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双语推荐：套期保值比率

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基于沪深300股指期货真实交易数据,选取对指数拟合程度高且可交易的沪深300ETF为现货研究对象,运用静态套期保值比率估计模型(OLS、B-VAR、VECM)和动态套期保值比率估计模型(VECMBGARCH、DBEKK-GARCH、DCC-GARCH、NormCopula-GARCH、tCopula-GARCH)对最优套期保值比率进行估计,并对规避风险效果进行比较。结果表明:无论在样本内期间和样本外期间中,各模型反映出的沪深300股指期货套期保值效率都较高,考虑期货与现货市场动态相关性的NormCopula-GARCH模型套期保值效果最优。
This paper selected CSI 300ETF which can fit CSI 300 index better and tradable as a spot research object,used the static hedging ratio estimation model (OLS,B-VAR,VECM)and the dynamic hedging ratio estimation model (VECM-BGARCH,DBEKK-GARCH,DCC-GARCH,Norm Copula-GARCH,tCopula-GARCH)to estimate the optimal hedging ratio based on actual transaction data of CSI 300 stock index futures.Furthermore,the hedging effectiveness of different models was tested and compared.The results showed that:both in the sample and out-sample period,the hedging effect by using CSI 300 index futures was good for each model.NormCopula-GARCH model that considering the dynamic correlation of futures and spot market has advantage of existing hedging ratio estimation models,it provides reference in the risk aversion for investors.

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期货市场最重要的功能是套期保值,它是大宗商品交易者规避价格风险的一个重要途径。文章基于我国铜期货市场的套期保值现状和相关理论,用误差修正模型对铜期货的套期保值比率进行了实证分析,研究结果发现沪铜期货价格和现货价格为一阶平稳序列并存在协整关系,利用误差修正模型计算出来的套期保值比率不为1。
The most important function of the futures market is hedging, and it is an important way to commodity traders avoiding the price risk. Firstly this paper introduces the main theoretical development and hedging of Chinese copper futures market, and then makes empirical analysis about hedging ratio by error correction model. And it’s found that the copper futures price and spot price as a first-or-der stationary and cointegration relationship, and the hedge ratio counted by error correction model is not “1”.

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为了进一步便于线缆企业原材料采购风险控制工作的开展，在介绍套期保值相关概念和套期保值比率的相关计算方法的基础上，从技术层面，利用 Excel VBA 技术实现了套保比率的自动计算，给出了相关编程代码及数据应用实例，为线缆企业开展套期保值工作以控制原材料采购风险提供了一个切实可行的工作思路。
In order to make the risk control of Cable Company’s raw material purchase much easier in the day -to -day work,this article introduces the related concepts and methods of Hedging.Meanwhile,through the related programming code and date application,it applies Excel VBA method to make the Hedge Ratio calculate automatically from a technical perspective as a useful working method.

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随机的碳排放价格变化直接导致资产组合的投资风险加剧,影响碳排放现货与期货资产的投资组合策略。依靠商品期货价格的期限结构,本文提出了一种新的在便利收益下动态套期保值比率及其套期保值效果评价方法。动态套期保值比率是由现货和便利收益的波动率、协方差及其相关系数、距离到期日时间、便利收益均值回复速度等参数存在紧密关联性。为了有效地规避碳排放现货价格剧烈波动所引发的市场风险,市场参与者利用便利收益的历史信息优化调整期货与现货的对冲比例,确定最优化的套期保值比率,可以有效规避现货资产的市场风险,实现资产投资组合最佳的投资收益。
Stochastic price change of carbon emissions directly determines drastic investment risks of assets portfolio , and affects portfolio policy between spot and futures of carbon emissions. Based on term structure of the commodity futures price , the paper proposes a newly estimating method to determine dynamic hedge ratios and hedging effectiveness under the stochastic conve-nience yields. Dynamic hedge ratios exhibit close correlation with the parameters of volatility , covariance and correlation both spot and convenience yields, the time to maturity, the mean-reverting speed of convenience yields. Market participants can establish dynamic hedge ratios using the term structure parameters of carbon emissions price , real-timely optimize and adjust portfolio size between spot and futures with different maturities for carbon emissions. Compared with unhedged effectiveness of carbon emissions assets, hedging returns variance of carbon emissions assets exhibit a significantly inclining trend

