【作者】 张帆；

【导师】 瞿慧；

【作者基本信息】 南京大学 ， 管理科学与工程， 2013， 硕士

【摘要】 随着金融市场的不断发展和完善,对金融市场的研究和探索也越发深入。其中对于金融市场中各类金融产品的波动率的研究在金融市场研究中占据着重要的地位。资产配置,套期保值,风险管理都无疑涉及到对波动率的把握和控制。近几年来,凭借着计算机技术突飞猛进的发展,高频交易数据获得越来越方便,而基于高频数据的己实现波动率的研究也越来越受到人们的重视,成为波动率研究中一个重要的方向。目前,将已实现波动率运用到中国金融市场中对我国金融市场的风险监管以及金融市场的建立和发展中的很多基础性问题的解决都具有非常重要的理论和现实意义。本文主要是通过金融实证的方法,在分析总结其他研究者研究成果和经验的基础上,结合我国目前股票交易市场的特点,利用沪深300指数的高频数据建立HAR模型,以实证的方式研究中国股票交易市场的异质性。在模型中,我们考察了短期,中期和长期交易者在效益中产生的波动率对中国股票市场整体收益率波动的影响。同时对于原有的HAR的改进一般是引入GARCH模型消除残差的异方差性,而在本文中我们提出了另种方法,及在原有的HAR模型中加入状态转移机制,提高原模型对现实数据的拟合程度和解释作用。并用实证的方法证明该方法的可行性。对实证结果进行分析后我们认为得到的改进后的H A R模型具有更好的解释作用。以日,周和月为状态量的改进后HAR模型的拟合优度均大于原有的H A R模型。同时我们还发现以日收益率分析市场行情走势的角度来说,市场的短期波动总是短期,中期,长期交易者产生的市场波动和市场中因重大信息或是其他因素引起的短期跳跃共同作用的结果；但是对于以周收益率和月收益率考察市场行情走势时,在市场行情上扬和行情低迷时,市场的短期波动总是短期,中期,长期交易者产生的市场波动发挥的作用却是不同的；而短期市场外部因素对市场波动不一定会有作用,这取决于市场行情的好坏。更多还原

【Abstract】 With the development and improvement of the financial markets, research and exploration of the financial markets become more and more deeply. The research on volatility is play an important role of the financial market’s study. Asset allocation, hedging and risk management are undoubtedly related to the volatility. With the rapid development of computer technology, the high-frequency trading data get more convenient. The researchers have been paid to become an important attention to th realized volatility which based on high-frequency data, and it become a great direct to the estimate way of volatility.In this paper, by the financial empirical methods, analyzed and summarized the results and experiences of other researchers have studied, incorporated the characteristics of the stock market, we build a HAR model based on the high-frequency data in the CSI300Index to study the heterogeneity of the Chinese stock market. In the model, we consider the influence of the volatility which created by the short-term, medium-term and long-term traders’trading behavior to the the volatility of the whole stock market. Furthermore, we improve the original HAR model by introduce a mechanism of state transition to eliminate the residual heteroscedasticity, which is different from general way that incorporate a GARCH model with the HAR model. This method could improve Improve the interpretation of the role of the model, which has been proved in this paper.Analysis of the empirical results, we believe that the improved HAR model has a better explanation to the volatility of the whole stock market. The empirical results of the improved HAR model in which regard the day, weekly and monthly yield as the amount of state is better than the original HAR model get. We also found that in the situation of day yield, the volatility of whole market is caused by the trading behavior of the short-term, medium-term and long-term traders and the short-term jump caused by the material information or other factors. But in the situation of weekly and monthly, the influence degree of short-term, medium-term, long-term traders’trading behavior to the market volatility is dependent on the market trends. And the short-term market fluctuations of external factors on the market might not be available, which is also decided by the market trends.更多还原