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Máková, Barbora. "Hedge Ratio Estimation in Inventory Management." Master's thesis, Vysoká škola ekonomická v Praze, 2013. http://www.nusl.cz/ntk/nusl-198395.
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Companies dependent on commodities for their production have to deal with volatile commodity prices and should employ measures for risk reduction as unfavourable spot price development may cause significant losses. A useful tool for diminishing the risk is hedging on futures market; however, this approach faces a crucial question of optimal hedge ratio determination (ratio between spot and futures units). Our thesis examines nine different ways of optimal hedge ratio estimation (naive, Sharpe, mean extended Gini coefficient, generalized semivariance, value at risk, and minimum variance through OLS, error correction, GARCH, and bivariate GARCH models) and evaluates their efficiency using the data on eight different commodities. The results differ across the respective commodities and cannot be generalized. Two conclusions resulting from the analysis refer to performance of naive and OLS hedge ratios and constant vs time varying hedge ratios. We find that complex hedge ratios, such as bivariate GARCH or VaR hedge ratios, do not outperform naive and OLS hedge ratios and that the results of constant hedge ratios are mostly as good as results of time-varying hedge ratios.
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Turner, Peter Alistair. "Determining the Optimal Commodity and Hedge Ratio for Cross-Hedging Jet Fuel." Thesis, North Dakota State University, 2014. https://hdl.handle.net/10365/27250.
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Airlines are exposed to risks in swings in the price of jet fuel. While there are many different options that they can use to hedge this risk, airlines often underutilize them. This study establishes the minimum variance hedge ratio for an airline wishing to hedge with futures, while also establishing the best cross-hedging asset. Airlines hedging with futures would create the most effective hedge by using 3-month maturity contracts of heating oil. 3- Month maturity contracts are slightly more effective as hedging tools than the next month, but beyond the 3-Month veil, increased maturity makes heating oil less effective as a cross hedging tool.Upper Great Plains Transportation Institute (UGPTI)
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Haglund, Fredrik, and Svensson Johan. "The volatility race in Commodities : The optimal hedge ratio in Copper, Gold, Oil and Cotton." Thesis, Jönköping University, JIBS, Business Administration, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-88.
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Introduction: Companies that are dependent on different commodities as input or output are exposed to price risk in these commodities. The price changes can be expressed as volatility and higher volatility results in higher risk. Hedging the commodity contracts with futures can offset this risk. One of the most important questions in this field is to what extent the risk exposure should be hedged with futures contract, i.e. the optimal hedge ratio.
Purpose: The study aims to conduct an analysis of the variance in different commodities contracts and provide evidence of the optimal hedge ratio in the respective commodities.
Method: We used a quantitative study with daily spot and futures price changes of Copper, Gold, Cotton and Oil. We investigated the 6-month hedging behaviour where timeseries were created for the period January-June each year during 2001-2004. We used a simple linear regression of the futures and spot price changes and a minimum variance model in order to calculate the optimal hedge ratio.
Conclusion: Companies that are dependent on Copper, Gold, Cotton and Oil can significantly reduce the risk by engaging in futures contracts. The optimal hedge ratio for Copper is (96%), Gold (52%), Cotton (96%) and Oil (88%). By applying the optimal hedge ratio, a company may reduce their risk exposure up to 90% compared to an unhedged position.
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Xu, Weijun Banking & Finance Australian School of Business UNSW. "Optimal hedging strategy in stock index future markets." Awarded by:University of New South Wales. Banking & Finance, 2009. http://handle.unsw.edu.au/1959.4/43728.
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In this thesis we search for optimal hedging strategy in stock index futures markets by providing a comprehensive comparison of variety types of models in the related literature. We concentrate on the strategy that minimizes portfolio risk, i.e., minimum variance hedge ratio (MVHR) estimated from a range of time series models with different assumptions of market volatility. There are linear regression models assuming time-invariant volatility; GARCH-type models capturing time-varying volatility, Markov regime switching (MRS) regression models assuming state-varying volatility, and MRS-GARCH models capturing both time-varying and state-varying volatility. We use both Maximum Likelihood Estimation (MLE) and Bayesian Gibbs-Sampling approach to estimate the models with four commonly used index futures contracts: S&P 500, FTSE 100, Nikkei 225 and Hang Seng index futures. We apply risk reduction and utility maximization criterions to evaluate hedging performance of MVHRs estimated from these models. The in-sample results show that the optimal hedging strategy for the S&P 500 and the Hang Seng index futures contracts is the MVHR estimated using the MRS-OLS model, while the optimal hedging strategy for the Nikkei 225 and the FTSE 100 futures contracts is the MVHR estimated using the Asymmetric-Diagonal-BEKK-GARCH and the Asymmetric-DCC-GARCH model, respectively. As in the out-of sample investigation, the time-varying models such as the BEKK-GARCH models especially the Scalar-BEKK model outperform those state-varying MRS models in majority of futures contracts in both one-step- and multiple-step-ahead forecast cases. Overall the evidence suggests that there is no single model that can consistently produce the best strategy across different index futures contracts. Moreover, using more sophisticated models such as MRS-GARCH models provide some benefits compared with their corresponding single-state GARCH models in the in-sample case but not in the out-of-sample case. While comparing with other types of models MRS-GARCH models do not necessarily improve hedging efficiency. Furthermore, there is evidence that using Bayesian Gibbs-sampling approach to estimate the MRS models provides investors more efficient hedging strategy compared with the MLE method.
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Neto, Carlos Santos Amorim. "Efetividade do hedge para o boi gordo com contratos da BM&FBOVESPA: análise para os estados de São Paulo e Goiás." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/11/11132/tde-12032015-152555/.
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O objetivo geral deste trabalho foi avaliar a eficiência do mercado futuro como forma de mitigação do risco associado aos preços do boi gordo para as praças de Araçatuba (SP) e Goiânia (GO). Calculou-se a efetividade do hedge por meio da razão ótima de hedge para as praças estudadas no período de 2002 a 2013, utilizando três tipos de modelos econométricos. No primeiro modelo, as variâncias e covariâncias condicionais foram tratadas como constantes e os preços spot e futuro não foram considerados correlacionados no tempo; no segundo modelo, relaxou-se a hipótese de que os preços spot e futuro não são correlacionados no tempo, portanto, adicionou-se um vetor de correção de erros ao modelo; e, no terceiro modelo, assumiu-se que as variâncias e covariâncias condicionais não são constantes. Os resultados obtidos por esses métodos indicaram que o uso do contrato futuro de boi gordo diminuiu a variância dos retornos no período estudado, de modo que as estimativas dinâmicas foram inferiores na efetividade em diminuir o risco de preço diante das estimativas obtidas por modelos estáticos. Ainda com o intuito de avaliar a eficiência do mercado futuro de boi gordo, foram quantificados a variância e os retornos do confinador nas praças estudadas através de simulações de compra de boi magro e posterior venda de boi gordo, realizando, simultaneamente, o hedge no mercado futuro. Observou-se que a utilização do contrato futuro diminuiu o coeficiente de variação para os períodos analisados em comparação às estratégias que não realizaram a utilização do hedge.The general objective of this research was to evaluate the efficiency of futures market in order to mitigate the risk of price of live cattle to the producers of Araçatuba (SP) and Goiânia (GO). To measure this effectiveness, we estimated the optimal hedge ratio from the period of 2002 to 2013, using three types of econometric models. In the first model, conditional variances and covariances were treated as constant and the spot and future prices were not considered correlated in time; in the second model, we relaxed the hypothesis that spot and future prices were not correlated in time, so, we added an error correction vector to the model; and, in the third model, we assumed that the conditional variances and covariances are not constant. The results obtained by these methods indicated that the use of live cattle contract was able to reduce the risk and also that the dynamic estimates do not overcome the static estimates. We also calculated the variance of returns for the producers of Araçatuba e Goiânia by purchasing simulations of steers and subsequent sale of live cattle, performing simultaneously the hedge on the market future. It was observed that the use of the futures contract decreased the coefficient of variation for the periods analyzed compared to the strategies that did not undergo the use of hedging.
