457 resultados para quantile hedging
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The L-moments based index-flood procedure had been successfully applied for Regional Flood Frequency Analysis (RFFA) for the Island of Newfoundland in 2002 using data up to 1998. This thesis, however, considered both Labrador and the Island of Newfoundland using the L-Moments index-flood method with flood data up to 2013. For Labrador, the homogeneity test showed that Labrador can be treated as a single homogeneous region and the generalized extreme value (GEV) was found to be more robust than any other frequency distributions. The drainage area (DA) is the only significant variable for estimating the index-flood at ungauged sites in Labrador. In previous studies, the Island of Newfoundland has been considered as four homogeneous regions (A,B,C and D) as well as two Water Survey of Canada's Y and Z sub-regions. Homogeneous regions based on Y and Z was found to provide more accurate quantile estimates than those based on four homogeneous regions. Goodness-of-fit test results showed that the generalized extreme value (GEV) distribution is most suitable for the sub-regions; however, the three-parameter lognormal (LN3) gave a better performance in terms of robustness. The best fitting regional frequency distribution from 2002 has now been updated with the latest flood data, but quantile estimates with the new data were not very different from the previous study. Overall, in terms of quantile estimation, in both Labrador and the Island of Newfoundland, the index-flood procedure based on L-moments is highly recommended as it provided consistent and more accurate result than other techniques such as the regression on quantile technique that is currently used by the government.
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This thesis aimed to contribute to the discussion about the relationship between agricultural production structure, occupation and poverty in Brazil, specifically in the state of Minas Gerais, in 2010. The issue of employment is becoming increasingly challenging in the face of ongoing modernization process in agriculture, capital intensive and labor saver looking levels ever higher production and productivity. The productive inclusion can be an effective way to exit from poverty (the work is often the only asset of the poor). In this sense, we sought to investigate what activities or groups of activities occupied a larger number of people and generated higher yields and can potentially have contributed to a lower incidence of poverty. The basis for primary data was the 2010 Population Census (microdata). To achieve the objectives we used descriptive analysis, Pearson correlation coefficients and quantile regressions. Among the main findings highlight that agriculture occupied more and generated higher overall income than ranching presented more precarious, despite having lower average incomes and income percentile values, greater heterogeneity and instability, as well as higher proportions of poor. Overall, commodities showed greater formalization and lower poor proportions. In the case of agriculture, commodities activities occupied less, generated lower mass income and middle-income (although income percentiles slightly larger and more informality) and had lower poverty indicators than non-commodity (more heterogeneous rents). In livestock, commodities had higher percentages of occupation, income (although middle-income values and percentiles slightly smaller), and smaller proportions of poor than non-commodity (more heterogenous). In terms of occupation and income stood out the farming activities unspecified (non-commodity), the coffee growing and cattle (commodities). The cultivation of coffee and cattle had the lowest poverty indicators. agricultural production diversification indicators showed positive correlations with the occupation in activities not commodities (only), but also with the proportion of poor, indigent and concentration of income. In addition, the occupation in not commodities showed positive correlations with poverty indicators. It is noteworthy that the occupations in soybeans, coffee and fruit showed negative correlation coefficients with the indicators of poverty, indigence and gini. Finally, among the agricultural activities, there was to go to occupied in agricultural activities not commodities for commodity would be 'more equalizer' (decreasing coefficients over the distribution of income) than for cattle. The occupation in livestock (mostly non-commodity) would generate greater impact on the lower income deciles, but their coefficients grow back in the last deciles, which shows its most perverse character. Among the activities that would affect more strongly the lower deciles and less the higher deciles stand out pig farming, poultry, citrus cultivation, coffee and sugar cane. The cattle and the cultivation of soy, had the highest rates, but they grow back in the last deciles, which shows a more wicked character.
