990 resultados para Variance ratio profile


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Changes in urinary porphyrin excretion may be the result of hereditary causes and/or from environmental or occupational exposure. The objective of this study was to measure the amount of some porphyrins in spot urine samples obtained from volunteers randomly selected from a healthy adult population of São Paulo with a sensitive HPLC method and to estimate normal ranges for a non-exposed population. Spot urine samples were collected from 126 subjects (both genders, 18 to 65 years old) not occupationally exposed to porphyrinogenic agents. Porphyrin fractions were separated on RP-18 HPLC column eluted with a methanol/ammonium acetate buffer gradient, pH 4.0, and measured fluorometrically (excitation 405 nm/emission 620 nm). The amount of porphyrins was corrected for urinary creatinine excretion. Only 8-carboxyl (uro) and 4-carboxyl (copro) porphyrins were quantified as µg/g creatinine. Data regarding age, gender, occupational activities, smoking and drinking habits were analyzed by Mann-Whitney and Kruskal-Wallis tests. Uroporphyrin results did not differ significantly between the subgroups studied. Copro and uro + copro porphyrins were significantly different for smokers (P = 0.008) and occupational activities (P = 0.004). With respect to alcohol consumption, only men drinking >20 g/week showed significant differences in the levels of copro (P = 0.022) and uro + copro porphyrins (P = 0.012). The 2.5-97.5th percentile limit values, excluding those for subjects with an alcohol drinking habit >20 g/week, were 0-20.8, 11.7-93.1, and 15.9-102.9 µg/g creatinine for uro, copro and uro + copro porphyrins, respectively. These percentile limit values can be proposed as a first attempt to provide urinary porphyrin reference values for our population, serving for an early diagnosis of porphyrinopathies or as biomarkers of exposure to porphyrinogenic agents.

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Mestrado em Finanças

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In this study, we verify the existence of predictability in the Brazilian equity market. Unlike other studies in the same sense, which evaluate original series for each stock, we evaluate synthetic series created on the basis of linear models of stocks. Following Burgess (1999), we use the “stepwise regression” model for the formation of models of each stock. We then use the variance ratio profile together with a Monte Carlo simulation for the selection of models with potential predictability. Unlike Burgess (1999), we carry out White’s Reality Check (2000) in order to verify the existence of positive returns for the period outside the sample. We use the strategies proposed by Sullivan, Timmermann & White (1999) and Hsu & Kuan (2005) amounting to 26,410 simulated strategies. Finally, using the bootstrap methodology, with 1,000 simulations, we find strong evidence of predictability in the models, including transaction costs.

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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.

