【作者】 王宜峰；

【导师】 王春发；

【作者基本信息】 浙江财经学院 ， 金融学， 2012， 硕士

【摘要】 在全球经济一体化过程中,国内企业的生产经营活动日益受到国际市场上原材料与商品价格的影响,尤其在08年国际金融危机爆发之后,国内企业面临着巨大的商品价格波动风险,国内企业纷纷寻找办法分散价格风险,从近几年的国内企业调查看来,原材料和产品的市场价格直接决定了企业的生存情况,所以规避价格风险是国内企业赖以生存前提。衍生品市场的发展为解决这一问题提供了有效方案,期货市场的一个重要功能是通过期货套期保值锁定商品价格,规避价格风险。本文研究的核心是利用期货合约的套期保值功能分散价格波动风险,文章旨在通过对比不同的套期保值模型,寻找最优套期保值率,提高期货套期保值的效果。目前研究套期保值策略主要是利用GARCH模型,但该模型存在了很大的问题,GARCH模型在刻画随机性上存在严重的不足。本文利用多元随机波动率模型(MSV模型)对套期保值进行研究,多元随机波动率模型是一类异方差模型,它将随机过程引入模型之中,能够比GARCH模型更好的反应金融市场波动的随机性,是刻画金融市场波动性的最理想的模型。本文首先利用固定相关系数多元随机波动率模型(CC-MSV)建立基于CC-MSV的风险最小套期保值模型来研究最优套期保值率。然后在CC-MSV模型的基础上上引入动态相关模型和t分布,建立基于厚尾的动态相关系数多元随机波动率模型(DC-t-MSV)的方差最小套期保值模型,该模型考虑了金融数据的尖峰厚尾的特点以及现货与期货的对数收益率的相关系数之间的局部相关性,更加符合金融时间序列的特点。最后,由于金融市场具有一定的脆弱性,容易受到类似于经济危机、自然灾害、经济政策变化等外部突发事件的影响,所以本文基于DC-t-MSV模型,引入了马尔科夫转换机制(regime-switching)来表示突发状况对期货市场的影响,建立了基于马尔科夫状态转换下厚尾的动态相关系数多元随机波动率模型(RSDC-t-MSV)的方差最小套期保值模型,RSDC-t-MSV模型及考虑了金融数据的内部特征又考虑了外部突发事件对金融市场的影响,符合金融市场的实际情况。文章的实证部分以2008年1月10日到2011年6月30日的黄金期货与现货价格的对数收益率数据为研究对象,利用该数据分别对CC-MSV模型、DC-t-MSV模型、RSDC-t-MSV模型在套期保值领域的应用加以研究,利用套期保值测度公式对比这三种模型的套期保值效果。实证研究中首先利用Eviews5.0对数据的统计特征加以分析,然后利用winbugs软件对模型进行编程运算。文章的参数估计部分采用MCMC方法中的切片抽样技术,该技术与Gibbs抽样相比能够有效的所点参数估计所需要的时间。通过对黄金期货套期保值效率的实证分析得到了理想的结论。三种模型所得到的最优套期保值率都是动态的,都取得了满意的套期保值效果,但是经过对比分析表明:利用RSDC-t-MSV模型计算最优套期保值率既能捕捉到市场的剧烈波动,又能保证套期保值率的稳定性,与DC-t-MSV模型和CC-MSV模型相比具有很大的优势。从套期保值效果看,RSDC-t-MSV模型能更大程度的降低黄金期货与现货的资产组合投资的风险,它的套期保值效果优于DC-t-MSV模型和CC-MSV模型。因此,可以认为利用RSDC-t-MSV模型进行套期保值能够更好的规避价格风险。文章实证分析的结论与理论分析完全吻合。更多还原

【Abstract】 In the process of global economic integration, the domestic enterprise’s production and operating activities increasingly influenced by the price of international market raw material and commodity, especially in the 08 years after the outbreak of the financial crisis in domestic enterprises are facing tremendous commodity price risk. Especially after the outbreak of the international financial crisis in 2008, domestic enterprises are facing a huge risk of commodity price fluctuations. The companies are looking for ways to disperse the price risk. The market price of raw materials and products determine the enterprise’s survival directly, so to avoid price risk is the prerequisite for the survival and development of domestic enterprises. The derivatives markets provide an effective solution to this program; an important function of futures market is locking the commodity prices and avoiding price risk through the futures hedge. The core of this study is using the function of hedge of futures contracts to spread the risk of price volatility. The article aims to compare among the different hedging models, find out the optimal hedge ratio and increase the effect of futures hedging.Current research of hedging strategy is based on GARCH model, but this model has a big problem, this model has serious shortcomings in characterize randomness. In this paper, we adopt multivariate stochastic volatility model (MSV model) to study hedge, multiple stochastic volatility model is a class of heteroscedastic models, and it introduced stochastic process into the model. Compared with GARCH, it will be better to reflect than the randomness of financial markets. It is the optimal models to depict financial market volatility.In this paper, firstly, we build minimum variance hedge model with CC-MSV model to study the optimal hedge ratio. Then based on CC-MSV model, we introduce dynamic correlation model and multivariate t-distribution. This new model is named DC-t-MSV. The model has considered the peak and fat-tail characteristics of financial data as well as the local correlation of the correlation coefficient between the spot and futures’logarithmic returns, which is more in line with the characteristics of financial time series. Finally, because of the vulnerability of financial market, the develop of financial market will suffered from unexpected events ,such as economic crises, natural disasters, changes in external economic policy and so on. So based on DC-t-MSV model, the article introduce Markov regime switching (regime -switching) to build the RSDC-t-MSV minimum variance hedge model to represent the sudden impact on the futures market. RSDC-t-MSV model has considered both the internal features of the financial data and external contingencies. It is consistent with the actual situation of financial markets.In the empirical part, the article uses logarithmic return of gold’s spot and future price from January 10, 2008 to June 30, 2011 to do empirical research. The data are used for CC-MSV model, DC-t-MSV model and RSDC-t-MSV model to study on hedging; it also uses hedging measure formula to compare the hedging effect based on the three different models. During the empirical research, we begin with the use of Eviews5.0 to analyze the statistical characteristics of data, and then use winbugs to compute the model. In the part of Parameter estimation, the article applies slice sampling techniques of MCMC methods. This technology can be more effective compared with the Gibbs sampling.The empirical analysis of gold futures hedging efficiency has come to the desirable conclusion. Three models have obtained the dynamic optimal hedge ratio. All of them have achieved a satisfactory effect of hedging. However, comparative analysis shows that the optimal hedge ratio calculated by the RSDC-t-MSV model not only can capture the market volatility, but also ensure the stability of the hedge rate. It has great advantage compared with DC-t-MSV model and CC-MSV model. From the side of hedge effort, RSDC-t-MSV model can achieve a greater degree of reduction of the portfolio investment risk. It can do well in hedge than CC-MSV model and DC-t-MSV model. Therefore, we can consider that the use of RSDC-t-MSV model can do better in the area of hedge. The empirical analysis is fully consistent with the theoretical analysis.更多还原