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Nogueira, Cinthya Muyrielle da Silva. "Efici?ncia e raz?o de hedge: uma an?lise dos mercados futuro brasileiros de boi, caf?, etanol, milho e soja." Universidade Federal do Rio Grande do Norte, 2013. http://repositorio.ufrn.br:8080/jspui/handle/123456789/12233.
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Previous issue date: 2013-10-08This 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
Esta pesquisa objetivou investigar a efici?ncia e raz?o ?tima de hedge para os mercados futuro de boi, caf?, etanol, milho e soja. Este trabalho tratou a raz?o ?tima e efetividade de hedge atrav?s de modelos GARCH multivariados com termo de corre??o de erro, atentando para o poss?vel fen?meno de diferenciais de raz?o ?tima de hedge nos per?odos de safra e entressafra. A raz?o ?tima de hedge deve ser maior na entressafra devido ? maior incerteza com rela??o a um poss?vel choque de oferta (LAZZARINI, 2010). Dentre os contratos futuros tratados nesta pesquisa, os contratos de caf?, etanol e soja ainda n?o foram objeto de investiga??o desse fen?meno. Al?m disso, os contratos futuros de milho e etanol ainda n?o foram objeto de pesquisas que tratam de estrat?gias de hedge din?mico. Este trabalho se diferencia ainda por incluir o mecanismo de corre??o de erro na modelagem GARCH, o que nunca foi considerado ao se investigar poss?veis diferenciais de raz?o ?tima de hedge nos per?odos de safra e entressafra. Foram utilizadas como pre?o futuro das commodities as cota??es das mesmas no mercado futuro da BM&FBOVESPA e como pre?o ? vista o ?ndice CEPEA, no per?odo de maio de 2010 a junho de 2013 para boi, caf?, etanol e milho e at? agosto de 2012 para a soja, com frequ?ncia di?ria. Foram obtidos resultados semelhantes para todas as commodities. H? rela??o de longo prazo entre os mercados ? vista e futuro, bicausalidade entre os pre?os ? vista e futuro do boi, caf?, etanol e milho, e unicausalidade do pre?o futuro da soja sobre o pre?o ? vista. A raz?o ?tima de hedge foi estimada a partir de tr?s diferentes estrat?gias: regress?o linear por MQO, modelo BEKK-GARCH diagonal e modelo BEKK-GARCH diagonal com dummy de entresssafra. O modelo de regress?o por MQO apontou para a inefici?ncia de hedge, tendo em vista que as raz?es ?timas apresentadas foram muito baixas. O segundo modelo, que representa a estrat?gia de hedge din?mico, captou varia??es temporais na raz?o ?tima. A ?ltima estrat?gia de hedge n?o detectou diferencial de raz?es ?timas de hedge entre os per?odos de safra e entressafra, logo, ao contr?rio do que se esperava, o investidor n?o precisa aumentar seu investimento no mercado futuro durante a entressafra
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Júnior, José César Cruz. "Modelo de razão de hedge ótima e percepção subjetiva de risco nos mercados futuros." Universidade de São Paulo, 2009. http://www.teses.usp.br/teses/disponiveis/11/11132/tde-05082009-075152/.
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O objetivo deste trabalho foi investigar motivos pelos quais os produtores brasileiros de boi gordo e milho fazem relativamente pouco uso dos mercados futuros como ferramenta de gerenciamento de risco de preços. Duas abordagens diferentes foram apresentadas na pesquisa. Para o mercado de boi gordo, onde a presença de hedgers parece ser maior, um modelo de razão de hedge ótima alternativo ao tradicional modelo de mínima variância foi utilizado. O modelo alternativo faz uso de uma função de utilidade com aversão relativa ao risco constante para modelar as preferências dos indivíduos. Esta abordagem é considerada mais realista, por permitir que o nível absoluto de aversão ao risco se altere com a riqueza. Além disso, uma medida de downside risk e o relaxamento das hipóteses do modelo tradicional de mínima variância foram adicionados na análise. De acordo com os resultados, quando consideradas a possibilidade de se realizar investimento em um ativo alternativo ao mercado agropecuário, e a presença de custos de transação, o incentivo ao hedge se reduz acentuadamente. A utilização de uma medida alternativa de risco colaborou para esta redução, que foi mais acentuada para indivíduos menos aversos ao risco. Isto pode ser concluído observando-se que as razões de hedge ótimas, obtidas através da maximização da utilidade esperada dos indivíduos, foram, em grande parte, inferiores àquelas obtidas pelo modelo tradicional. Além disso, na maior parte dos casos, a utilização das razões de hedge ótimas alternativas mostrou-se mais eficiente que a obtida pelo modelo tradicional, pois possibilitou a obtenção de maiores razões retorno/risco no período selecionado para teste. Para o mercado de milho, um questionário foi aplicado a 90 produtores no sul e centro-oeste do Brasil. O questionário teve o objetivo de verificar se existem sinais de excesso de confiança nos preços por parte dos produtores de milho entrevistados. Adicionalmente, perguntas sobre o conhecimento do mercado futuro na BM&FBOVESPA foram também apresentadas. Em relação a este último tema, a maior parte dos produtores respondeu que conhece sobre o mercado futuro na bolsa brasileira, mas não fazem uso do mesmo. O principal motivo apontado pelos produtores foi não possuir informação suficiente sobre os mercados futuros. Associado a este resultado, descobriu-se que existe pouco incentivo para que os produtores realizem proteção de preços da produção, pois, para a maior parte dos entrevistados, as variâncias subjetivas de preços foram significativamente inferiores às variâncias dos preços históricos no mercado físico e futuro. Este resultado permitiu concluir que o excesso de confiança nos preços pode ser considerado uma explicação alternativa para o baixo uso dos mercados futuros como ferramenta de gestão de risco de preços. Como conclusões gerais, ações que visem promover reduções de custos de transação no mercado futuro e uma maior divulgação dos benefícios desta importante ferramenta na redução de risco de preços devem ser mais exploradas pela BM&FBOVESPA. Além disso, a promoção do maior conhecimento a respeito de como se negociar nesse mercado pode ser também uma boa estratégia para se fazer com que um maior número de produtores passe a negociar nesse mercado.This research aimed to investigate the significant underuse of futures markets as a risk management tool by Brazilian live cattle and corn producers. To this end, the paper used two different approaches. In the live cattle market, where there appears a higher participation of hedgers trading, an alternative hedge ratio model was used instead of the standard minimum variance model. The alternative model uses a constant relative risk aversion utility function to model individual preferences. This approach is considered more realistic as use of the constant relative risk aversion utility function allows for the absolute level of risk aversion to change with wealth. In addition, a downside risk measure was introduced and certain restrictive assumptions to the minimum variance model were relaxed. According to the results, when the possibility of investment in an alternative asset and transaction costs are considered, the incentive to hedge is dramatically reduced. The use of an alternative risk measure also proved important to this reduction, which was higher for less risk averse individuals. This conclusion may be drawn after observing that the optimal hedge ratios obtained from the expected utility maximization are, in most cases, lower than those obtained by the standard model. Moreover, in most cases the use of alternative optimal hedge ratios provides higher return/risk ratios during the test period. For the corn market, a survey questionnaire was conducted of ninety producers in South and Central- West Brazil. The survey was conducted in order to verify the presence of overconfidence in prices among corn producers. The survey also asked questions regarding their knowledge of futures markets at BM&FBOVESPA. Most respondents answered that while they know about futures markets at the Brazilian board of trade, they do not trade on it because they do not have enough information about trading. The results also revealed that there is a low incentive for producers to hedge their production in futures markets because for most producers, subjective price variances are significantly lower than the variance of historical futures and spot prices. Given the results, one may conclude that the overconfidence effect in prices can be considered an alternative explanation to the low use of futures markets as a price risk management tool. Furthermore, actions which promote transaction costs reductions and promote the benefits to producers of using this important risk management tool while trading in the futures markets must be more carefully explored by the BM&FBOVESPA. Moreover, promoting knowledge of trading in futures markets may likely be a successful strategy for the wider adoption of futures trading among corn and live cattle producers.
