974 resultados para mean-variance efficiency
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ABSTRACTAiming to compare three different methods for the determination of organic carbon (OC) in the soil and fractions of humic substances, seventeen Brazilian soil samples of different classes and textures were evaluated. Amounts of OC in the soil samples and the humic fractions were measured by the dichromate-oxidation method, with and without external heating in a digestion block at 130 °C for 30 min; by the loss-on-ignition method at 450 °C during 5 h and at 600 °C during 6 h; and by the dry combustion method. Dry combustion was used as reference in order to measure the efficiency of the other methods. Soil OC measured by the dichromate-oxidation method with external heating had the highest efficiency and the best results comparing to the reference method. When external heating was not used, the mean recovery efficiency dropped to 71%. The amount of OC was overestimated by the loss-on-ignition methods. Regression equations obtained between total OC contents of the reference method and those of the other methods showed relatively good adjustment, but all intercepts were different from zero (p < 0.01), which suggests that more accuracy can be obtained using not one single correction factor, but considering also the intercept. The Walkley-Black method underestimated the OC contents of the humic fractions, which was associated with the partial oxidation of the humin fraction. Better results were obtained when external heating was used. For the organic matter fractions, the OC in the humic and fulvic acid fractions can be determined without external heating if the reference method is not available, but the humin fraction requires the external heating.
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The scope of this paper is to adapt the standard mean-variance model of Henry Markowitz theory, creating a simulation tool to find the optimal configuration of the portfolio aggregator, calculate its profitability and risk. Currently, there is a deep discussion going on among the power system society about the structure and architecture of the future electric system. In this environment, policy makers and electric utilities find new approaches to access the electricity market; this configures new challenging positions in order to find innovative strategies and methodologies. Decentralized power generation is gaining relevance in liberalized markets, and small and medium size electricity consumers are also become producers (“prosumers”). In this scenario an electric aggregator is an entity that joins a group of electric clients, customers, producers, “prosumers” together as a single purchasing unit to negotiate the purchase and sale of electricity. The aggregator conducts research on electricity prices, contract terms and conditions in order to promote better energy prices for their clients and allows small and medium customers to benefit improved market prices.
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Many texture measures have been developed and used for improving land-cover classification accuracy, but rarely has research examined the role of textures in improving the performance of aboveground biomass estimations. The relationship between texture and biomass is poorly understood. This paper used Landsat Thematic Mapper (TM) data to explore relationships between TM image textures and aboveground biomass in Rondônia, Brazilian Amazon. Eight grey level co-occurrence matrix (GLCM) based texture measures (i.e., mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation), associated with seven different window sizes (5x5, 7x7, 9x9, 11x11, 15x15, 19x19, and 25x25), and five TM bands (TM 2, 3, 4, 5, and 7) were analyzed. Pearson's correlation coefficient was used to analyze texture and biomass relationships. This research indicates that most textures are weakly correlated with successional vegetation biomass, but some textures are significantly correlated with mature forest biomass. In contrast, TM spectral signatures are significantly correlated with successional vegetation biomass, but weakly correlated with mature forest biomass. Our findings imply that textures may be critical in improving mature forest biomass estimation, but relatively less important for successional vegetation biomass estimation.
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Standalone levelised cost assessments of electricity supply options miss an important contribution that renewable and non-fossil fuel technologies can make to the electricity portfolio: that of reducing the variability of electricity costs, and their potentially damaging impact upon economic activity. Portfolio theory applications to the electricity generation mix have shown that renewable technologies, their costs being largely uncorrelated with non-renewable technologies, can offer such benefits. We look at the existing Scottish generation mix and examine drivers of changes out to 2020. We assess recent scenarios for the Scottish generation mix in 2020 against mean-variance efficient portfolios of electricity-generating technologies. Each of the scenarios studied implies a portfolio cost of electricity that is between 22% and 38% higher than the portfolio cost of electricity in 2007. These scenarios prove to be “inefficient” in the sense that, for example, lower variance portfolios can be obtained without increasing portfolio costs, typically by expanding the share of renewables. As part of extensive sensitivity analysis, we find that Wave and Tidal technologies can contribute to lower risk electricity portfolios, while not increasing portfolio cost.