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The dyslipidemia and excess weight in adolescents, when combined, suggest a progression of risk factors for cardiovascular disease (CVD). Besides these, the dietary habits and lifestyle have also been considered unsuitable impacting the development of chronic diseases. The study objectives were: (1) estimate the prevalence of lipid profile and correlate with body mass index (BMI), waist circumference (WC) and waist / height ratio (WHR) in adolescents, considering the maturation sexual, (2) know the sources of variance in the diet and the number of days needed to estimate the usual diet of adolescents and (3) describe the dietary patterns and lifestyle of adolescents, family history of CVD and age correlates them with the patterns of risk for CVD, adjusted for sexual maturation. A cross-sectional study was performed with 432 adolescents, aged 10-19 years from public schools of the Natal city, Brazil. The dyslipidemias were evaluated considering the lipid profile, the index of I Castelli (TC / HDL) and II (LDL / HDL) and non-HDL cholesterol. Anthropometric indicators were BMI, WC and WHR. The intake of energy, nutrients including fiber, fatty acids and cholesterol was estimated from two 24-hour recalls (24HR). The variables of lipid profile, anthropometric and clinical data were used in the models of Pearson correlation and linear regression, considering the sexual maturation. The variance ratio of the diet was calculated from the component-person variance, determined by analysis of variance (ANOVA). The definition of the number of days to estimate the usual intake of each nutrient was obtained by taking the hypothetical correlation (r) ≥ 0.9, between nutrient intake and the true observed. We used the principal component analysis as a method of extracting factors that 129 accounted for the dependent variables and known cardiovascular risk obtained from the lipid profile, the index for Castelli I and II, non-HDL cholesterol, BMI, and WC the WHR. Dietary patterns and lifestyle were obtained from the independent variables, based on nutrients consumed and physical activity weekly. In the study of principal component analysis (PCA) was investigated associations between the patterns of cardiovascular risk factors in dietary patterns and lifestyle, age and positive family history of CVD, through bivariate and multiple logistic regression adjusted for sexual maturation. The low HDL-C dyslipidemia was most prevalent (50.5%) for adolescents. Significant correlations were observed between hypercholesterolemia and positive family history of CVD (r = 0.19, p <0.01) and hypertriglyceridemia with BMI (r = 0.30, p <0.01), with the CC (r = 0.32, p <0.01) and WHR (r = 0.33, p <0.01). The linear model constructed with sexual maturation, age and BMI explained about 1 to 10.4% of the variation in the lipid profile. The sources of variance between individuals were greater for all nutrients in both sexes. The reasons for variances were  1 for all nutrients were higher in females. The results suggest that to assess the diet of adolescents with greater precision, 2 days would be enough to R24h consumption of energy, carbohydrates, fiber, saturated and monounsaturated fatty acids. In contrast, 3 days would be recommended for protein, lipid, polyunsaturated fatty acids and cholesterol. Two cardiovascular risk factors as have been extracted in the ACP, referring to the dependent variables: the standard lipid profile (HDL-C and non-HDL cholesterol) and "standard anthropometric index (BMI, WC, WHR) with a power explaining 75% of the variance of the original data. The factors are representative of two independent variables led to dietary patterns, "pattern 130 western diet" and "pattern protein diet", and one on the lifestyle, "pattern energy balance". Together, these patterns provide an explanation power of 67%. Made adjustment for sexual maturation in males remained significant variables: the associations between puberty and be pattern anthropometric indicator (OR = 3.32, CI 1.34 to 8.17%), and between family history of CVD and the pattern lipid profile (OR = 2.62, CI 1.20 to 5.72%). In females adolescents, associations were identified between age after the first stage of puberty with anthropometric pattern (OR = 3.59, CI 1.58 to 8.17%) and lipid profile (OR = 0.33, CI 0.15 to 0.75%). Conclusions: The low HDL-C was the most prevalent dyslipidemia independent of sex and nutritional status of adolescents. Hypercholesterolemia was influenced by family history of CVD and sexual maturation, in turn, hypertriglyceridemia was closely associated with anthropometric indicators. The variance between the diets was greater for all nutrients. This fact reflected in a variance ratio less than 1 and consequently in a lower number of days requerid to estimate the usual diet of adolescents considering gender. The two dietary patterns were extracted and the pattern considered unhealthy lifestyle as healthy. The associations were found between the patterns of CVD risk with age and family history of CVD in the studied adolescents

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The aim of the current study was to describe the sources of variation of energy and nutrient intake and to calculate the number of repetitions of diet measurements to estimate usual intake in adolescents from São Paulo, Brazil. Data was collected using 24-hour dietary recalls (24hR) in 273 adolescents between 2007 and 2008. Individuals completed a repeat 24hR around two months later. The sources of variation were estimated using the random effect model. Variance ratios (within-person to between-person variance ratio) and the number of repetitions of 24hR to estimate usual intake were calculated. The principal source of variation was due to within-person variance. The contribution of day of week and month of year was less than 8%. Variations ranged from 1.15 for calcium to 7.31 for vitamin E. The number of 24hR repeats required to estimate usual intake varied according to nutrient and gender, numbering 15 for males and 8 for females.

