Optimal Hedge Ratio of Commodity Futures Using Bivariate DCC-CARR and DCC-GARCH Models

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 ana...

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Bibliographic Details
Main Authors: Nash Chen, 陳昱宏
Other Authors: Gang Shyy
Format: Others
Language:en_US
Published: 2005
Online Access:http://ndltd.ncl.edu.tw/handle/83027752092707981578
Description
Summary: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.