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Engström, Daniel, and Niklas Gustafsson. "Swedish Equity Sectors Risk Management with Commodities : Revisiting dynamic conditional correlations and hedge ratios." Thesis, Linköpings universitet, Nationalekonomi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139040.
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The purpose of this study is to investigate changes in dynamic conditional correlations between Swedish equity sector indices and commodities using oil, gold, copper and a general commodity index. Additionally the purpose is to evaluate which of the two methods, DCC- GARCH or GO-GARCH that is more efficient in estimating correlation for hedge ratio calculation. Daily data on the FTSE30 index of Sweden and its sector indices have been studied between the years 1994 and 2017. A DCC-GARCH (1,1) and GO-GARCH (1,1) model with one autoregressive term AR(1) using multivariate Student t- and Multivariate Affine Negative Inverse Gaussian distribution were used to estimate conditional correlations. Correlations between Swedish FTSE30, its sector indices and commodities are considerably lower than previous research has found American or emerging markets correlation with commodities to be. This suggests better diversification opportunities with commodities for the Swedish market. Optimal hedge ratios (OHR) was calculated and back tested using a rolling window analysis with 1000 days forecast length and 20 days re-estimation window and evaluated using a calculated hedge effectiveness index (HE). Determined by HE, copper is the best hedge for the Swedish composite FTSE30 and sector indices using conditional correlation from the GO-GARCH during the data period. Gold is considered as a semi-strong safe haven due to its negative correlation with all sectors. Additionally, this study identifies a temporarily large increase in the correlation between the Swedish equities sectors and composite index with commodities around the years 2015/2016. This study also emphasizes the difference between stressful and calm periods in the market.
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Leite, Gustavo Ribas de Almeida. "Hedge de crédito através de equity: uma análise empírica com uso de ativos corporativos brasileiros." reponame:Repositório Institucional do FGV, 2011. http://hdl.handle.net/10438/9777.
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This paper aims to analyze the results of an operation to hedge a diversified credit portfolio through the use of equity. Initially, a reference to the main theoretical aspects of this dissertation with their definitions and literature review will be made. Furthermore, there will be an explanation about the basic parameters of the selection of the sample used and the period during which such protection strategy will be implemented.
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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Li, Chiu-chan, and 李秋貞. "Leptokurtic Distribution and Optimal Hedge Ratio." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/84503226020231308652.
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碩士國立高雄第一科技大學
金融營運所
92
When we use futures to hedge a portfolio of risky assets, the most important objective is to estimate the optimal hedge ratio (OHR). When the futures price follows a martingale and investors have mean-variance utility, the OHR is equal to the minimum variance hedge ratio. Owing to time-varying volatility in financial asset returns, moving average, GARCH, or EWMA models are commonly employed to estimate OHR. All of the approaches to estimating the OHR described above are based on the sample variance and covariance estimators of returns. These are consistent estimators of the population variance and covariance, irrespective of the underlying distribution of data, but they are not in general efficient. In particular, when the distribution of the data is leptokurtic, these estimators will attach too much weight to extreme observations. This paper uses the Power EWMA estimator of Guermat and Harris (2002) to estimate OHR. The Power EWMA estimator (that is, the robust estimator) can capture the leptokurtic distribution of the data. We also compare the results of the robust estimator to those based on the standard estimators. Our empirical analysis is restricted to the SGX-DT and the TAIFEX Taiwan stock index futures. The empirical results show that use of the robust estimator generates reductions in the variance of the hedged portfolio and the volatility of the OHR for the SGX-DT futures market, and for subperiod 1 of high kurtosis. It also reduce the transaction costs of rebalancing that are associated with changes in the OHR.
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Tseng, Yingli, and 曾瑛琍. "Portfolio Value And The Optimal Hedge Ratio." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/19991715402624703901.
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碩士東海大學
財務金融學系碩士在職專班
100
To make the stock portfolio will not suffer huge losses in the broader stock index fell , and the value of its investment portfolio to maintain stability . Therefore, this study has a basket of equity portfolio investment , for fear fell taken short hedging strategy to sell stock index does not consider transaction costs, exchange rate risk, the transaction limit on the number respectively to explore the use of the Taiwan stock index futures ( TX ), Taiwan index options ( TXO ) to circumvent the risk of a single stock system , hedge length of the period of two kinds in use day , week, etc. , the use of different beta estimation model to find the optimal hedge ratio , and compare hedge before and after the standard deviation the size and the choice of the hedging period . The empirical results show the better of the portfolio hedge ratio of the standard deviation of minimum variance , and TAIEX options hedge standard deviation of the poor , showing the introduction of the futures and spot -linked higher , as a portfolio hedge The tools can be effective to reduce systemic risk . In addition , in terms of hedging performance of hedge performance using daily returns better than the hedging performance of the weekly return . Therefore , this study confirmed that the performance is better than a simple hedge with minimum risk hedge ratio method , and simple hedge will is better than not hedging .
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Suh-Jen, Chen, and 陳素珍. "OPTIMAL HEDGE RATIO OF HEDGING DOWNSIDE RISK." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/82413856635719149509.
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碩士國立臺灣大學
國際企業學研究所
87
One of the major functions of derivative instruments is risk reduction. A long-standing tradition in the finance literature treated the risk with a two-sided notion. Standard deviation or variance are employed to measure risk. However, in fact corporate managers are more concerned with downside risk, the variability in losses. An appropriate measure of the downside risk is lower partial moment (LPM). The thesis construct a bivariate APARCH-M model for the spot and futures returns and derives the time-varying LPM hedge ratio. The purpose of the thesis is to compare the LPM hedge ratio with the traditional minimum variance (MV) hedge ratio. The method is applied to the MSCI Taiwan Index Futures traded in the Singapore International Monetary Exchange (SIMEX). For the futures series, the settlement prices of the nearest contract are used. For the spot series, the closing index values are used. Our data consist of daily observations of the spot and futures prices from July 2, 1997 through March 30, 1999. Thus, the data set consists of 477 daily observations. The conclusions of the study are presented as follows： 1. Both the spot and futures series are not stationary. However, further analysis reveals that the spot and futures series have stationary properties as the first difference. 2. The spot and futures series have the cointegration relationship, so we have to add the error correction term into APARCH-M model. Besides, both the series have ARCH effect. 3. Both the LPM hedge ratio and MV hedge ratio are time-varying. When compared to the MV hedge ratio, we found that the largest difference appears when the order of the lower partial moment is small and the target return is positive and large. When the target return is 1.5%, and the order is 1, the LPM ratio has the largest mean and standard deviation.
