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O objetivo deste trabalho foi demonstrar a utilização da estatística como ferramenta para minimizar o risco em operações de hedge de boi gordo, tendo como base a série histórica de preços na cidade de Itapetinga no estado da Bahia. Os preços no mercado futuro foram obtidos junto ao Centro de Estudos Avançados em Economia Aplicada [CEPEA] Esalq/USP. Os preços do mercado físico foram levantados junto a Secretária da Agricultura, Pecuária, Irrigação, Pesca e Aquicultura [SEAGRI-BA]. Foi calculada a correlação entre os preços nos mercados físico e futuro com o objetivo de saber o quanto a variação de um acompanha a variação do outro. Foram calculadas as bases para todos os dias do período de tempo em análise, em seguida foram encontrados a média e o desvio padrão da base. Encontrado o risco de base das operações de hedge, tendo como referência a tabela da distribuição normal-padrão, foram simulados contratos de compra e venda diariamente no período de um ano, utilizando o conceito de custo de base para determinar o preço objetivo, aumentando a segurança nas operações. Sugeriu-se na prática encerrar algumas posições e assumir outras à medida que o mercado se movimenta a favor ou contra a posição do hedge. Desta forma, estratégias hedge em mercados futuros se mostram como excelentes opções para se precaver contra a variação de preços de boi gordo.

Made available in DSpace on 2020-12-10T17:02:24Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-12-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) The research aim was to evaluate the genotype-environment interactions (GxE) through a study of the reaction norms of Nellore cattle raised in the North and Northeast regions of Brazil at the age at first calving (AFC), with scrotal circumference at 365 and 450 days of age (SC365 and SC450), gestation length (GL) and accumulated productivity (ACP). Bayes hierarchical models with defined parameters at structured levels or stages were used. The Markov chain Monte Carlo method was used to obtain genetic parameter estimates. The environmental gradient of each trait was defined using a 99% credibility interval of the contemporary group's solutions. The animal model showed a better fit for AFC data, and the two-step reaction norms model was the best for the other characteristics. Heritabilities were 0.21 +/- 0.01 for AFC; and ranged from 0.27 +/- 0.04 to 0.58 +/- 0.02, 0.26 +/- 0.05 to 0.57 +/- 0.02, 81 +/- 0.03 to 0.03 +/- 0.02, 0.05 +/- 0.02 to 0.86 +/- 0.03 along the environmental gradient for SC365, SC450, GL and ACP, respectively. Correlations between intercept and slope of the reaction norms allied with reaction norms graphic plots of the ten sires with the greatest number of calves suggest the presence of GxE complex for SC365 and SC450, and thcE scale effect for GL and ACP. However, high correlations between the environments indicate that the GxE for SC450 and ACP is of a low magnitude and its inclusion in genetic evaluations would not influence the population selection. State Univ Southwest Bahia, Itapetinga, BA, Brazil State Univ Southwest Bahia, Dept Biol Sci, Jequie, BA, Brazil Fed Inst Amapa, Porto Grande, Amapa, Brazil Natl Assoc Breeders & Researchers, Ribeirao Preto, SP, Brazil Univ Fed Ceara, Juazeiro Do Norte, Ceara, Brazil Sao Paulo State Univ Unesp, Sch Agr & Vet Sci, Jaboticabal, SP, Brazil Sao Paulo State Univ Unesp, Sch Agr & Vet Sci, Jaboticabal, SP, Brazil CAPES: 001

The objective of this research is to estimate the genetic parameters and covariance components for growth characteristics in cattle from Tabapua breed through random regression models (RRM). The estimates of covariance functions are considered nowadays, interesting alternatives to work with longitudinal data that allow the description of covariances changes due to time and prediction of variances and covariances along the growth curve. The RRM has been used to estimate the variance components and genetic parameters of milk production on the control day of the lactation curve and meat production in many species, including bodyweight of beef cattle and among these the cattle from Tabapua breed, enabling us to work with features of growth curves that are measured repeatedly during the animal's life, known as longitudinal data. These models used in genetic evaluation in cattle are considered special cases of covariance functions that allow estimation of coefficients of genetic covariance functions directly through the method of restricted maximum likelihood.