991 resultados para optimal hedge ratio


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The use of commodity, currency and stock index futures to hedge risky exposures in the underlying assets is well documented in financial literature. However single stock futures are a relatively new addition to the family of futures and as such, academic research on its use as a hedging tool is relatively thin. In this study we have explored the efficacy of two different methodological approaches that may be applied when hedging a long position in the underlying stock with a single stock future. We use daily trading data covering years 2002 to 2007 from the Indian market, where single stock futures have been really thriving in terms of volume of trade, to extract the optimal hedge ratios using both static OLS as well as 30-day, 60-day and 90-day moving least squares. The method of moving least squares has been in use by market practitioners for some time primarily as a trend analysis and charting tool. Our results indicate that the moving least squares approach outperforms the static OLS in terms of the hedging efficiency, which has been measured by the root mean square hedging error.

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There is widespread evidence that the volatility of stock returns displays an asymmetric response to good and bad news. This article considers the impact of asymmetry on time-varying hedges for financial futures. An asymmetric model that allows forecasts of cash and futures return volatility to respond differently to positive and negative return innovations gives superior in-sample hedging performance. However, the simpler symmetric model is not inferior in a hold-out sample. A method for evaluating the models in a modern risk-management framework is presented, highlighting the importance of allowing optimal hedge ratios to be both time-varying and asymmetric.

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As observações relatadas por Myers e Thompson, em seu artigo “Generalized Optimal Hedge Ratio Estimation” de 1989, foram analisadas neste estudo utilizando o boi gordo como a commodity de interesse. Myers e Thompson, demonstraram teórica e empiricamente, ser inapropriado o uso do coeficiente angular da regressão simples, dos preços à vista sobre os preços futuros como forma de estimar a razão ótima de hedge. Porém, sob condições especiais, a regressão simples com a mudança dos preços resultou em valores plausíveis, próximos àqueles determinados por um modelo geral. Este modelo geral, foi desenvolvido com o intuito de estabelecer os parâmetros para comparar as diferentes abordagens na estimativa da razão ótima de hedge. O coeficiente angular da reta da regressão simples e a razão ótima de hedge tem definições similares, pois ambos são o resultado da divisão entre a matriz de covariância dos preços, à vista e futuros e a variância dos preços futuros. No entanto, na razão ótima de hedge estes valores refletem o momento condicional, enquanto que na regressão simples são valores não condicionais. O problema portanto, está em poder estimar a matriz condicional de covariância, entre os preços à vista e futuros e a variância condicional dos preços futuros, com as informações relevantes no momento da tomada de decisão do hedge. Neste estudo utilizou-se o modelo de cointegração com o termo de correção de erros, para simular o modelo geral. O Indicador ESALQ/BM&F foi utilizado como a série representativa dos preços à vista, enquanto que para os preços futuros, foram utilizados os valores do ajuste diário dos contratos de boi gordo, referentes ao primeiro e quarto vencimentos, negociados na Bolsa Mercantil e de Futuros - BM&F. Os objetivos do presente estudo foram: investigar se as observações feitas por Myers e Thompson eram válidas para o caso do boi gordo brasileiro, observar o efeito do horizonte de hedge sobre a razão ótima de hedge e o efeito da utilização das séries diárias e das séries semanais sobre a estimativa da razão ótima de hedge. Trabalhos anteriores realizados com as séries históricas dos preços do boi gordo, consideraram apenas os contratos referentes ao primeiro vencimento. Ampliar o horizonte de hedge é importante, uma vez que as atividades realizadas pelos agentes tomam mais do que 30 dias. Exemplo disto é a atividade de engorda do boi, que pode levar até 120 dias entre a compra do boi magro e a venda do boi gordo. Demonstrou-se neste estudo, que o uso das séries semanais, é o mais apropriado, dado a diminuição substancial da autocorrelação serial. Demonstrou-se também, que as regressões com as mudanças dos preços, resultaram em estimativas da razão de hedge próximas daquelas obtidas com o modelo geral e que estas diminuem com o aumento do horizonte de hedge.

