中国股市波动问题研究
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摘要
以资本资产定价模型、套利定价、BS期权定价公式为代表的现代金融理论研究中,波动率作为特定投资组合的风险度量指标,直接影响着风险定价、风险管理以及资产配置。投资者要利用金融工具对其风险进行控制和管理,并进行一定的投资组合,必须首先研究波动率自身的性质,在此基础上对资产收益的波动率建立模型,并从中发现波动规律和探讨波动过程中的诸多影响因素,这样才能提高整个市场中的资产配置效率,降低经济运行成本。
本文在随机波动率模型框架下,以问题为导向,研究中国股市的波动问题,重点研究了以下几个方面：
(1)针对中国股市波动中存在的非对称性效应,运用带杠杆效应的ASVDJ模型研究了上证综指和深圳成指受好坏消息冲击时对波动的影响差异,并用基于Gibbs抽样的MCMC算法对模型进行参数估计。在将研究期数据划分不同态势以及不同阶段的实证中,证实上海和深圳股市在整个过程中,牛市阶段“坏消息”引发的波动更大、熊市阶段“好消息”引发的波动更大,此发现不同于股票市场上普遍认为的“杠杆效应”的结论。若把整个熊市阶段细分为前期、中期、后期等三个不同时期,则发现在熊市中期发生明显的“杠杆效应”,前期和后期则发生反向的“杠杆效应”。文中对此类异常的“杠杆效应”从行为金融学的角度进行了解释。
(2)在格兰杰因果多变量随机波动率模型(GC-MSV)基础之上引入改进的双向GC-MSV模型(Bidirectional GC-MSV)即在多变量随机波动率模型中,考虑股指期货波动性与现货市场波动性之间的双向因果关系,利用日内15分钟间隔的沪深300股指期货和现货指数数据来实证分析股指期货推出对股市波动性的影响。实证结果表明在我国股指期货推出以来,在股指期货市场和现货市场之间确实存在着显著的双向的波动溢出,沪深300IF价格波动是现货价格波动(包括沪深300、上证综指以及深圳成指)的Granger原因,现货价格波动也是期货价格波动的Granger原因,而期货引起的现货市场波动性更大。
(3)对易志高、茅宁等人编制的投资者情绪指数提出改进,以投资者信心指数代替消费者信心指数,并去掉争议较大的封闭式基金折价作为代理变量,利用主成分分析法重新编制适合的投资者情绪指数,结合当前国内市场银行、房地产、有色金属、电子信息等19个行业板块指数,构建时间序列的个体固定效应模型,得出了投资者情绪对不同行业板块波动的影响,其中情绪对有色金属、电子信息、房地产、机械、银行等行业影响较大,而对运输物流、供水供气、汽车、医药等行业影响不太明显。
The capital asset pricing model, arbitrage pricing, BS option pricing formula are the representative of modern financial theory. As a specific measurement indicator of portfolio, volatility directly affects risk pricing, risk management and asset allocation. Using financial tools to control and manage their risk and decide portfolio, investors must first examine the feature of volatility and establish volatility model to find law, so as to improve the the efficiency of asset allocation in overall market, and reduce the cost of economic operation.
This paper studies the volatility of Chinese stock market as the research object and focus on the following issues:
According to the existence of leverage in Chinese stock market, this paper use the asymmetric SV model with double jump on the Shanghai and Shenzhen Composite Index to study the impact of good or bad news on the fluctuations and use MCMC algorithm based on Gibbs sampling for parameter estimation. In the research, from division of the data situation and the different stages of different empirical process, we can confirm that during the Shanghai and Shenzhen stock markets in the whole process, in the bull market phase, "bad news" cause greater fluctuations, while in the bear market phase, the "good news" lead to greater volatility. This finding is different from the stock market research widely recognized "leverage effect". If the bear market phase of the whole divided into early, middle, end stage in three different periods, reverse "leverage effect" were found to occur significantly in the early and late term bear market. This paper explained the leverage effect from the aspect of behavioral finance.
