【作者】 杨明；

【导师】 黄炜；

【作者基本信息】 浙江大学 ， 概率论与数理统计， 2016， 硕士

【摘要】 2015年我国股市的跌宕起伏牵动着几亿股民的市场投资,证券市场投资者偏好中小市值个股,一方面风险投资带来高回报；另一方面中小板、创业板个股市场波动幅度大,市场风险很高。基于中证500的股指期货套期保值工具能够有效规避市场风险,本文的核心在于研究中证500股指期货,确定最优套期保值比率。基于该研究课题,本文首先回顾了国内外股指期货套期保值工具的相关研究,发现传统的风险最小化套期保值模型、效用最大化模型在实际应用中都存在不同程度的缺陷。在重新梳理了股指期货套期保值相关概念基础上,本文提出了将择时因子引入动态的GARCH(1,1)套保模型来提高最优套期保值比率。基于择时因子的GARCH(1,1)套期保值模型本质上是一种阶段性套期保值策略,投资者可在中证500指数下跌时进行套保,在中证500指数上涨时放弃套保,既降低了套期保值择时的难度,又可以提高套期保值的效率。本文通过Ifind金融数据终端,选取了中证500股指期货、中证500ETF上市一年以来的日线收益率及15分钟收益率数据,运用R和Eviews软件,分别对OLS模型、GARCH(1,1)模型以及加入择时因子的GARCH(1,1)模型进行实证研究分析。结果表明,本研究所构建的加入择时策略因子的GARCH(1,1)模型无论在日收益率还是更高频率的15分钟收益率序列中,均获得更好的最优套期保值比率。本文在风险最小化模型基础上增加择时因子来研究最优套期保值比率的变化情况为投资者提供了研究套期保值模型的新思路。与此同时,本文对中证500股指期货不同套期保值模型的实证分析结果,可为机构投资者以及高频交易者套期保值过程中提供参考。更多还原

【Abstract】 By 2015 the stock market had affected millions of investors. Chinese investors prefer small and medium-sized stocks. High-risk investment can bring higher return, meanwhile, the volatility of stocks in SME board and growth enterprise market is very high and the market risk is high. The stock index future based on CSI 500 can act as an effective risk hedging tool. This paper aimed at figuring out the optimal hedge ratio based on the study of CSI 500 stock index future.Firstly, this paper reviewed the relevant research and basic concepts about stock index futures hedging instruments. We found there exist various practical application limits in both the traditional minimum risk hedging model and utility maximization model. After summarizing the relevant concepts about stock index future heding, this paper introduced the dynamic timing GARCH (1,1) model to improve the optimal hedge ratio. GARCH (1,1) model based on timing strategy of hedging is essentially a periodic hedging strategy, investors could start hedging when the CSI 500 index falls down, and stop hedging when this index rises up. It not only decreases the difficulty of market timing in hedging, but also can improve the efficiency of hedging.We collected the CSI 500 stock index futures and CSI 500 ETF data including daily returns and 15 min’ returns since last year through Royal Flush Ifind financial database. Using R and Eviews, this paper respectively analyzed the OLS model, GARCH (1,1) model and GARCH (1,1) model based on timing strategy. The results showed that the GARCH (1,1) model based on timing strategy we built, obtained a better optimal hedge ratio in both series of the 15 min’ returns and daily returns.The results of this paper can provide a new way to study the hedging model for investors. Meanwhile, the empirical results of this paper about different CSI 500 heding models are great references for institutional investors and high-frequency traders.更多还原