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Esta dissertação tem três objetivos. O primeiro é encontrar o melhor método para se calcular a taxa ótima de “hedge” no mercado brasileiro do boi gordo. Para isso, foram testados cinco modelos: BEKK, DCC de Tse e Tsui (2002), DCC de Engle e Sheppard (2001), BEKK com dummy de safra e BEKK com dummy de entressafra. O segundo é calcular o diferencial de razões de “hedge” entre a safra e entressafra, pois a taxa de “hedge” na entressafra deve ser maior devido a uma maior incerteza sobre um possível choque de oferta, o que afetaria negativamente os custos dos frigoríficos. O terceiro e último objetivo é desvendar o porquê da literatura brasileira de taxa ótima de “hedge” estar encontrando estimativas muito pequenas das taxas quando comparadas às realizadas no mercado. Conclui-se que os modelos DCC’s são os que, no geral, obtém um desempenho melhor pelo critério de redução de variância e aumento do índice de Sharpe e que a taxa de “hedge” na entressafra não deve ser maior que na safra. Nota-se também que a quebra da expectativa intertemporal com a mudança de contratos faz com que a variância da série dos retornos futuros aumente muito, diminuindo assim a taxa de “hedge”.

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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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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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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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This dissertation proposes a bivariate markov switching dynamic conditional correlation model for estimating the optimal hedge ratio between spot and futures contracts. It considers the cointegration between series and allows to capture the leverage efect in return equation. The model is applied using daily data of future and spot prices of Bovespa Index and R$/US$ exchange rate. The results in terms of variance reduction and utility show that the bivariate markov switching model outperforms the strategies based ordinary least squares and error correction models.

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Dissertação (mestrado)—Universidade de Brasília, Faculdade de Agronomia e Medicina Veterinária, Programa de Pós-Graduação em Agronegócios, 2016.

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This study proposes a utility-based framework for the determination of optimal hedge ratios (OHRs) that can allow for the impact of higher moments on hedging decisions. We examine the entire hyperbolic absolute risk aversion family of utilities which include quadratic, logarithmic, power, and exponential utility functions. We find that for both moderate and large spot (commodity) exposures, the performance of out-of-sample hedges constructed allowing for nonzero higher moments is better than the performance of the simpler OLS hedge ratio. The picture is, however, not uniform throughout our seven spot commodities as there is one instance (cotton) for which the modeling of higher moments decreases welfare out-of-sample relative to the simpler OLS. We support our empirical findings by a theoretical analysis of optimal hedging decisions and we uncover a novel link between OHRs and the minimax hedge ratio, that is the ratio which minimizes the largest loss of the hedged position. © 2011 Wiley Periodicals, Inc. Jrl Fut Mark

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Este trabalho tem como objetivo analisar os resultados de uma operação de hedge de um diversificado portfólio de crédito de empresas brasileiras através do uso de ativos de equity. Inicialmente, faz-se uma alusão aos principais aspectos teóricos da presente dissertação com suas definições e revisão bibliográfica. Posteriormente, são apresentados os parâmetros básicos da seleção da amostra utilizada e do período durante o qual tal estratégia de proteção será implementada.

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We characterize the optimal reserves, and the generated probability of a bank run, as a function of the penalty imposed by the central bank, the probability of depositors’ liquidity needs, and the return on outside investment opportunities.

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This paper investigates time-varying optimal hedge ratios in individual stock futures markets in India. The analysis employs data on individual stock futures from an unexplored but highly traded (both in terms of volume and quantity) emerging market. The hedge ratios derived in this study incorporate mean reversion in volatility, which is an important extension of the bivariate BEKK-GARCH model of Engle and Kroner. This extension generates improved optimal hedge ratios over the traditional BEKK-GARCH model and static error correction type alternatives.

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This paper investigates time-varying optimal hedge ratios in individual stock futures markets in India. The analysis employs data on individual stock futures from an unexplored but highly traded (both in terms of volume and quantity) emerging market. The hedge ratios derived in this study incorporate mean reversion in volatility, which is an important extension of the bivariate BEKK-GARCH model of Engle and Kroner. This extension generates improved optimal hedge ratios over the traditional BEKK-GARCH model and static error correction type alternatives.

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The article offers information about hedge funds, which refers to pooled investments that are privately organized and professionally managed by investment managers. It examines the statistical properties of the 70 Asian hedge funds and shows the inappropriateness of the traditional mean-variance optimizer to form optimal hedge fund portfolios. The article also introduces a practical heuristic approach using the senti-variance as a measure for downside risk, and describes the risk measures and the methodology to generate optimal hedge fund portfolio.