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Este estudo propôs-se a descrever as fontes de variação da ingestão de energia e nutrientes e calcular o número de dias necessários para a estimativa da ingestão habitual em adolescentes do Município de São Paulo, Brasil. Foi aplicado um recordatório alimentar de 24 horas (R24h) em 273 adolescentes, durante os anos de 2007 e 2008, e posteriormente cada indivíduo foi convidado a responder a outro R24h. Foram estimadas as fontes de variação da ingestão utilizando-se modelo de efeitos aleatórios. A variância intrapessoal foi o componente de variância que mais contribuiu para a variabilidade da ingestão de energia e nutrientes, ao passo que a contribuição do dia da semana e mês do ano foi pequena (< 8por cento ) para a variabilidade total da ingestão. As razões de variância variaram de 1,15 para o cálcio a 7,31 para a vitamina E. O número de R24h necessário para estimar a ingestão habitual variou de acordo com o nutriente: em torno de 15 para o sexo masculino e 8 para o feminino

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The restricted maximum likelihood is preferred by many to the full maximumlikelihood for estimation with variance component and other randomcoefficientmodels, because the variance estimator is unbiased. It is shown that thisunbiasednessis accompanied in some balanced designs by an inflation of the meansquared error.An estimator of the cluster-level variance that is uniformly moreefficient than the fullmaximum likelihood is derived. Estimators of the variance ratio are alsostudied.

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Tämän tutkielman tavoitteena on tarkastella Kiinan osakemarkkinoiden tehokkuutta ja random walk -hypoteesin voimassaoloa. Tavoitteena on myös selvittää esiintyykö viikonpäiväanomalia Kiinan osakemarkkinoilla. Tutkimusaineistona käytetään Shanghain osakepörssin A-sarjan,B-sarjan ja yhdistelmä-sarjan ja Shenzhenin yhdistelmä-sarjan indeksien päivittäisiä logaritmisoituja tuottoja ajalta 21.2.1992-30.12.2005 sekä Shenzhenin osakepörssin A-sarjan ja B-sarjan indeksien päivittäisiä logaritmisoituja tuottoja ajalta 5.10.1992-30.12.2005. Tutkimusmenetelminä käytetään neljä tilastollista menetelmää, mukaan lukien autokorrelaatiotestiä, epäparametrista runs-testiä, varianssisuhdetestiä sekä Augmented Dickey-Fullerin yksikköjuuritestiä. Viikonpäiväanomalian esiintymistä tutkitaan käyttämällä pienimmän neliösumman menetelmää (OLS). Testejä tehdään sekä koko aineistolla että kolmella erillisellä ajanjaksolla. Tämän tutkielman empiiriset tulokset tukevat aikaisempia tutkimuksia Kiinan osakemarkkinoiden tehottomuudesta. Lukuun ottamatta yksikköjuuritestien saatuja tuloksia, autokorrelaatio-, runs- ja varianssisuhdetestien perusteella random walk-hypoteesi hylättiin molempien Kiinan osakemarkkinoiden kohdalla. Tutkimustulokset osoittavat, että molemmilla osakepörssillä B-sarjan indeksien käyttäytyminenon ollut huomattavasti enemmän random walk -hypoteesin vastainen kuin A-sarjan indeksit. Paitsi B-sarjan markkinat, molempien Kiinan osakemarkkinoiden tehokkuus näytti myös paranevan vuoden 2001 markkinabuumin jälkeen. Tutkimustulokset osoittavat myös viikonpäiväanomalian esiintyvän Shanghain osakepörssillä, muttei kuitenkaan Shenzhenin osakepörssillä koko tarkasteluajanjaksolla.

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The thesis examines the performance persistence of hedge funds using complement methodologies (namely cross-sectional regressions, quantile portfolio analysis and Spearman rank correlation test). In addition, six performance ranking metrics and six different combinations of selection and holding periods are compared. The data is gathered from HFI and Tremont databases covering over 14,000 hedge funds and time horizon is set from January 1996 to December 2007. The results suggest that there definitely exists performance persistence among hedge funds and the strength and existence of persistence vary among fund styles. The persistence depends on the metrics and combination of selection and prediction period applied. According to the results, the combination of 36-month selection and holding period outperforms other five period combinations in capturing performance persistence within the sample. Furthermore, model-free performance metrics capture persistence more sensitively than model-specific metrics. The study is the first one ever to use MVR as a performance ranking metric, and surprisingly MVR is more sensitive to detect persistence than other performance metrics employed.