It proposes improved bidirectional GC-MSV, considering the volatility and stock index futures stock market volatility and using 15-minute intervals data of Shanghai and Shenzhen 300 stock index futures for empirical analysis. The empirical results show that the introduction of stock index futures in China since the stock index futures market and spot market does exist between the significant two-way volatility spillover, Shanghai and Shenzhen 300IF price fluctuations in spot price volatility of the Granger causes the spot price volatility is Granger caused by futures price volatility, and futures cause more volatile than spot market.
This paper improves the sentiment index made by Yi Zhigao and Mao Ning and uses behavioral finance theories and methods to work out the investor sentiment index. It is based on the composite index of investor sentiment to study the sector plates of different fluctuations. Based on SV-t model and according to nineteen industries index, it turns out that investors'sentiment influence differently on industries, in which emotion on non-ferrous metals, electronic information, real estate, machinery, banking and other industries is obvious, but on the automotive, pharmaceutical and other industries is not obvious.
本文在随机波动率模型框架下,以问题为导向,研究中国股市的波动问题,重点研究了以下几个方面：
(1)针对中国股市波动中存在的非对称性效应,运用带杠杆效应的ASVDJ模型研究了上证综指和深圳成指受好坏消息冲击时对波动的影响差异,并用基于Gibbs抽样的MCMC算法对模型进行参数估计。在将研究期数据划分不同态势以及不同阶段的实证中,证实上海和深圳股市在整个过程中,牛市阶段“坏消息”引发的波动更大、熊市阶段“好消息”引发的波动更大,此发现不同于股票市场上普遍认为的“杠杆效应”的结论。若把整个熊市阶段细分为前期、中期、后期等三个不同时期,则发现在熊市中期发生明显的“杠杆效应”,前期和后期则发生反向的“杠杆效应”。文中对此类异常的“杠杆效应”从行为金融学的角度进行了解释。
(2)在格兰杰因果多变量随机波动率模型(GC-MSV)基础之上引入改进的双向GC-MSV模型(Bidirectional GC-MSV)即在多变量随机波动率模型中,考虑股指期货波动性与现货市场波动性之间的双向因果关系,利用日内15分钟间隔的沪深300股指期货和现货指数数据来实证分析股指期货推出对股市波动性的影响。实证结果表明在我国股指期货推出以来,在股指期货市场和现货市场之间确实存在着显著的双向的波动溢出,沪深300IF价格波动是现货价格波动(包括沪深300、上证综指以及深圳成指)的Granger原因,现货价格波动也是期货价格波动的Granger原因,而期货引起的现货市场波动性更大。
(3)对易志高、茅宁等人编制的投资者情绪指数提出改进,以投资者信心指数代替消费者信心指数,并去掉争议较大的封闭式基金折价作为代理变量,利用主成分分析法重新编制适合的投资者情绪指数,结合当前国内市场银行、房地产、有色金属、电子信息等19个行业板块指数,构建时间序列的个体固定效应模型,得出了投资者情绪对不同行业板块波动的影响,其中情绪对有色金属、电子信息、房地产、机械、银行等行业影响较大,而对运输物流、供水供气、汽车、医药等行业影响不太明显。
The capital asset pricing model, arbitrage pricing, BS option pricing formula are the representative of modern financial theory. As a specific measurement indicator of portfolio, volatility directly affects risk pricing, risk management and asset allocation. Using financial tools to control and manage their risk and decide portfolio, investors must first examine the feature of volatility and establish volatility model to find law, so as to improve the the efficiency of asset allocation in overall market, and reduce the cost of economic operation.