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Hung, Wei-Kai, and 洪煒凱. "Futures Optimal Hedge Ratio and Transaction Cost." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/tg948v.
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碩士國立交通大學
經營管理研究所
107
This paper uses three smoothing strategies, moving average (MA), exponential smoothing (EWMA), and Hodrick-Prescott Filter (HP-Filter), to curb the transaction cost while hedging with dynamic models, such as CCC and DCC-GARCH models. In order to look for the relationship between the hedging performance and the transaction cost, the smoothing parameters in each strategy are given different values. The sample set is built by the weekly data of fourteen underlying assets and its corresponding futures across six investment classes. With the evaluation of the one-period-ahead out-of-sample hedging performance with and without smoothing during the sample period from July 3, 1998 to June 26, 2015, the result shows that the hedging performance became worse in most of the futures market, no matter which smoothing methodologies are used. In addition, according to the comparison within three strategies of different smoothing parameters, the smoother the smoothed dynamic hedge ratio series are, the more cost can be cut down. Moreover, different smoothing strategies also show different patterns between portfolio variance and transaction cost in the same futures markets, while the moving average and the HP-Filter show a negative correlation, and the exponential smoothing demonstrates a positive one in most futures commodities.
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HE, JIA-JYUN, and 何嘉郡. "The Optimal Hedge Ratio with Downside Risk." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/39757254183158757189.
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碩士德明財經科技大學
理財與稅務管理研究所
99
Abstract As the economy grows, financial market has gained more exposure. When investors construct their investment portfolio, they can diversify the risks by having various investment portfolios. Besides, derivatives are also used to hedge against risk. Normally hedge ratio depends on the smallest variance. However, this method does not consider the fact that variance consists both gain and loss risks. In fact, investors are not bothered by gain risk, but they are worried about the loss risk. Thus, it is unreasonable to apply full variance directly to get the hedge ratio. In view of this, this research adopts the downside risk theory by Markowitz（1959）、Bawa（1975）and Fishburn（1977）to measure the loss risk. This research takes Taiwan Stock Exchange and Taiwan futures Exchange as the benchmark. Different estimation period, holding period and sampling period are taken to compare the difference among three investment portfolio, i.e. mean variance, mean-symmetric-lower-partial-moment and mean-asymmetric-lower-partial-moment. Empirical observation shows us that the models that consider about the downside risk performs better than those that consider full risk in avoiding excess loss regardless of which estimation period, holding period and sampling period are taken. Thus, it is advisable that investors refer to the downside risk model of this research to avoid excess loss risk when they invest in Taiwan stock market.
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Huang, Hsin Kai, and 黃信凱. "Robust estimation of the optimal hedge ratio." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/69744824660876374796.
Full textAbstract:
碩士國立政治大學
國際經營與貿易研究所
97
Because on the method of Harris and Shen (2003), we implement the robust estimator of optimal hedge ratio in Taiwan stock market. By using the Taiwan Stock Index and Taiwan Stock Index Futures, we used the robust estimation of optimal hedge ratio. We use two estimators, the rolling window model and the exponentially weighted moving average (EWMA), to estimate the robust optimal hedge ratio. We also compare the hedging effectiveness of the robust hedge ratios and the traditional least- squared hedge ratios. We find that the volatility of the hedged portfolio using robust optimal hedge ratio is substantially lower than that of the portfolio using the traditional hedge ratios. With the less excessive volatility, the transaction cost decrease substantially, and the cost of rebalancing portfolio is lower as well.
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Yeh, Hui-Fen, and 葉惠芬. "A study of optimal hedge ratio for stock index futures－a comparison of optimal VaR Hedge and M-V hedge." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/20857184340437764716.
Full textAbstract:
碩士國立高雄第一科技大學
財務管理所
91
In the futures market, the main hedging objective generally focuses on achievement of the minimum variances. However, from the viewpoint of the investor, he or she generally values the downside risk most importantly. This research applies the optimal VaR Hedge method to discover optimal hedging ratio. Furthermore, we will compare the hedging effectiveness of optimal VaR Hedge and Minimum Variance (MV) strategy. The results of performance show that Optimal VaR Hedge performs better than MV hedge.
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Wen-Chi, Chang, and 張雯琪. "A study of optimal hedge ratio and hedge performance for stock index futures." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/49715370265426136654.
Full textAbstract:
碩士淡江大學
管理科學研究所
92
Abstract The purpose of the thesis is to examine the hedging ratios and efficiency of stock index futures to Taiwan Stock Market The stock index data consist of TAIEX, TSEC Taiwan50 index and ETF. The stock index futures contracts include TX, MTX, T5F. Under th e objective functions of maximizing investors’ expected utility and minimizing portfolio risk. The study use four models to measure the hedge ratios and hedge performance. The model contents Minimum Variance（MV）Model、Lower Partial Moment（LPM）Model、Value-at-Risk（VaR）、and Expected Shortfall（ES）Model. The risk index contents HE1、HE2、HE3 and HE4. Conclusion are as following： 1、TO compare with different optimal hedging ratio, when the estimation period fixed, the hedging ratios decreased along with the hedging period increased. No matter what futures or hedge ratios we employ, hedging strategies will perform better generally when the estimation period or hedging period increased. 2、In hedge cost, The TAIEX and TX is higher than TAIEX and MTX. The TSEC Taiwan50 index and T5F is higher than ETF and T5F. The result shows that when the portfolio has higher volatility , the hedge cost is higher than another portfolio. 3、In sum, the performance of Minimum Variance（MV）Model hedge ratio is the best in almost all cases.
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He, Guang-Zheng, and 何光正. "Optimal hedge ratio for asset allocation of Differential Evolution." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/82807905983629256825.
Full textAbstract:
碩士輔仁大學
資訊管理學系
100
The purpose of this study is to build an integrated asset allocation of the portfolio selection, capital allocation and the hedge ratio. Portfolio of the Optimal Computing Budget Allocation (OCBA), the innovation of this study is to combine the differential evolution (DE), expect to identify the evolutionary characteristics, and Efficient Frontier, to enhance the investor's investment performance and reduce investment risk. This study use the stock index futures of Taiwan stock market, as experimental subjects, and evaluating of the model through the company's fundamentals indicators and portfolio return. In addition, we use the OCBA to solve the problem of optimal design of the DE parameters, and expect to improve the performance of DE evolution, as well as to construct the model of optimal portfolio allocation of funds and hedge ratio (OHR). The experimental results show that the OCBA parameter optimization module has good stability, effectiveness and efficiency. Secondly, DE asset allocation module to construct the optimal portfolio of hedge ratios in cattle, bear markets is a good performance. Third, the asset allocation and hedging strategies model with a hedging mechanism, have a lower investment risks and ability to improve profitability. Finally, this study design OCBA-DE asset allocation module, you can find the portfolio in line with the efficient frontier, but Dataset (Train7) market volatility is too large, resulting in a higher portfolio risk of the optimal hedging strategy.
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CHIN, CHENG WEN, and 鄭文欽. "THE OPTIMAL HEDGE RATIO OF STOCK INDEX FUTURES ── EMPIRICAL." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/41453369196955106186.
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Chuang, Cheng-Chiu, and 莊盛旭. "The Study of Optimal Hedge Ratio in Stocks Investment." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/87485812817300539677.