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The framework presents how trading in the foreign commodity futures market and the forward exchange market can affect the optimal spot positions of domestic commodity producers and traders. It generalizes the models of Kawai and Zilcha (1986) and Kofman and Viaene (1991) to allow both intermediate and final commodities to be traded in the international and futures markets, and the exporters/importers to face production shock, domestic factor costs and a random price. Applying mean-variance expected utility, we find that a rise in the expected exchange rate can raise both supply and demand for commodities and reduce domestic prices if the exchange rate elasticity of supply is greater than that of demand. Whether higher volatilities of exchange rate and foreign futures price can reduce the optimal spot position of domestic traders depends on the correlation between the exchange rate and the foreign futures price. Even though the forward exchange market is unbiased, and there is no correlation between commodity prices and exchange rates, the exchange rate can still affect domestic trading and prices through offshore hedging and international trade if the traders are interested in their profit in domestic currency. It illustrates how the world prices and foreign futures prices of commodities and their volatility can be transmitted to the domestic market as well as the dynamic relationship between intermediate and final goods prices. The equilibrium prices depends on trader behaviour i.e. who trades or does not trade in the foreign commodity futures and domestic forward currency markets. The empirical result applying a two-stage-least-squares approach to Thai rice and rubber prices supports the theoretical result.
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Cette thèse s'intéresse à étudier les propriétés extrémales de certains modèles de risque d'intérêt dans diverses applications de l'assurance, de la finance et des statistiques. Cette thèse se développe selon deux axes principaux, à savoir: Dans la première partie, nous nous concentrons sur deux modèles de risques univariés, c'est-à- dire, un modèle de risque de déflation et un modèle de risque de réassurance. Nous étudions le développement des queues de distribution sous certaines conditions des risques commun¬s. Les principaux résultats sont ainsi illustrés par des exemples typiques et des simulations numériques. Enfin, les résultats sont appliqués aux domaines des assurances, par exemple, les approximations de Value-at-Risk, d'espérance conditionnelle unilatérale etc. La deuxième partie de cette thèse est consacrée à trois modèles à deux variables: Le premier modèle concerne la censure à deux variables des événements extrême. Pour ce modèle, nous proposons tout d'abord une classe d'estimateurs pour les coefficients de dépendance et la probabilité des queues de distributions. Ces estimateurs sont flexibles en raison d'un paramètre de réglage. Leurs distributions asymptotiques sont obtenues sous certaines condi¬tions lentes bivariées de second ordre. Ensuite, nous donnons quelques exemples et présentons une petite étude de simulations de Monte Carlo, suivie par une application sur un ensemble de données réelles d'assurance. L'objectif de notre deuxième modèle de risque à deux variables est l'étude de coefficients de dépendance des queues de distributions obliques et asymétriques à deux variables. Ces distri¬butions obliques et asymétriques sont largement utiles dans les applications statistiques. Elles sont générées principalement par le mélange moyenne-variance de lois normales et le mélange de lois normales asymétriques d'échelles, qui distinguent la structure de dépendance de queue comme indiqué par nos principaux résultats. Le troisième modèle de risque à deux variables concerne le rapprochement des maxima de séries triangulaires elliptiques obliques. Les résultats théoriques sont fondés sur certaines hypothèses concernant le périmètre aléatoire sous-jacent des queues de distributions. -- This thesis aims to investigate the extremal properties of certain risk models of interest in vari¬ous applications from insurance, finance and statistics. This thesis develops along two principal lines, namely: In the first part, we focus on two univariate risk models, i.e., deflated risk and reinsurance risk models. Therein we investigate their tail expansions under certain tail conditions of the common risks. Our main results are illustrated by some typical examples and numerical simu¬lations as well. Finally, the findings are formulated into some applications in insurance fields, for instance, the approximations of Value-at-Risk, conditional tail expectations etc. The second part of this thesis is devoted to the following three bivariate models: The first model is concerned with bivariate censoring of extreme events. For this model, we first propose a class of estimators for both tail dependence coefficient and tail probability. These estimators are flexible due to a tuning parameter and their asymptotic distributions are obtained under some second order bivariate slowly varying conditions of the model. Then, we give some examples and present a small Monte Carlo simulation study followed by an application on a real-data set from insurance. The objective of our second bivariate risk model is the investigation of tail dependence coefficient of bivariate skew slash distributions. Such skew slash distributions are extensively useful in statistical applications and they are generated mainly by normal mean-variance mixture and scaled skew-normal mixture, which distinguish the tail dependence structure as shown by our principle results. The third bivariate risk model is concerned with the approximation of the component-wise maxima of skew elliptical triangular arrays. The theoretical results are based on certain tail assumptions on the underlying random radius.
