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Research On Optimize Hedge Ratio Model

Posted on:2008-01-22Degree:MasterType:Thesis
Country:ChinaCandidate:C L DuFull Text:PDF
GTID:2189360215455416Subject:Quantitative Economics
Abstract/Summary:PDF Full Text Request
The key issue of futures markets is the determination of hedge ratio. The research of the hedge model is essential for the hedger and is a key issue of futures markets. Through hedge model to determine the optimize hedge ratio can improve the hedge efficiency and effectively averse the risk of spot markets.There are six chapters in this paper. The first chapter is about the significant of the research, present research review, frame of the paper and main content. The second chapter show what is,why and how to hedge in order to reduce the risk ,and present theory and model of futures hedging. In the third chapter, we build a single MV futures hedging model on base of ordinary least square method. In the fourth chapter, we build a single MV futures hedging model on base of multiple garch model, and in chapter five, we build it through copula-garch method. In chapter six we show the efficiency of copula-garch compare with other model. The final chapter is the conclusion. The main works of the paper are shown as follows.(1) We build a single MV futures hedging model on base of CopulaOn the base of minimum variance hedge ratio, this paper put forward principle of nonlinear matching of futures and cashes, and the one of return variance anticipation, using Copula model to calculate the nonlinear correlation, and using GARCH model to anticipate the standard deviation of futures'and cashes'return rate, so the hedge efficiency will be enhanced. Empirical test shows that, the efficiency of this model is higher than present ones. Using this paper's model to hedge can effectively averse cash risk.(2)We extend the constant correlation copula to time varying copula in this paper, and empirical test show that the time-varying copula makes the hedging model more efficiency.
Keywords/Search Tags:Hedge, Nonlinear correlation, Conditional covariance, Multiple GARCH, Copula
PDF Full Text Request
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