. The daily maximum air temperature series is also described by a non-stationary model, whose location parameter decreases over time, and the scale parameter related to sample variance rises between the beginning and end of the series. This result indicates a drop in the mean of daily maximum air temperature values and increased dispersion of the sample data.

Geostatistical radar-raingauge combination with nonparametric correlograms: methodological considerations and application in Switzerland

Modelling spatial covariance is an essential part of all geostatistical methods. Traditionally, parametric semivariogram models are fit from available data. More recently, it has been suggested to use nonparametric correlograms obtained from spatially complete data fields. Here, both estimation techniques are compared. Nonparametric correlograms are shown to have a substantial negative bias. Nonetheless, when combined with the sample variance of the spatial field under consideration, they yield an estimate of the semivariogram that is unbiased for small lag distances. This justifies the use of this estimation technique in geostatistical applications. Various formulations of geostatistical combination (Kriging) methods are used here for the construction of hourly precipitation grids for Switzerland based on data from a sparse realtime network of raingauges and from a spatially complete radar composite. Two variants of Ordinary Kriging (OK) are used to interpolate the sparse gauge observations. In both OK variants, the radar data are only used to determine the semivariogram model. One variant relies on a traditional parametric semivariogram estimate, whereas the other variant uses the nonparametric correlogram. The variants are tested for three cases and the impact of the semivariogram model on the Kriging prediction is illustrated. For the three test cases, the method using nonparametric correlograms performs equally well or better than the traditional method, and at the same time offers great practical advantages. Furthermore, two variants of Kriging with external drift (KED) are tested, both of which use the radar data to estimate nonparametric correlograms, and as the external drift variable. The first KED variant has been used previously for geostatistical radar-raingauge merging in Catalonia (Spain). The second variant is newly proposed here and is an extension of the first. Both variants are evaluated for the three test cases as well as an extended evaluation period. It is found that both methods yield merged fields of better quality than the original radar field or fields obtained by OK of gauge data. The newly suggested KED formulation is shown to be beneficial, in particular in mountainous regions where the quality of the Swiss radar composite is comparatively low. An analysis of the Kriging variances shows that none of the methods tested here provides a satisfactory uncertainty estimate. A suitable variable transformation is expected to improve this.

Meta-análise de parâmetros genéticos relacionados ao consumo alimentar residual e a suas características componentes em bovinos

The objective of this work was to estimate, by meta-analysis, the heritability (h(2)) and the genetic (r(g)) and phenotypic (r(f)) correlations of residual feed intake (RFI), and of its component traits in beef cattle from 19 breeds or genetic groups. Twenty-two scientific papers published from 1963 to 2011, from eight countries, totaling 52,637 cattle of ages from 28 days up to slaughter, were evaluated. The estimates of RFI, dry matter intake (DMI), average daily gain (ADG) and metabolic weight (BW0.75) were weighted by the inverse of sample variance. The variation between studies of h(2) for each trait was analyzed by weighted least squares. The effects of sex, country and breed were significant for h(2) of RFI, explaining 67% of variation between studies. For DMI, country and breed effects were significant and explained 96% of variation. Pooled estimates of h(2) were: 0.255+/-0.008, 0.278+/-0.012, 0.321+/-0.015, and 0.397+/-0.032 for RFI, DMI, ADG and BW0.75, respectively. Pooled estimates of genetic and phenotypic correlations were low between RFI and ADG and between RFI and BW0.75 (from -0.021+/-0.034 to 0.025+/-0.035), and moderate between RFI and DMI (0.636+/-0.035 and 0.698+/-0.041) and between DMI, ADG and BW0.75 (0.441+/-0.062 to 0.688+/-0.032). The trait RFI has lower heritability estimates than its components.

A single statistic for monitoring the covariance matrix of bivariate processes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Comportamento Espacial dos Percentis 75 da Precipitação Decencial para O Estado de São Paulo, Na Primavera

No presente estudo foi avaliada a distribuição espacial do percentil 75 da precipitação decendial para o Estado de São Paulo, utilizando-se um total de 136 postos pluviométricos com séries acima de 27 anos de registros. Em um estágio preliminar os valores dos percentis 75 da precipitação decendial foram georeferenciados, permitindo a utilização de técnicas da geoestatística para proceder à interpolação dos dados. Modelos experimentais de semivariogramas padronizados foram obtidos, utilizando-se a variância amostral como fator de escalonamento, permitindo a verificação de proporcionalidade entre os modelos e agrupando-os sob a mesma tendência. O modelo teórico exponencial foi o que melhor se ajustou aos semivariogramas experimentais, seguido pelo modelo esférico. Os parâmetros estimados para os modelos, efeito pepita, patamar e alcance foram utilizados para a realização da krigagem e confecção dos mapas de isolinhas. A distribuição espacial dos percentis 75 da precipitação decendial reflete o comportamento da circulação atmosférica no Estado, apresentando alta variabilidade. As regiões oeste , sudoeste e noroeste apresentaram as menores intensidades de precipitação e foram variáveis de acordo com os níveis temporais na primavera. A região litorânea apresentou as maiores intensidades de precipitação para quase todos os níveis temporais estudados, diferenciando-se das demais regiões do Estado. A exceção foi à região nordeste no final da primavera que apresentou valores de intensidades maiores do que os registrados no litoral. A faixa litorânea apresentou comportamento homogêneo, detectado pelo forte agrupamento das isolinhas em quase todos os decêndios analisados.