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铜期货已经成为铜行业上中下游企业不可或缺的定价和风险管理工具,越来越多铜企业参与到了铜期货套期保值中。然而期货价格与现货价格并非平行运动,即它们之间的价格变动不完全一致,因此,套期保值的关键在于套期保值比率的确定。本文从上海期交所选取了490个期货和现货数据进行探讨与研究,主要运用OLS模型、EMC模型对套期保值进行估算,并对估算结果进行了分析。
Copper futures have become indispensable pricing and risk management tools for copper industry upstream and downstream enterprises. A growing number of copper enterprises have participated in copper futures hedging. However, the futures'' price and spot price are not in parallel motion, i.e. the price changes between them are not completely consistent. Therefore, the key of hedging is the determination of its ratio. The article explores and researches 490 futures and spot data from the Shanghai Futures Exchange, estimates the hedging by using OLS model and EMC model, and finally analyzes the estimation results.

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对棉农而言，国内现有关于棉花期货最优套保比率的研究存在明显不足。文章分别用OLS与ECM方法估计了不同套保期限下棉花期货最优套保比率，结果显示两种方法得到的最优套保比率和套保效果相差极小，而不同套保期限的套保效果却显著不同：套保期限越长，最优套保比率就越大，套保效果也越好。故对棉农而言，在棉花种植时即进行套期保值能更好地对冲风险；此外，随着棉花期货市场的发展，套保的有效性会不断增强，棉农运用期货能更好地规避价格风险。
Cotton futures is an important tool to avoid the risk of cotton price fluctuation for the cotton farmer, but there is an obviously deficiency in the domestic study of the optimal hedging ratios of cotton futures: none of the studies provided a simple and operable hedging project for the cotton famer. This paper estimates the optimal hedging ratios of cotton futures by applying OLS and ECM methods. The results show that the difference between the two estimations is small, but the difference between the estimation in different hedging term is big: the longer the hedge term is, the bigger the hedge ratio is, and the better the hedging performance is. For the cotton farmer, more risks can be reduced if he undertakes the hedging when the cotton is planted in spring. With the development of cotton future market, hedge will become more and more effective.

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文章采用OLS、ECM、CCC-BGARCH以及DCC-BGARCH模型分别计算了两支300ETF的最优套期保值比率，并分别比较了两支300ETF的套期保值效果，结果发现：动态多元GARCH类模型的效果明显好于OLS和ECM模型；无论采用哪种模型，华泰柏瑞沪深300ETF的套期保值效果都要好于嘉实沪深300ETF；由于华泰柏瑞沪深300ETF的高流动性和相对完善的套利机制，使得其适合较大方差变化的DCC-BGARCH模型；而嘉实沪深300ETF采用CCC-BGARCH模型的套期保值效果更好，这可能是因为嘉实沪深300ETF和沪深300股指期货间的关联性波动较小，相关系数更接近于常数的缘故。
This article uses models of OLS、ECM、CCC-BGARCH and DCC-BGARCH,calculates the opti-mal hedge ratio of the two CSI 300 ETF,and compares the hedging effects of the two CSI 300 ETF. The research in-dicates that the effect of dynamic multivariate GARCH model is significantly detter than the effect of OLS and ECM model. Whichever model,the hedging effect of Huatai-PineBridge CSI 300 ETF is detter than the effect of Harvest CSI 300 ETF. Due to its high liquidity and relatively well -developed arditrage mechanism,Huatai -PineBridge CSI 300 ETF is more suitadle for DCC-BGARCH model which has larger variance changes. Meanwhile,Harvest CSI 300 ETF is more suitadle for CCC-BGARCH model decause the relevance fluctuations detween the two ETF in futures is small and the correlation coefficient is closer to constant.

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