Full textAbstract:
碩士朝陽科技大學
財務金融系碩士班
92
Abstract To manage portfolio well, it depends not only on the fundamental and technologic strategies in searching out returns, but the diversification techniques in unsystematic risk reduce. Systematic risk can be eliminated by stock index futures and stock index options. Focus on diversification, this study takes the broad stock index as spot price, and computes the hedge ratios between stock spot and stock index futures, as well as the hedge ratios between stock spot and stock index options. Then, the hedge ratios are used to hedge the spot risk in simulations of investment. Finally, Different approaches used to compute hedge ratios are compared with each others in their performances. When stock spot is hedged by stock index futures, results show that the GARCH model performs better than the OLS model, and the OLS model than the Naïve model on a daily trading basis. The GARCH model outperforms the Naïve model and the Naïve model outperforms the OLS model on a weekly trading basis. In short, the GARCH model appears the best model in forecasting hedge ratio of the very next day. Evidence also shows that the performances observed in a weekly basis are always better that in a daily basis for all models. Thus, even for hedge, frequent trade is not a good policy. When stock spot is hedged by stock index options, the OLS model performs better than the GARCH model, and the GARCH model than the Naïve model in the first stage. The OLS model outperforms the Naïve model, and the Naïve model outperforms the GARCH model in the second stage. The GARCH model is outperforms the OLS model, and the OLS model outperforms the Naïve model in the third stage. It appears that no consist result can be drawn, and the OLS model likely performs best.
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Ching, Wang Shiu, and 王秀菁. "The optimal hedge ratio in future market - time series analysis." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/12222050631744010336.
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WANG, CHIA-PIN, and 王嘉彬. "The study on the optimal hedge ratio using wavelet analysis." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/70928232414601744227.
Full textAbstract:
碩士樹德科技大學
金融與風險管理系碩士班
99
This paper argues that the noise contained in the original series influence the hedging effectiveness, especially in the long term. First of all, the noise is removed by using wavelet analysis. Secondly, the hedge ratios are estimated by OLS and GARCH with original series and de-noise signal, respectively. Finally, this paper compares the original series and de-noise signal of the hedging effectiveness. The best hedging effectiveness is using OLS model estimations by de-noise signal under four weekly. Furthermore, the most significant improvement on hedging effectiveness is using the BGARCH model with de-noise signal.
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Miao, Howard, and 繆俊華. "The Optimal Hedge Ratio of Foreigh Currency Future and Option." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/84148366172939959775.
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Chiang, Pei-chen, and 江佩蓁. "The Optimal Hedge Ratio for Currency Futures under Leptokurtic Distribution." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/85252549963079961790.
Full textAbstract:
碩士國立高雄第一科技大學
金融營運所
93
The major function of currency futures is how to avoid the risk. And the performance of hedging strategies depends on the adequacy of hedging ratios. Therefore, how to decide the hedging ratios is the major part when we try to set up our hedging strategies and afterward to measure the effectiveness. This paper tries to use time-varying variance to estimate hedging ratios, and considers that financial asset returns are fat-tailed or leptokurtic. Therefore, this paper uses the Power EWMA estimator of Guermat and Harris (2002) (this is, the robust estimator) and bivariate GARCH model to estimate OHR. Our empirical research uses British Pounds, Canadian Dollar, Japanese Yen, and Euro Fx as currencies of consideration. The empirical results show that when financial asset returns are leptokurtic remarkably, the Power EWMA estimator outperforms bivariate GARCH model in the effectiveness of the hedge ratio.
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Weng, Ni-Ling, and 翁妮鈴. "Optimal Hedge Ratio of Energy Futures Using CCC and DCC Models." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/71366762412200080538.
Full textAbstract:
碩士國立交通大學
經營管理研究所
95
Crude oil keeps country’s economy running, and crude oil futures is one of the most actively traded commodity, as well as the world's largest-volume futures contract trading on a physical commodity. Energy price is highly dependent on global macroeconomic conditions, and what amount of energy futures contracts should be purchased to minimise the risk of holding spot energy is important issue in recent years. This research applies various methods in minimum-variance hedge strategy, and computes the Optimal Hedge Ratios (OHRs) between the amount of spot and futures for energy commodity prices using different econometric methods. Namely, using Dynamic Conditional Correlation, and DCC-CARR model proposed by Chou et. al. (2005) to compute OHRs. Other methods used for comparison include the ordinary least squares (OLS) estimator, Constant Correlation models and so on. The research period is from 1995 to 2007, and daily data is collected. Different methods are compared with each other in their hedging performance of variance-reduction. For the out of sample hedge, the CCC or DCC model is the best one for three commodities, and could to find the minimum-variance of a portfolio for investor. In conclusion, dynamic hedging model is better than the traditional OLS model. Meanwhile, the optimal hedge ratio is not constant, it should be time-varying.
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Tseng, Cheng-Wen, and 曾正文. "Robust Estimation of Optimal Hedge Ratio in Taiwan stock index futures." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/01201599776127779329.
Full textAbstract:
碩士淡江大學
財務金融學系碩士班
93
This article considers solving that conditional distribution of most financial asset return tends to vary over time and the distribution of underlying asset does not conform with ordinary assumption simultaneously. In order to fit time-varying volatility in returns of asset, estimators dealt with simple weighted moving average (SWMA), GARCH, or EWMA models are usually applied. However, these methods are estimated according to sample variance and covariance estimators of returns. When the distribution of underlying asset does not match with the ordinary assumption, the estimators are not in general efficient. The primary purpose in the article is to verify the dynamic hedging strategies in Taiwan stock index futures and MSCI futures by estimating the robust estimation of optimal hedge ratio (OHR) when the data is leptokurtic and fat-tail. This article uses conditional SWMA and EWMA at the same time to estimate the robust estimation of OHR, and compares with the results in unconditional SWMA and EWMA. The variance of hedged portfolio is computed in the robust OHR are less than that in the unconditional way. In addition, the variance of hedged portfolio is computed in the robust OHR are much less than before, thus reducing the transaction costs which produces in dynamic hedging strategies.
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Quar, Chen Jear, and 陳治國. "The Estimation of Optimal Hedge Ratio - The Application of ARCH Model." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/84698739087166977024.
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Chao, Wan-Hsin, and 趙婉辛. "Estimation of Optimal Hedge Ratio for Stock Index Futures：Bias-Corrected EWMA Method." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/c4v78p.
Full textAbstract:
碩士國立高雄第一科技大學
財務管理所
96
This study applies Bias-Corrected EWMA model to estimate optimal hedge ratios for stock index futures. Using for stock index futures and three sample periods, we compare the optimal hedge ratios and hedge performances with EWMA model which under normal distribution and Power EWMA model which considers the distribution of assets is leptokutic. Empirical result shows that the (1) Four stock index futures under any of models, the hedge performances of Bias-Corrected EWMA model outperform EWMA model and Power EWMA model. (2) There is no consistency between the hedge performances and various decay factors.
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Li, Gang. "The determination of an optimal hedge ratio and a generalized measure of risk." Thesis, 2006. http://spectrum.library.concordia.ca/8870/1/MR14371.pdf.