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Aims To investigate whether the predominant finding of generalized positive associations between self-rated motives for drinking alcohol and negative consequences of drinking alcohol are influenced by (i) using raw scores of motives that may weight inter-individual response behaviours too strongly, and (ii) predictor-criterion contamination by using consequence items where respondents attribute alcohol use as the cause. Design Cross-sectional study within the European School Survey Project on Alcohol and other Drugs (ESPAD). Setting School classes. Participants Students, aged 13-16 (n = 5633). Measurements Raw, rank and mean-variance standardized scores of the Drinking Motives Questionnaire-Revised (DMQ-R); four consequences: serious problems with friends, sexual intercourse regretted the next day, physical fights and troubles with the police, each itemized with attribution ('because of your alcohol use') and without. Findings As found previously in the literature, raw scores for all drinking motives had positive associations with negative consequences of drinking, while transformed (rank or Z) scores showed a more specific pattern: external reinforcing motives (social, conformity) had negative and internal reinforcing motives (enhancement, coping) had non-significant or positive associations with negative consequences. Attributed consequences showed stronger associations with motives than non-attributed ones. Conclusion Standard scoring of the Drinking Motives Questionnaire (Revised) fails to capture motives in a way that permits specific associations with different negative consequences to be identified, whereas use of rank or Z-scores does permit this. Use of attributed consequences overestimates the association with drinking motives.
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This paper shows how to introduce liquidity into the well known mean-variance framework of portfolio selection. Either by estimating mean-variance liquidity constrained frontiers or directly estimating optimal portfolios for alternative levels of risk aversion and preference for liquidity, we obtain strong effects of liquidity on optimal portfolio selection. In particular, portfolio performance, measured by the Sharpe ratio relative to the tangency portfolio, varies significantly with liquidity. Moreover, although mean-variance performance becomes clearly worse, the levels of liquidity onoptimal portfolios obtained when there is a positive preference for liquidity are much lower than on those optimal portfolios where investors show no sign of preference for liquidity.
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This paper aims to estimate a translog stochastic frontier production function in the analysis of a panel of 150 mixed Catalan farms in the period 1989-1993, in order to attempt to measure and explain variation in technical inefficiency scores with a one-stage approach. The model uses gross value added as the output aggregate measure. Total employment, fixed capital, current assets, specific costs and overhead costs are introduced into the model as inputs. Stochasticfrontier estimates are compared with those obtained using a linear programming method using a two-stage approach. The specification of the translog stochastic frontier model appears as an appropriate representation of the data, technical change was rejected and the technical inefficiency effects were statistically significant. The mean technical efficiency in the period analyzed was estimated to be 64.0%. Farm inefficiency levels were found significantly at 5%level and positively correlated with the number of economic size units.