A Single Statistic for Monitoring the Covariance Matrix of Bivariate Processes

In this article, we present a new control chart for monitoring the covariance matrix in a bivariate process. In this method, n observations of the two variables were considered as if they came from a single variable (as a sample of 2n observations), and a sample variance was calculated. This statistic was used to build a new control chart specifically as a VMIX chart. The performance of the new control chart was compared with its main competitors: the generalized sampled variance chart, the likelihood ratio test, Nagao's test, probability integral transformation (v(t)), and the recently proposed VMAX chart. Among these statistics, only the VMAX chart was competitive with the VMIX chart. For shifts in both variances, the VMIX chart outperformed VMAX; however, VMAX showed better performance for large shifts (higher than 10%) in one variance.

Fertilización foliar con macronutrientes a plantas de naranja Valencia late (Citrus sinensis (L.) Osbeck) y tangor Murcott (Citrus reticulata Blanco x Citrus sinensis (L.) Osbeck)

El objetivo de este trabajo fue analizar el efecto de diferentes dosis de fertilizantes foliares con macronutrientes en plantas de naranja Valencia y de tangor Murcott. Los experimentos fueron realizados durante tres campañas consecutivas en Corrientes Argentina. El diseño experimental fue en bloques completos al azar con cuatro repeticiones y parcelas experimentales de cuatro plantas. Los tratamientos ensayados fueron T1 control; T2 N (12%) 2 L.ha-1; T3 N (12%) 4 L.ha-1; T4 N (9%) y P (2,6%) 2 L ha- 1; T5 N (9%) y P (2,6%) 4 L.ha-1; T6 N (9,3%), P (2,6%) y K (2,1%) 2 L.ha-1; T7 N (9,3%), P (2,6%) y K (2,1%) 4 L.ha-1, de fertilizante foliar formulados en base a sales de sulfato de amonio, fosfato monoamónico y nitrato de potasio según tratamiento. Los mismos fueron aplicados por campaña en prefloración, plena floración y en otoño. Se midieron las concentraciones foliares de N, P y K en hojas de otoño de ramas fructíferas y al momento de cosecha se determinó rendimiento total, diámetro de fruta, porcentaje de jugo, sólidos solubles, acidez y relación sólidos solubles/acidez. En Valencia late todos los tratamientos incrementaron el contenido de P foliar en comparación con el control. El tratamiento T7 incrementó un 38,7% el rendimiento respecto de T1, aunque los frutos presentaron menor diámetro. En "Murcott" todos los tratamientos incrementaron el rendimiento comparados con T1, y las máximas producciones se observaron en los tratamientos T7 (64,9% mayor) y T6 (43,8% mayor) además T7 incrementó el contenido de P foliar y disminuyó el contenido de sólidos solubles en comparación con el control. La fertilización foliar con macronutrientes incrementó la productividad en naranja Valencia late y tangor Murcott. Este trabajo muestra la utilidad de la fertilización foliar con macronutrientes como una herramienta complementaria en los programas de fertilización diseñados para optimizar el rendimiento.

Sample size and statistical power in the hierarchical analysis of variance: applications in morphometry of the nervous system.

Analysis of variance is commonly used in morphometry in order to ascertain differences in parameters between several populations. Failure to detect significant differences between populations (type II error) may be due to suboptimal sampling and lead to erroneous conclusions; the concept of statistical power allows one to avoid such failures by means of an adequate sampling. Several examples are given in the morphometry of the nervous system, showing the use of the power of a hierarchical analysis of variance test for the choice of appropriate sample and subsample sizes. In the first case chosen, neuronal densities in the human visual cortex, we find the number of observations to be of little effect. For dendritic spine densities in the visual cortex of mice and humans, the effect is somewhat larger. A substantial effect is shown in our last example, dendritic segmental lengths in monkey lateral geniculate nucleus. It is in the nature of the hierarchical model that sample size is always more important than subsample size. The relative weight to be attributed to subsample size thus depends on the relative magnitude of the between observations variance compared to the between individuals variance.

Variance components analyses of multiple asthma traits in a large sample of Australian families ascertained through a twin proband

Background: Intermediate phenotypes are often measured as a proxy for asthma. It is largely unclear to what extent the same set of environmental or genetic factors regulate these traits. Objective: Estimate the environmental and genetic correlations between self-reported and clinical asthma traits. Methods: A total of 3073 subjects from 802 families were ascertained through a twin proband. Traits measured included self-reported asthma, airway histamine responsiveness (AHR), skin prick response to common allergens including house dust mite (Dermatophagoides pteronyssinus [D. pter]), baseline lung function, total serum immunoglobulin E (IgE) and eosinophilia. Bivariate and multivariate analyses of eight traits were performed with adjustment for ascertainment and significant covariates. Results: Overall 2716 participants completed an asthma questionnaire and 2087 were clinically tested, including 1289 self-reported asthmatics (92% previously diagnosed by a doctor). Asthma, AHR, markers of allergic sensitization and eosinophilia had significant environmental correlations with each other (range: 0.23-0.89). Baseline forced expiratory volume in 1 s (FEV1) showed low environmental correlations with most traits. Fewer genetic correlations were significantly different from zero. Phenotypes with greatest genetic similarity were asthma and atopy (0.46), IgE and eosinophilia (0.44), AHR and D. pter (0.43) and AHR and airway obstruction (-0.43). Traits with greatest genetic dissimilarity were FEV1 and atopy (0.05), airway obstruction and IgE (0.07) and FEV1 and D. pter (0.11). Conclusion: These results suggest that the same set of environmental factors regulates the variation of many asthma traits. In addition, although most traits are regulated to great extent by specific genetic factors, there is still some degree of genetic overlap that could be exploited by multivariate linkage approaches.