股指期货的最优套期保值比率及投资组合研究

发布时间：2018-05-03 12:12

本文选题：股指期货 + 最优套期保值比率　；参考：《天津财经大学》2013年硕士论文

【摘要】：2008年全球金融危机过后,我国沪深两市股票市场的一个显著的特点就是股市的系统风险增大,股票市场投资者急切需要一种新的金融衍生工具用于规避股市系统风险。2010年4月16日,沪深300股指期货合约在上海金融期货交易所挂牌上市,弥补了我国股指期货的市场空白,同时也为沪深两市的股票投资者提供了一种新的有效的风险规避工具。股指期货的风险规避功能是通过套期保值策略实现的,投资者利用股指期货对股票现货投资组合进行套期保值,可以达到防范股市的系统风险,减少投资损失的目的。利用股指期货合约进行套期保值,其中核心的问题在于如何选择最优的套期保值比率,因此文章从如何选择最优的套期保值比率这个角度展开研究,这也是文章的研究目的和意义所在。文章选取沪深300指数样本股权重排名前50名的股票作为备选样本股,并以样本股的收益率与沪深300股指期货收益率的相关系数大于0.5为准则选择个股,并构建股票现货投资组合。在建立已有的股票现货投资组合基础上,分别从静态和动态的两个角度来研究最优套期保值比率。研究静态最优套期保值比率采用的方法是OLS模型、B-VAR模型、VECM模型；研究动态最优套期保值比率采用的方法是VECH-GARCH模型、BEKK-MGARCH模型、CCC-MGARCH模型、DCC-MGARCH模型。实际研究过程中由于不同估计方法得出的套期保值比率往往不一致,因此需要比较和评价各套期保值比率的套期保值绩效,并选择套期保值绩效最优的套期保值比率进行套期保值。文章分别从风险降低角度与效用最大化角度比较各套期保值比率的套期保值绩效。风险降低衡量指标是HE测度指标,效用最大化衡量指标是Sharp Ratio测度指标。在比较动态套期保值比率的套期保值绩效时,我们在Sharp Ratio测度指标中加入了动态调整成本变动对套期保值绩效的影响。比较结果显示：动态模型估计出的套期保值比率的套期保值绩效要优于静态套期保值估计模型,而加入动态调整成本因素的影响的Sharp Ratio指标更加符合实际,对套期保值投资者更有实际的指导意义。
[Abstract]:After the 2008 global financial crisis, one of the notable features of the stock market in China's Shanghai and Shenzhen stock markets is the increased systemic risk in the stock market. Investors in the stock market urgently need a new financial derivative to avoid the risk of the stock market system. On April 16, 2010, the CSI 300 Stock Index Futures contract was listed on the Shanghai Financial Futures Exchange, which made up for the gap in the stock index futures market in China. At the same time, it also provides a new effective risk-aversion tool for stock investors in Shanghai and Shenzhen stock markets. The function of risk aversion of stock index futures is realized by hedging strategy. Investors can use stock index futures to hedge stock spot portfolio, which can prevent the systematic risk of stock market and reduce the investment loss. How to choose the best hedge ratio is the core problem of using stock index futures contract, so this paper studies how to choose the optimal hedge ratio. This is also the purpose and significance of the article. This paper selects the top 50 stocks in the Shanghai and Shenzhen 300 index as the alternative sample stocks, and selects the stocks with the correlation coefficient greater than 0.5 between the yield of the sample stock and the return rate of the Shanghai and Shenzhen 300 stock index futures. And build stock spot investment portfolio. Based on the existing stock spot portfolio, the optimal hedging ratio is studied from the static and dynamic perspectives. The method to study the static optimal hedging ratio is OLS model / B-VAR model / VECM model, and the dynamic optimal hedging ratio method is VECH-GARCH model / CCC-MGARCH model / DCC-MGARCH model. In the actual research process, because the hedge ratio obtained by different estimation methods is often inconsistent, it is necessary to compare and evaluate the hedging performance of each hedge ratio. And select the best hedge performance hedge ratio to hedge. This paper compares the hedge performance of each hedge ratio from the angle of risk reduction and utility maximization. The risk reduction measure index is HE measure index, the utility maximization measure index is Sharp Ratio measure index. When comparing the hedge performance of the dynamic hedging ratio, we add the effect of the dynamic adjustment cost change to the hedging performance in the Sharp Ratio measure index. The results show that the hedge performance of the dynamic model is better than that of the static model, and the Sharp Ratio index with the effect of dynamic adjustment cost is more realistic. To hedge investors more practical guidance.
【学位授予单位】：天津财经大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F832.51;F224

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