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This paper surveys asset allocation methods that extend the traditional approach. An important feature of the the traditional approach is that measures the risk and return tradeoff in terms of mean and variance of final wealth. However, there are also other important features that are not always made explicit in terms of investor s wealth, information, and horizon: The investor makes a single portfolio choice based only on the mean and variance of her final financial wealth and she knows the relevant parameters in that computation. First, the paper describes traditional portfolio choice based on four basic assumptions, while the rest of the sections extend those assumptions. Each section will describe the corresponding equilibrium implications in terms of portfolio advice and asset pricing.
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The objective of this work was to assess the effect of six rootstocks on yield, fruit quality, and growth of 'Oneco' mandarin during the first seven harvesting seasons, in Butiá, Rio Grande do Sul State, Brazil. The rootstocks evaluated were: 'Swingle' citrumelo (Citrus paradisi × Poncirus trifoliata), 'Caipira' orange (C. sinensis), 'Troyer' citrange (C. sinensis × P. trifoliata), 'Rangpur' lime (C. limonia), 'Volkamer' lemon (C. volkameriana), and 'Flying Dragon' trifoliata orange (P. trifoliata var. monstrosa). Plants budded onto 'Flying Dragon' had the lowest vegetative development, which indicates the dwarfing characteristics of this rootstock, and had the highest mean production efficiency, despite low yield. Plants grafted on 'Volkamer' lemon and 'Rangpur' lime had the highest alternate bearing. Under the experimental conditions evaluated, the most adequate rootstocks for mandarin 'Oneco' are 'Swingle' citrumelo and 'Troyer' citrange, regarding fruit yield and quality.
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In this study it was evaluated the start-up procedures of anaerobic treatment system with three horizontal anaerobic reactors (R1, R2 and R3), installed in series, with volume of 1.2 L each. R1 had sludge blanket, and R2 and R3 had half supporter of bamboo and coconut fiber, respectively. As an affluent, it was synthesized wastewater from mechanical pulping of the coffee fruit by wet method, with a mean value of total chemical oxygen demand (CODtotal) of 16,003 mg L-1. The hydraulic retention time (HRT) in each reactor was 30 h. The volumetric organic loading (VOL) applied in R1 varied from 8.9 to 25.0 g of CODtotal (L d)-1. The mean removal efficiencies of CODtotal varied from 43 to 97% in the treatment system (R1+R2+R3), stabilizing above 80% after 30 days of operation. The mean content of methane in the biogas were of 70 to 76%, the mean volumetric production was 1.7 L CH4 (L reactor d)-1 in the system, and the higher conversions were around at 0.20 L CH4 (g CODremoved)-1 in R1 and R2. The mean values of pH in the effluents ranged from 6.8 to 8.3 and the mean values of total volatile acids remained below 200 mg L-1 in the effluent of R3. The concentrations of total phenols of the affluent ranged from 45 to 278 mg L-1, and the mean removal efficiency was of 52%. The start-up of the anaerobic treatment system occurred after 30 days of operation as a result of inoculation with anaerobic sludge with active microbiota.
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The Bartlett-Lewis Rectangular Pulse Modified (BLPRM) model simulates the precipitous slide in the hourly and sub-hourly and has six parameters for each of the twelve months of the year. This study aimed to evaluate the behavior of precipitation series in the duration of 15 min, obtained by simulation using the model BLPRM in situations: (a) where the parameters are estimated from a combination of statistics, creating five different sets; (b) suitability of the model to generate rain. To adjust the parameters were used rain gauge records of Pelotas/RS/Brazil, which statistics were estimated - mean, variance, covariance, autocorrelation coefficient of lag 1, the proportion of dry days in the period considered. The results showed that the parameters related to the time of onset of precipitation (λ) and intensities (μx) were the most stable and the most unstable were ν parameter, related to rain duration. The BLPRM model adequately represented the mean, variance, and proportion of the dry period of the series of precipitation lasting 15 min and, the time dependence of the heights of rain, represented autocorrelation coefficient of the first retardation was statistically less simulated series suitability for the duration of 15 min.
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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.