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Extremal quantile index is a concept that the quantile index will drift to zero (or one)
as the sample size increases. The three chapters of my dissertation consists of three
applications of this concept in three distinct econometric problems. In Chapter 2, I
use the concept of extremal quantile index to derive new asymptotic properties and
inference method for quantile treatment effect estimators when the quantile index
of interest is close to zero. In Chapter 3, I rely on the concept of extremal quantile
index to achieve identification at infinity of the sample selection models and propose
a new inference method. Last, in Chapter 4, I use the concept of extremal quantile
index to define an asymptotic trimming scheme which can be used to control the
convergence rate of the estimator of the intercept of binary response models.
Modelling the effectiveness of grass buffer strips in managing muddy floods under a changing climate
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Muddy floods occur when rainfall generates runoff on agricultural land, detaching and transporting sediment into the surrounding natural and built environment. In the Belgian Loess Belt, muddy floods occur regularly and lead to considerable economic costs associated with damage to property and infrastructure. Mitigation measures designed to manage the problem have been tested in a pilot area within Flanders and were found to be cost-effective within three years. This study assesses whether these mitigation measures will remain effective under a changing climate. To test this, the Water Erosion Prediction Project (WEPP) model was used to examine muddy flooding diagnostics (precipitation, runoff, soil loss and sediment yield) for a case study hillslope in Flanders where grass buffer strips are currently used as a mitigation measure. The model was run for present day conditions and then under 33 future site-specific climate scenarios. These future scenarios were generated from three earth system models driven by four representative concentration pathways and downscaled using quantile mapping and the weather generator CLIGEN. Results reveal that under the majority of future scenarios, muddy flooding diagnostics are projected to increase, mostly as a consequence of large scale precipitation events rather than mean changes. The magnitude of muddy flood events for a given return period is also generally projected to increase. These findings indicate that present day mitigation measures may have a reduced capacity to manage muddy flooding given the changes imposed by a warming climate with an enhanced hydrological cycle. Revisions to the design of existing mitigation measures within existing policy frameworks are considered the most effective way to account for the impacts of climate change in future mitigation planning.
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This study is a corpus-based comparison between student essays written in the subject areas of English linguistics and literature at undergraduate level. They are 200 Bachelor degree theses submitted at a variety of university departments (such as English, Language and Literature, Humanities, Social and Intercultural Studies) in Sweden. The comparison concerns frequencies of core modal verbs and how often they occur together with the I, we and it subject pronouns and in the structures this/the [essay, study, project, thesis] when students attempt to communicate their personal claims. Quantitative and qualitative analyses of the essays show few similarities in the ways that core modal verbs appear in both disciplines. The results indicate mainly distinct differences, especially in relation to clusters and variation of performative verbs. Specific patterns in the ways that students use core modal verbs as hedges have also been identified.
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Thesis (Ph.D.)--University of Washington, 2016-07
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Thesis (Ph.D.)--University of Washington, 2016-08
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There are a great number of evidences showing that education is extremely important in many economic and social dimensions. In Brazil, education is a right guaranteed by the Federal Constitution; however, in the Brazilian legislation the right to the three stages of basic education: Kindergarten, Elementary and High School is better promoted and supported than the right to education at College level. According to educational census data (INEP, 2009), 78% of all enrolments in College education are in private schools, while the reverse is found in High School: 84% of all matriculations are in public schools, which shows a contradiction in the admission into the universities. The Brazilian scenario presents that public universities receive mostly students who performed better and were prepared in elementary and high school education in private schools, while private universities attend students who received their basic education in public schools, which are characterized as low quality. These facts have led researchers to raise the possible determinants of student performance on standardized tests, such as the Brazilian