我国黄金期货市场套期保值绩效实证研究

发布时间：2018-01-28 21:02

本文关键词： 套期保值套期保值绩效 OLS模型 GARCH模型　出处：《广西师范大学》2017年硕士论文　论文类型：学位论文

【摘要】：黄金作为重要的金融资产之一,被广大的投资者热爱,由于其具有的良好的物理特性,在人们的日常生活和生产中被广泛的利用。而面对跌宕起伏犹如过山车似的黄金价格,我国的黄金生产消费企业和众多的投资者迫切需求金融工具来规避这一风险。2008年1月9日,在我国上海期货交易所黄金期货开始挂牌交易,给期盼已久的投资者带来了规避风险的途径。套期保值作为风险规避重要的手段,颇受广大投资者和企业的青睐。近些年来对我国黄金期货市场套期保值绩效研究也层出不穷。2013年7月5日,黄金期货市场夜盘的推出,黄金期货市场进入到了“夜盘时代”,把交易时间由原来的每周一至周五的北京时间9:00-11:30,13:30-15:00,延伸到每周一至周五的北京时间9:00-11:30,13:30-15:00,21:00至次日2:30。随着交易时间的改变黄金期货的日交易量,波动变化幅度等都有明显的变化。本文是在这个基础上,分别运用静态的套期保值模型最小二乘法OLS、双变量向量自回归VAR、误差修正ECM模型、广义自回归条件异方差GARCH模型、ECM-GARCH模型以及二元GARCH模型进行研究。通过对黄金夜盘推出前2009.9-2013.7和夜盘推出后2013.7-2017.2两组数据实证检验,笔者计算出我国黄金期货市场上的套期保值比率,并依托于套期保值比率的研究进行套期保值效率的检验和比对分析。从六种模型的绩效结果看,夜盘前六种模型的绩效都在0.81左右,夜盘后六种模型的绩效都在0.76左右。无论夜盘前还是夜盘后,六种模型都能有效的规避现货市场带来的风险。夜盘前的绩效值都大于夜盘后的绩效值,说明六种模型在夜盘前套期保值效果要好于夜盘后套期保值的效果。从夜盘前的绩效结果看,六种模型中OLS模型效果最好,二元GARCH模型效果最差。从夜盘后的绩效结果看,其中OLS模型最好,GARCH(1,1)模型最差。实证结果表明:无论夜盘前还是夜盘后,六种模型中都是OLS模型最好。相比于其他模型OLS模型操作起来简单方便,也不用像动态套期保值模型那样要经常变换套期保值比率,增加了交易成本。希望本研究能对我国的广大黄金投资者和黄金生产、消费企业能有所借鉴。
[Abstract]:As one of the important financial assets, gold is loved by the majority of investors because of its good physical characteristics. It is widely used in people's daily life and production. The price of gold is like a roller coaster in the face of ups and downs. Gold production and consumption enterprises and many investors in China urgently need financial instruments to avoid this risk. In January 9th 2008, gold futures began to be traded in Shanghai Futures Exchange. For long-awaited investors to bring a way to avoid risk. Hedging as an important means of risk aversion. In recent years, the research on hedging performance of gold futures market in China is also endless. In July 5th 2013, the launch of gold futures market night. The gold futures market has entered the "night-time era," trading time from the original Monday to Friday Beijing time from 9: 00-11: 30 30: 13: 30-15: 00. It extends to 9: 00-11: 30: 1330-15: 00 Beijing time every Monday to Friday, to 21: 00 to 2: 30 the next day. The daily trading volume of gold futures changes with the trading time. On this basis, we use the static hedging model least square method, bivariate vector autoregressive VARs, error correction ECM model. Generalized autoregressive conditional heteroscedasticity GARCH model. The ECM-GARCH model and the binary GARCH model were studied. Through the analysis of the two models before and after the launch of the Golden Night Disc, 2009.9-2013.7 and 2013.7-2017.2, respectively. Group data empirical test. The author calculates the hedge ratio in China's gold futures market, and relies on the study of hedging ratio to test and compare the hedging efficiency. The performance of the first six models is about 0.81, and the performance of the six models is about 0.76. The six models can effectively avoid the risk brought by the spot market. It shows that the six models have better hedging effect before and after the night disc. From the results of the performance before the night disc, the OLS model is the best. The effect of binary GARCH model is the worst. From the performance results after night disc, OLS model is the best one. The empirical results show that: before or after the night disc. Compared with other models, OLS model is simple and convenient to operate, and it does not need to change the hedge ratio as the dynamic hedging model. It is hoped that this study can be used as a reference for gold investors and gold production in China.
【学位授予单位】：广西师范大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F832.54;F724.5

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