Full textAbstract:
The use of futures contracts as hedging instruments to reduce risk has been the focus of much research. Various risk measures have been developed and have subsequently been employed in an effort to create hedging strategies and to calculate optimal hedge ratios. This thesis proposes a more generalized risk model to measure the risk of hedged assets. The five-parameter model presented herein assumes that each investor has a different target return, level of risk aversion, and degree of sensitivity to lower and higher partial moments. The optimal hedging activity for each investor should then seek to minimize the unique generalized risk measure. This paper utilizes an out-of-sample test on a hedged position in the S&P500 index in the period from December 1982 to December 2004. Tests are conducted to determine whether the change of target returns and sensitivity parameters will affect optimal hedge ratios. In addition, whether hedging effectiveness changes significantly in-sample versus out-of-sample, and between each model and a naïve hedging strategy is investigated. Also, mean returns of hedged portfolios are compared for various models. This thesis makes three important contributions. First, this study is the first to implement both higher and lower partial moments in the determination of optimal hedge ratios. Second, an out-of-sample test is considered while most studies use only in-sample tests. Third, this thesis is the first to use discontinuous sample periods to separate market conditions and to analyze hedging performance in bull and bear markets
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KAO, PEI-LIEN, and 高佩蓮. "The Optimal Hedge Ratio and Performances of USD/CNH Futures in Cross-Markets." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/fbqj38.
Full textAbstract:
碩士東吳大學
國際經營與貿易學系
106
The empirical results are as follows: first, in terms of overall hedge performance, the risk reduction is the highest by using the Mean-Variance model in Taiwan futures market. Second, if consider the expected return reduction, the Mean-Semi Variance Approach in Singapore futures market was preferred. Third, if we consider the variation in hedge ratio, the volatility of the hedge ratio of the Minimum Variance Approach is the lowest, which imply that the transaction cost is less.
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Chen, Shu Chieh, and 陳恕潔. "On the Optimal Hedge Ratio Between Stock and Future—Application of Copula Functions." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/34775675289631041389.
Full textAbstract:
碩士輔仁大學
金融研究所
97
Abstract This thesis uses the stock and future market data of Taiwan, Japan, Hong Kong, and Korea to analysis hedging performance. This thesis uses constant correlation and dynamic correlation to estimate hedge ratio and want to know which have better hedge effective. In addition, this thesis uses three Copula model to estimate dynamic correlation and want to know which have better hedge effective. Later but not least, holding period of the portfolios is extended to one day, two days, and three days. This thesis wants to know what holding period can make better hedging performances. Empirical result is that hedge ratio from dynamic correlation have better hedge effective than constant correlation. Different market, different period of empire, different holding period can't affect this result. Three hedge ratio from dynamic correlation, in period of simulate hedging 1, Gumbel Copula have better hedge effective. The other factors differs can't affect this result. In the other period of simulate hedging, besides, Hong Kong in the period of simulate hedging 2, Guassian Copula have better hedge effective. The other empirical result, Clayton Copula have better hedge effective. The other factors differs can't affect this result. Empirical result in three holding period of the portfolios, no one holding period of the portfolios is better than the other. Keywords: Copula model, GARCH model, hedge ratio
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Chen, Nash, and 陳昱宏. "Optimal Hedge Ratio of Commodity Futures Using Bivariate DCC-CARR and DCC-GARCH Models." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/83027752092707981578.
Full textAbstract:
碩士國立中央大學
財務金融研究所
93
When traders participate in both cash and futures markets they must choose a hedging strategy that reflects their individual goals and attitudes towards risk. At the same time, optimal portfolio management depends not only on the fundamental and technological analysis in maximizing returns, but it also encompasses diversification techniques in (un)systematic risk. Nevertheless, systematic risk can be effectively eliminated by futures contracts. In this thesis, we focus on diversification to minimize the portfolio variance and will consider the minimum-variance hedge strategy because the benefits of sophisticated estimation techniques of the hedge ratio are small (Lence, 1995b). At first, we take the commodity prices, and then compute the Optimal Hedge Ratios (OHRs) between spot and futures using different methods. Here, the hedge ratios are used to hedge the spot price risk in simulations of investment. In analysis, we use the Dynamic Conditional Correlation - Conditional Autoregressive Range (DCC-CARR) model proposed by Chou et. al. (2005) to compute the OHRs. Other alternative methods used for comparison include the ordinary least squares (OLS) estimator which provides an estimate for the minimum-variance hedge ratio, Constant Conditional Correlation –Generalized Autoregressive Conditional Heteroskedasticity and CARR (CCC-GARCH and CCC-CARR) models, and DCC-GARCH model. Different methods used to compute hedge ratios are compared with each other in their performance of variance-reduction. While the spot price risk is hedged by their corresponding futures, within-sample hedge, the results show that the DCC-CARR model performs better than the other hedge models for the selected commodities with the exception of gold. For an out-sample hedge in one-period it supports that the DCC-CARR model is the best model for any commodity. But, in other period, the results are mixed because of the trading noises. In conclusion, we suggest that the DCC-CARR model is the better model for investors to find the minimum-variance of a portfolio.
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Fu, Cong Yi, and 傅叢禕. "A Comprehensive Study to the Optimal Estimations of Hedge Ratio by Monte Carlo Simulation." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/w7zqk8.
Full textAbstract:
碩士國立清華大學
計量財務金融學系
103
Abstract Estimation error has been a major problem when the simple linear regression model is used to estimate optimal hedge ratios. Herbst (1989) pointed out that Ederingtion’s (1979) method of using the OLS regression to estimate optimal hedge ratios between spot and futures rates of foreign currencies would yield biased estimators because the error terms are significantly serially correlated which violates stringent assumptions of the OLS regression. Meanwhile, time series data of spot and futures may follow the I (1) process and is not cointegrated. Thus the OLS will yield spurious estimators. Due to this problem, more recent studies estimate the optimal hedge ratios based on the change of spots and the change of futures contracts. These studies transform the nonstationary process into the stationary process in order to avoid solving the possible spurious regression problem. Thus, they only study hedge ratio problem based on either the cointegration or stationary situation, which in fact is not necessary. Even if we get stationary equations by taking first difference of dependent and independent variables, heteroscedasticity usually appears, making another estimation error. This paper provides a guideline on how to choose the estimation methods to solve the estimation error problem in different situations. We perform Monte Carlo simulations of cointegrated and spurious regressions with and without measurement errors and heteroscedasticity. Serial correlation is simulated in all the cases. Then eight estimation methods are used to estimate these regressions. Finally, we find the best estimation method in each case. In empirical study, we use CVAR (Gatarek and Johansen, 2014) model combined with our eight estimation methods to compute post-sample performances and we show that the present method produces better results than those of the VAR and EC models, which are prevalent in hedge ratio study.
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Hsiao, Ying-Tse, and 蕭穎澤. "The application of Riskiness on the optimal natural hedge ratio in life insurance companies." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/vksf5w.
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碩士國立臺灣大學
財務金融學研究所
107
Since the fluctuation of mortality rates will make an opposite impact on the values of annuity and life insurance, natural hedging strategy suggests creating a product mix from both products to hedge longevity risk. Numerous papers have provided findings which determine optimal hedge ratio by minimizing different risk measures, while none of whom satisfy the monotonicity with respect to stochastic dominance. To measure risk more objectively, Aumann and Serrano (2008) have proposed a new economic index of riskiness. The index, Riskiness, contains many good properties including duality, positive homogeneity, first-order stochastic dominance and second-order stochastic dominance. This thesis applies the approach that determines the optimal natural hedge ratio by minimizing Riskiness of product mix (Chen et al., 2014). To create a hedging portfolio, CBD model (Cairns et al., 2006b) is implemented to project the future mortality rates in U.S. The results show that whether whole-life or term-life insurance serves as a hedging vehicle, Riskiness-minimizing method can properly reflect both gains and losses in comparison of the CVaRM method (Tsai et al., 2010), that is, a higher profit loading and a lower Riskiness.