Vestibular exam, to guide the development of policies aimed at equal access to College education. Seeking inspiration in North American models of affirmative action policies, some Brazilian public universities have suggested rate policies to enable and facilitate the entry of "minorities" (blacks, pardos1, natives, people of low income and public school students) to free College education. At the Federal University of the state Rio Grande do Norte (UFRN), the first incentives for candidates from public schools emerged in 2006, being improved and widespread during the last 7 years. This study aimed to analyse and discuss the Argument of Inclution (AI) - the affirmative action policy that provides additional scoring for students from public schools. From an extensive database, the Ordinary Least Squares (OLS) technique was used as well as a Quantile Regression considering as control the variables of personal, socioeconomic and educational characteristics of the candidates from the Brazilian Vestibular exam 2010 of the Federal University of the state Rio Grande do Norte (UFRN). The results demonstrate the importance of this incentive system, besides the magnitude of other variables
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This research aims to investigate the Hedge Efficiency and Optimal Hedge Ratio for the future market of cattle, coffee, ethanol, corn and soybean. This paper uses the Optimal Hedge Ratio and Hedge Effectiveness through multivariate GARCH models with error correction, attempting to the possible phenomenon of Optimal Hedge Ratio differential during the crop and intercrop period. The Optimal Hedge Ratio must be bigger in the intercrop period due to the uncertainty related to a possible supply shock (LAZZARINI, 2010). Among the future contracts studied in this research, the coffee, ethanol and soybean contracts were not object of this phenomenon investigation, yet. Furthermore, the corn and ethanol contracts were not object of researches which deal with Dynamic Hedging Strategy. This paper distinguishes itself for including the GARCH model with error correction, which it was never considered when the possible Optimal Hedge Ratio differential during the crop and intercrop period were investigated. The commodities quotation were used as future price in the market future of BM&FBOVESPA and as spot market, the CEPEA index, in the period from May 2010 to June 2013 to cattle, coffee, ethanol and corn, and to August 2012 to soybean, with daily frequency. Similar results were achieved for all the commodities. There is a long term relationship among the spot market and future market, bicausality and the spot market and future market of cattle, coffee, ethanol and corn, and unicausality of the future price of soybean on spot price. The Optimal Hedge Ratio was estimated from three different strategies: linear regression by MQO, BEKK-GARCH diagonal model, and BEKK-GARCH diagonal with intercrop dummy. The MQO regression model, pointed out the Hedge inefficiency, taking into consideration that the Optimal Hedge presented was too low. The second model represents the strategy of dynamic hedge, which collected time variations in the Optimal Hedge. The last Hedge strategy did not detect Optimal Hedge Ratio differential between the crop and intercrop period, therefore, unlikely what they expected, the investor do not need increase his/her investment in the future market during the intercrop
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Development of adequate diving capabilities is crucial for survival of seal pups and may depend on age and body size. We tracked the diving behavior of 20 gray seal pups during their first 3 mo at sea using satellite relay data loggers. We employed quantile analysis to track upper limits of dive duration and percentage time spent diving, and lower limits of surface intervals. When pups first left the breeding colony, extreme (ninety-fifth percentile) dive duration and percentage time spent diving were positively correlated with age, but not mass, at departure. Extreme dive durations and percentage time spent diving peaked at [Formula: see text] d of age at values comparable with those of adults, but were not sustained. Greater peaks in extreme percentage time spent diving occurred in pups that had higher initial values, were older at their peak, and were heavier at departure. Pups that were smaller and less capable divers when they left the colony improved extreme dive durations and percentage time spent diving more rapidly, once they were at sea. Minimum survival time correlated positively with departure mass. Pups that were heavier at weaning thus benefitted from being both larger and older at departure, but smaller pups faced a trade-off. While age at departure had a positive effect on early dive performance, departure mass impacted on peak percentage time spent diving and longer-term survival. We speculate that once small pups have attained a minimum degree of physiological development to support diving, they would benefit by leaving the colony when younger but larger to maximize limited fuel reserves, rather than undergoing further maturation on land away from potential food resources, because poor divers may be able to "catch up" once at sea.