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This study examines performance persistence of hedge funds from investor's point of view and look at the methods by which an investor could choose the successful hedge funds to the portfolio. This study was used the data from HFI & Tremont databases on period 1998-2007. In this study used the 36-month combination (24-month selection and 12-month prediction periods). As the research methods used the Sharpe index, raw returns, MVR (mean variance ratio), GSC-clustering, the SDI index and the new combination of metrics. The evaluation criterions of the results used the volatility, excess returns and the Sharpe index. This study compared different results from the 7 time series with each other, and commenting the problems on a portfolio loss of funds.

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The purpose of the thesis is to examine the long-term performance persistence and relative performance of hedge funds during bear and bull market periods. Performance metrics applied for fund rankings are raw return, Sharpe ratio, mean variance ratio and strategy distinctiveness index calculated of the original and clustered data correspondingly. Four different length combinations for selection and holding periods are employed. The persistence is examined using decile and quartile portfolio formatting approach and on the basis of Sharpe ratio and SKASR as performance metrics. The relative performance persistence is examined by comparing hedge portfolio returns during varying stock market conditions. The data is gathered from a private database covering 10,789 hedge funds and time horizon is set from January 1990 to December 2012. The results of this thesis suggest that long-term performance persistence of the hedge funds exists. The degree of persistence also depends on the performance metrics employed and length combination of selection and holding periods. The best results of performance persistence were obtained in the decile portfolio analysis on the basis of Sharpe ratio rankings for combination of 12-month selection period and the holding period of equal length. The results also suggest that the best performance persistence occurs in the Event Driven and Multi strategies. Dummy regression analysis shows that a relationship between hedge funds and stock market returns exists. Based on the results, Dedicated Short Bias, Global Macro, Managed Futures and Other strategies perform well during bear market periods. The results also indicate that the Market Neutral strategy is not absolutely market neutral and the Event Driven strategy has the best performance among all hedge strategies.

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Margin policy is used by regulators for the purpose of inhibiting exceSSIve volatility and stabilizing the stock market in the long run. The effect of this policy on the stock market is widely tested empirically. However, most prior studies are limited in the sense that they investigate the margin requirement for the overall stock market rather than for individual stocks, and the time periods examined are confined to the pre-1974 period as no change in the margin requirement occurred post-1974 in the U.S. This thesis intends to address the above limitations by providing a direct examination of the effect of margin requirement on return, volume, and volatility of individual companies and by using more recent data in the Canadian stock market. Using the methodologies of variance ratio test and event study with conditional volatility (EGARCH) model, we find no convincing evidence that change in margin requirement affects subsequent stock return volatility. We also find similar results for returns and trading volume. These empirical findings lead us to conclude that the use of margin policy by regulators fails to achieve the goal of inhibiting speculating activities and stabilizing volatility.

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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.

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The estimation of the long-term wind resource at a prospective site based on a relatively short on-site measurement campaign is an indispensable task in the development of a commercial wind farm. The typical industry approach is based on the measure-correlate-predict �MCP� method where a relational model between the site wind velocity data and the data obtained from a suitable reference site is built from concurrent records. In a subsequent step, a long-term prediction for the prospective site is obtained from a combination of the relational model and the historic reference data. In the present paper, a systematic study is presented where three new MCP models, together with two published reference models �a simple linear regression and the variance ratio method�, have been evaluated based on concurrent synthetic wind speed time series for two sites, simulating the prospective and the reference site. The synthetic method has the advantage of generating time series with the desired statistical properties, including Weibull scale and shape factors, required to evaluate the five methods under all plausible conditions. In this work, first a systematic discussion of the statistical fundamentals behind MCP methods is provided and three new models, one based on a nonlinear regression and two �termed kernel methods� derived from the use of conditional probability density functions, are proposed. All models are evaluated by using five metrics under a wide range of values of the correlation coefficient, the Weibull scale, and the Weibull shape factor. Only one of all models, a kernel method based on bivariate Weibull probability functions, is capable of accurately predicting all performance metrics studied.