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Yu, Kai-Hui, and 游凱卉. "The Optimal Hedge Ratio and Timing under the Adaptive Market Hypothesis: An Empirical Study of the S&P500 Index." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/fe65x6.
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碩士國立中央大學
財務金融學系
104
In this studies, we have delved into the monthly logarithmic returns of S&P500 index to characterize the transition between efficient and inefficient market under the Adaptive Market Hypothesis (AMH). By utilizing the Markov switching regression, we identify the efficient and inefficient market regimes. Through implementing different strategy in each regime, we find evidence for the AMH in the aspect of hedging and investment. For hedging, we apply distinct hedge ratio in two market regimes, and the AMH hedge outperforms the naïve and the OLS hedge. And for investment, besides estimating switching model of conditional returns, we also construct the switching model of conditional Realized Volatility (RV), which is inspired by the volatility timing. By applying different investment strategy during inefficient periods detected by the Markov switching model, the AMH timing portfolio outperforms the B&H portfolio with the regime regression of conditional returns, and the cumulative returns even increase after including the volatility timing by implementing different strategy during the sentimental periods identified with the switching model of conditional RV. Besides appealing cumulative returns, the AMH timing portfolio also has significant cross-sectional returns after explained by a four-factor model and considering transaction costs.
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Chen, Yu-lang, and 陳玉郎. "APPLIES VOLATILITY SPILLOVER AND MRS-DCC-GARCH MODEL TO INVESTIGATE THE OPTIMAL HEDGE RATIO OF HONG KONG STOCK INDEX AND RELATED FUTURES MARKET." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/97490560429694655792.
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碩士銘傳大學
經濟學系碩士班
96
This thesis applies MRS-DCC-GARCH (Markov Regime Switching -Dynamic Conditional Correlation -Generalized Autoregressive Conditional Heteroskedasticity) Model, and VS-DCC-GARCH (Volatility Spillover -Dynamic Conditional Correlation -Generalized Autoregressive Conditional Heteroskedasticity) Model to investigate the optimal hedge ratio of Hong Kong Hang Seng stock index and related futures market. The rationale behind the use of these models stems from the fact that the dynamic relationship between spot prices and futures returns may be characterized by regime shifts. The empirical results show that MRS-CCC-GARCH model performs better than the other models.
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Jamil, Mehdi. "Currency hedging in emerging market investments." Master's thesis, 2019. http://hdl.handle.net/10362/73504.
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This paper investigates whether currencies enhance performance of portfolios
diversified over a number of different international markets from the perspective of an
American based investor and determines what is the source and the extend of the added value.
While the US market is considered to be the largest in the world, emerging markets are smaller,
more volatile and contain more inherent risks but they do present huge potential and
diversification opportunities for investors. Hence adding these foreign investments into their
portfolios present risk reduction benefits for investors but it exposes them to the notion of
currency risk. Hedging currency exposure could help mitigate those risks but it at what cost?
It is indeed shown that hedging levels have different impacts on performance but also on the
volatility associated with those investments. This paper aims at showing this risk-return
dilemma, and explore optimal hedging strategies to mitigate against currency exposures in
American emerging markets.
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Lin, Yen-Lin, and 林沿霖. "Nonlinear Cointegration and Optimal Hedge Ratios." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/69267356374947446777.
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碩士國立高雄應用科技大學
金融資訊研究所
98
In recent years, Taiwan's Financial markets are internationalization and liberalization, Government speed up the pace of financial products, Therefore, how investors pursuit of profit simultaneously to avoid risks, has become an important issue. This article use vector error correction model (VECM) and threshold vector error correction model (TVECM) and exponential smooth transition vector error correction model (ESTVECM) in order to find the optimal hedge ratio, and compare the hedging performance of different models. This article focuses on Taiwan's Weighted Price Index and Taiwan Stock Index Futures as study object and sampling period from January 2, 2004 to December 31, 2009. The study findings reveal: volatility of hedge portfolio will be increased with the rise in hedge horizon no matter what kind of model, and non-linear threshold error correction model can improve the performance of a traditional hedge model.
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Hsu, Mimg-Hsiu, and 許名秀. "Optimal Hedge Ratios Estimate :Comparison Among Alternative EWMA Method." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/65532171318311960987.
Full textAbstract:
碩士國立高雄第一科技大學
風險管理與保險所
97
This study applies the restricted least squares estimator(RLS),the absolute restricted least squares estimator(A-RLS), and Bias-Corrected EWMA model to estimate optimal hedge ratios for stock index futures. Using for stock index futures ,we compare the optimal hedge ratios and hedge performances with EWMA mode which under normal distribution and Power EWMA model which considers the distribution of assets return is leptokutic. Empirical result shows that the (1) Two stock index futures under any of models, using the hedge performances we can find Power EWMA model is the best. (2) There is no consistency between the hedge performances and various decay factors.
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Wei, Yang Tsung, and 楊宗瑋. "The discussion of regime switching model and optimal hedge ratios." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/12548088372396583329.
Full textAbstract:
碩士南台科技大學
財務金融系
94
This research primarily uses Markov Regime Switching model to investigate the optimal hedge ratio between Taiwan Stock Index and Taiwan Future Exchange (TAIFEX). In the past researches, when it comes to hedge ratio between spot and future markets, Bivariate-GARCH model is often used. This is because that Bivariate-GARCH model is able to catch the interaction between these two markets.On the other hand, Alizadeh and Nomikos（2004）claimed that there may be different regimes in the interaction between stock index and index future. Therefore, hedge ratios may depend on different regimes. Also, Sarno and Valente（2000）found Regime Switching Model outperforms OLS when investigating the relationship between stock index and index futures price. Thus, this research examines the optimal hedge ration in TAIFEX with Markov Regime Switching model.This research also takes Random Coefficient Autoregressive model (RCAR) and other models into consideration, such as Bivariate GARCH model, OLS, and Naïve, to compare the hedge efficiency between all models. Finally, the empirical result shows: RCAR outperforms other models in-sample, and MRS model is next to it; asymmetric Bivariate GARCH has better out-of-sample performance than other models, and RCAR Model is only second to it. Therefore, this research suggests that investors will be able to enhance efficiency in hedge strategy if they could take account of different regimes.
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Chen, Hui-Ying, and 陳慧吟. "The Optimal Hedge Ratios of Index Futures in Different Econometric Models." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/49105455523352257546.