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This dissertation contains four essays that all share a common purpose: developing new methodologies to exploit the potential of high-frequency data for the measurement, modeling and forecasting of financial assets volatility and correlations. The first two chapters provide useful tools for univariate applications while the last two chapters develop multivariate methodologies. In chapter 1, we introduce a new class of univariate volatility models named FloGARCH models. FloGARCH models provide a parsimonious joint model for low frequency returns and realized measures, and are sufficiently flexible to capture long memory as well as asymmetries related to leverage effects. We analyze the performances of the models in a realistic numerical study and on the basis of a data set composed of 65 equities. Using more than 10 years of high-frequency transactions, we document significant statistical gains related to the FloGARCH models in terms of in-sample fit, out-of-sample fit and forecasting accuracy compared to classical and Realized GARCH models. In chapter 2, using 12 years of high-frequency transactions for 55 U.S. stocks, we argue that combining low-frequency exogenous economic indicators with high-frequency financial data improves the ability of conditionally heteroskedastic models to forecast the volatility of returns, their full multi-step ahead conditional distribution and the multi-period Value-at-Risk. Using a refined version of the Realized LGARCH model allowing for time-varying intercept and implemented with realized kernels, we document that nominal corporate profits and term spreads have strong long-run predictive ability and generate accurate risk measures forecasts over long-horizon. The results are based on several loss functions and tests, including the Model Confidence Set. Chapter 3 is a joint work with David Veredas. We study the class of disentangled realized estimators for the integrated covariance matrix of Brownian semimartingales with finite activity jumps. These estimators separate correlations and volatilities. We analyze different combinations of quantile- and median-based realized volatilities, and four estimators of realized correlations with three synchronization schemes. Their finite sample properties are studied under four data generating processes, in presence, or not, of microstructure noise, and under synchronous and asynchronous trading. The main finding is that the pre-averaged version of disentangled estimators based on Gaussian ranks (for the correlations) and median deviations (for the volatilities) provide a precise, computationally efficient, and easy alternative to measure integrated covariances on the basis of noisy and asynchronous prices. Along these lines, a minimum variance portfolio application shows the superiority of this disentangled realized estimator in terms of numerous performance metrics. Chapter 4 is co-authored with Niels S. Hansen, Asger Lunde and Kasper V. Olesen, all affiliated with CREATES at Aarhus University. We propose to use the Realized Beta GARCH model to exploit the potential of high-frequency data in commodity markets. The model produces high quality forecasts of pairwise correlations between commodities which can be used to construct a composite covariance matrix. We evaluate the quality of this matrix in a portfolio context and compare it to models used in the industry. We demonstrate significant economic gains in a realistic setting including short selling constraints and transaction costs.
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Cette étude évalue l’impact des formations formelles sur le revenu et la durée du chômage des immigrants de la classe des travailleurs qualifiés résidant dans la province de Québec. En effet, elle cherche à vérifier l’adéquation entre les formations formelles et les caractéristiques observables de ces immigrants d’une part, puis l’adéquation entre ces formations et la situation économique des immigrants d’autre part. Après avoir effectué une analyse descriptive de la base de données, la méthode d’appariement multiple basée sur les scores de propension généralisés est utilisée pour estimer l’effet causal des formations formelles sur le revenu et la durée du chômage des immigrants. De plus, la méthode de régression par quantile est utilisée pour faire ressortir l’effet causal de ces formations par quantile. En moyenne, les résultats de l’étude montrent que les formations formelles diminuent la durée de chômage des participants, avec une baisse de 580 jours pour les participants aux formations linguistiques. Les effets quantiles des formations professionnelles et académiques sont plus élevés sur le 75è quantile des distributions de la durée du chômage, avec des baisses respectives de 491 et 495 jours. Cependant, les formations formelles n’augmentent pas le revenu des participants. C’est pourquoi le gouvernement du Québec doit bien clarifier ses objectifs d’immigration selon l’augmentation de l’employabilité d’une part ou selon l’augmentation du niveau salarial d’autre part. Pour une optimisation des ressources, il est recommandé au gouvernement d’orienter les immigrants vers les formations linguistiques car elles diminuent plus la durée du chômage et de chercher la meilleure politique qui permettrait de rattraper l’écart salarial entre les participants et les non-participants des formations.
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Mestrado em Fiscalidade