BARRA模型对国内ETF市场业绩的归因分析

发布时间：2018-02-21 09:56

本文关键词： BARRA模型 ETF 归因分析风险预测　出处：《首都经济贸易大学》2014年硕士论文　论文类型：学位论文

【摘要】：ETF (Exchange Trade Fund),中文名为交易所交易基金,1993年自美国诞生,随后逐步在全球金融市场蔓延开来,经过20多年的发展,截止到2013年年底,全球的ETF规模已经达到了2.387万亿美元,占比达到了全球基金市场(剔除货币和FOF)规模的10%,ETF已成为基金市场不可或缺的组成部分。华夏上证50ETF-国内首只ETF,自2004年开始在上海证券交易所上市交易,经过9年多的发展,截至2013年底,上交所共发行了48只ETF,市值达到1100亿,交易额超过6200亿,覆盖范围包括股票、债券、商品、货币等。本文根据BARRA模型的研究理念以及联系国内ETF市场的现状,并且在基于对A股市场数据的长期分析和风险特性的数量化筛选的条件下,共选取了31个风格因子和26个行业因子共57公共因子,涵盖了从各个维度衡量的个股风险和收益的相关情况。通过聚类分析和主成份分析并进行降维处理以后最终选出12个行业因子和10个风格因子来对于国内ETF市场的收益情况进行归因研究以及对其风险波动情况进行解释。文章选取上证50ETF和创业ETF作为研究实例来对ETF的市场业绩进行分析,并且利用银河99基金来研究ETF的波动性。首先求出22个公共因子对于个股的因子报酬,然后利用50ETF的超额收益和22个公共因子的因子报酬进行时间序列回归,得出共有18个公共因子对50ETF有影响。同理对创业ETF进行分析,由于创业ETF成立时间短,在进行SPSS分析时采用Backward法,共有16个公共因子进入模型,通过检验最终得出只有8个公共因子对创业ETF的收益会产生影响。另外,通过对公共因子的波动性进行研究,发现公共因子的风险波动率走势与银河99基金市场的风险波动率走势基本一致。
[Abstract]:ETF exchange Trade fund, named Exchange Trade Fund in Chinese, was born from the United States in 1993, and then gradually spread in the global financial market. After more than 20 years of development, by the end of 2013, the global ETF scale had reached two tillion three hundred and eighty-seven billion US dollars. The 10 ETFs, which have reached the size of the global fund market (excluding currencies and FOFs), have become an integral part of the fund market. China Shanghai 50ETF- the first ETF in China, has been listed and traded on the Shanghai Stock Exchange since 2004, after more than nine years of development. By end of 2013, 48 ETFs had been issued on the Shanghai Stock Exchange, with market value reaching 110 billion and trading more than 620 billion, covering stocks, bonds, commodities and currencies. According to the research idea of BARRA model and the current situation of domestic ETF market, and based on the long-term analysis of A-share market data and quantitative screening of risk characteristics, A total of 31 style factors and 26 industry factors were selected and 57 common factors were selected. Through cluster analysis and principal component analysis and dimensionality reduction, 12 industry factors and 10 style factors are selected for the domestic ETF market. The return of the attribution study and its risk volatility to explain. This paper selects Shanghai 50 ETF and entrepreneurial ETF as research examples to analyze the market performance of ETF, and uses Yinhe 99 Fund to study the volatility of ETF. Then using the excess returns of 50 ETFs and the factor returns of 22 public factors for time series regression, it is concluded that 18 public factors have influence on 50 ETFs. In the analysis of SPSS, the Backward method is used. There are 16 public factors entering the model. Finally, only 8 public factors have an impact on the income of entrepreneurial ETF. In addition, the volatility of public factors is studied. It is found that the trend of risk volatility of common factors is basically consistent with that of Yinhe 99 fund market.
【学位授予单位】：首都经济贸易大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F832.51;F224

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