Full textAbstract:
碩士逢甲大學
財務金融學所
92
The purpose of the thesis is to examine the optimal hedge ratios of major international stock index futures, including S&P 500, FTSE100, DAX30, Nikkei225, Hang Seng, SIMEX MSCI Taiwan, and TAIFEX Taiwan stock index futures, by using the bivariate asymmetric GJR EC-GARCH, GJR GARCH, EC-GARCH, GARCH, EC-OLS, OLS, and Naïve models. The objective functions of the expected utility maximization, portfolio variance minimization, and Sharpe-ratio model are employed to measure the hedge ratios and hedging effectiveness. Both within-sample and out-of-sample tests are performed. The results are summarized as follows: 1、 The results of unit-root tests indicate that the prices of spot and futures are non-stationary, and the first-difference is required to induce stationarity. Engle-Granger and Johansen statistics suggest that each stock index and its futures contract are cointegrated. Thus, an error-correction term should be included in the conditional mean equations. Volatility specification test results also indicate that information asymmetry exists in the second moments of the stock index return series except for Nikkei225. 2、 For conservative investors in both within-sample and out-of-sample tests, the hedge ratios of dynamic models and static models are close to one. The hedge ratios of TAIFEX Taiwan stock index futures are higher than that of SIMEX MSCI Taiwan stock index futures in within-sample tests. 3、 The results of the within-sample and out-of-sample tests reveal that error-correction models are better than other models. The hedging effectiveness is significantly positive in terms of portfolio risk reduction and expected utility improvement, except for Sharpe-ratio model. The empirical findings also suggest that for aggressive investors, the bivariate GJR EC-GARCH and EC-GARCH models would be the better choice in within-sample tests, whereas the bivariate GJR GARCH and GARCH models would perform better in out-of-sample tests. As for conservative investors, the error-correction OLS model would be the better choice in hedging, the results remain the same after considering the transaction costs in within-sample and out-of-sample tests. 4、 Compared with the hedging effectiveness of other models, the error-correction models perform better. Especially for conservative investors, there is no significant difference among GJR EC-GARCH, EC-GARCH, and EC-OLS models, even after considering the transaction costs. 5、 In within-sample and out-of-sample tests, conservative investors can use GJR EC-GARCH, EC-GARCH, and EC-OLS models to improve expected utility and decrease the risk of stock index price changes to an extent of 96 percent
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Chi, Jan Tsung, and 詹宗錡. "The Research of The Optimal Hedge Ratios and Hedge Performarce For Domestic Short Term Interest Rate Futures." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/66075353608070985555.
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碩士亞洲大學
經營管理研究所
94
The purpose of this research is to estimate optimal hedge ratio and compare hedge performance by using Naive model , OLS model and VECM model . The data include Taiwan 30-Day Commercial Paper Futures and Taiwan 10-Day , 90-Day , 180-Day Commercial Paper . The major results are as follows： 1. By using unit roots testing of all data , we find that the significance of unit roots and the nonstationarity of the price series . Hence , price series should be differenced to induce stationary . 2. The result of cointegration test has shown that there is a long-run equilibrium relationships between spot and futures prices . Consequently , a cointegration measure can be taken into account in the hedge model . 3. We find the same result in detecting the effects of in-of sample periods and out-of sample periods . The OLS model performs more well than all other hedge models for Taiwan 30-Day Commercial Paper Futures , and the VECM model is the second best . The results also has indicated that the VECM model can not improve the hedge performance . The portfolio including Taiwan 30-Day Commercial Paper Futures and Taiean 90-Day Commercial Paper can make the best hedge performance.
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Liu, Hsiao-Chun, and 劉肖君. "Analysis of the Optimal Hedge Ratios and the Hedging Effectiveness of Foreign Currency Futures." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/10371618177674709180.
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碩士淡江大學
財務金融學系碩士在職專班
99
US subprime mortgage crisis led to a global financial crisis in 2008. This highlighted that global financial market developed borderless and derivatives resulted in complicated financial environment. Foreign currency hedging has become a main issue for business and investment organizations. Variance was mostly used as a risk measure for financial assets in the past literatures. However, it is hard to distinguish the direction of changes in assets value for comprising upside and downside risk. In this essay, Minimum Variance Hedge Ratio (M-V) is compared with Lower Partial Moment (LPM) and Value at Risk (VaR), which are with the concept of downside risk, to find the optimal hedge ratios and hedging effectiveness. The data used in this essay is foreign currency futures of European Dollar (EUR), Japanese Yen (JPY), British Pound (GBP) and Australian Dollar (AUD) to US Dollar (USD). The empirical results show that the hedging effectiveness of foreign currency futures is VaR following LPM and M-V in static hedging strategy. On the other hand, the best strategy does not exist in dynamic hedging strategy. Investors should choose different strategies for different foreign currencies. For example, LPM is a better hedging strategy for EUR and AUD; GBP adopts VaR, and better hedging effectiveness for JPY is M-V. Moreover, the estimation period of 39 weeks obtains better hedging effectiveness and two-week hedging period is better than one-week.
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羅月璟. "A study of the optimal hedge ratios for U.S. Treasury Bill using futures contracts." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/16092280297631980896.
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Wu, Wen-Yi, and 吳玟儀. "Analysis of the Optimal Hedge Ratios and the Hedging Effectiveness of Foreign Currency Futures." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/9j3923.
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碩士逢甲大學
財務金融學所
90
As the interaction of international financial markets and the mobility of capital increases, the international financial risk, especially the foreign exchange risk becomes the major concern of multinational enterprises and individual investors. The purpose of the thesis is to study the optimal hedge ratios and hedging effectiveness of the foreign currency futures, including Japanese yen futures, British pound futures, Deutsche mark futures, Swiss franc futures, Canadian dollar futures, Australian dollar futures, and Euro futures. Besides the direct hedging, the cross hedging performance of Euro futures is also measured against the spot exchange rate risk of British pound and Swiss franc, respectively. The bivariate error-correction GARCH model, GARCH model, error-correction OLS model, and OLS model are used to measure the optimal hedge ratios and hedging effectiveness, based on the objective functions of maximizing expected utility and minimizing variance of portfolio returns. The empirical results of the study indicate that although the time series data of the currency spot and futures prices are nonstationary, there is a long-term cointegration relationship between them. Among the currency futures examined, the within-sample hedge ratios are found stationary. The within-sample hedging effectiveness of Australian dollar futures is the highest, while that of Canadian dollar futures is the lowest. The cross hedging performance of Euro futures is better in hedging the spot exchange rate risk of Swiss franc, which may be explained by the higher conditional correlation coefficients between them. As for the out-of-sample hedging effectiveness, Japanese yen futures and Australian dollar futures outperform the others. The empirical findings also suggest that the bivariate error-correction GARCH model and the GARCH model would be the better models for the aggressive investors with lower degree of risk aversion, whereas the bivariate error-correction GARCH model and the error-correction OLS model would be better for the conservative investors with higher degree of risk aversion. Overall, the naïve hedge model has the worst hedging performance.
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Hsieh, Mei-hua, and 謝美華. "A Study of Foreign Exchange Futures Optimal Hedge Ratios Estimation: Exponentially Weighted Moving Average." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/08707982456580457297.
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碩士國立高雄第一科技大學
財務管理所
93
ABSTRACT Risk managers generally concern the usage of futures to hedge the portfolio exposure. Investors, arbitragers, and hedgers can manage the assets well in the standardized futures market. This study mainly discusses how to use a simple approach to estimate the foreign exchange futures’ optimal hedge ratio (OHR) for well hedging performance. Under the most widely used minimum variance framework, OHR correlates to the estimation of the covariance between spot and futures returns and the variance of futures return. This paper replaces more complex models (like multivariate GARCH model) by the EWMA (exponentially weighted moving average) estimator for the estimation of OHR. Additionally, whether different settings of the decay factor influences the hedging performance is examined in the research. Five foreign exchange (GBP.EUR.JPY.AUD.CAD) futures’ OHR are computed and relative performance based on different decay factors are also compared to choose an optimal setting of the EWMA estimator. There are 1,000 daily samples covering the period from 2001.2.13 to 2004.12.31. The empirical findings of this research indicate that the highest hedging efficiency can be achieved while the decay factor is 0.99, and declines with the lower setting of the decay factor. However, the further examine of the statistic significant difference shows that under the 1% significant level, there are no significant differences between the hedging performances based on various settings of the decay factor. This implies that the determined decay factors do not influence the hedging performance.