This paper studies the volatility of Chinese stock market as the research object and focus on the following issues:
According to the existence of leverage in Chinese stock market, this paper use the asymmetric SV model with double jump on the Shanghai and Shenzhen Composite Index to study the impact of good or bad news on the fluctuations and use MCMC algorithm based on Gibbs sampling for parameter estimation. In the research, from division of the data situation and the different stages of different empirical process, we can confirm that during the Shanghai and Shenzhen stock markets in the whole process, in the bull market phase, "bad news" cause greater fluctuations, while in the bear market phase, the "good news" lead to greater volatility. This finding is different from the stock market research widely recognized "leverage effect". If the bear market phase of the whole divided into early, middle, end stage in three different periods, reverse "leverage effect" were found to occur significantly in the early and late term bear market. This paper explained the leverage effect from the aspect of behavioral finance.
It proposes improved bidirectional GC-MSV, considering the volatility and stock index futures stock market volatility and using 15-minute intervals data of Shanghai and Shenzhen 300 stock index futures for empirical analysis. The empirical results show that the introduction of stock index futures in China since the stock index futures market and spot market does exist between the significant two-way volatility spillover, Shanghai and Shenzhen 300IF price fluctuations in spot price volatility of the Granger causes the spot price volatility is Granger caused by futures price volatility, and futures cause more volatile than spot market.
This paper improves the sentiment index made by Yi Zhigao and Mao Ning and uses behavioral finance theories and methods to work out the investor sentiment index. It is based on the composite index of investor sentiment to study the sector plates of different fluctuations. Based on SV-t model and according to nineteen industries index, it turns out that investors'sentiment influence differently on industries, in which emotion on non-ferrous metals, electronic information, real estate, machinery, banking and other industries is obvious, but on the automotive, pharmaceutical and other industries is not obvious.
引文
①易志高、茅宁等最先结合Baker的综合指数编制法,对中国股市的投资者情绪指数进行编制,他们详细阐述了单个指标对情绪的测度,并采用新增开户数、IPO数量、IPO首日收益率、交易量、消费者信心指数、封闭式基金折价等作为情绪代理变量制定综合指数。但是,封闭式基金折价率能否反映情绪,在国内一直有较大的争议,消费者信心指数对投资者信心指数的替代,也有待考证。
①宏观经济景气指数以96为100,采用一致指数。即反映当前经济的基本走势,由工业生产、就业、社会需求(投资、消费、外贸)、社会收入(国家税收、企业利润、居民收入)等4个方面合成。
①DL\DZXX\FDC\GT\GCJZ\GSGQ\JX\JTSS\JYCM\MTSY\NL\QC\SYLS\TX\YY\YH\YSJS\YSWL\ZZYS分别是行业板块拼音首字母的缩写,即分别代表电力、电子信息、房地产、钢铁、工程建筑、供水供气、机械、交通设施、教育传媒、煤炭石油、农林、汽车、商业连锁、通信、医药、银行、有色金属、运输物流、造纸印刷。
①详情请参《投资者情绪效应：基于不同行业板块的实证研究》.武汉理工大学学报,2010,(6).
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[145]张瑞锋.金融市场协同波动溢出分析及实证研究.数量经济技术经济研究,2006,23(10)：141-149
[146]童汉飞,陈浪南.管理浮动机制下的人民币汇率行为分析——基于贝叶斯MCMC推断法与ESVDJ模型.数量经济技术经济研究,2007(11)
①宏观经济景气指数以96为100,采用一致指数。即反映当前经济的基本走势,由工业生产、就业、社会需求(投资、消费、外贸)、社会收入(国家税收、企业利润、居民收入)等4个方面合成。
①DL\DZXX\FDC\GT\GCJZ\GSGQ\JX\JTSS\JYCM\MTSY\NL\QC\SYLS\TX\YY\YH\YSJS\YSWL\ZZYS分别是行业板块拼音首字母的缩写,即分别代表电力、电子信息、房地产、钢铁、工程建筑、供水供气、机械、交通设施、教育传媒、煤炭石油、农林、汽车、商业连锁、通信、医药、银行、有色金属、运输物流、造纸印刷。
①详情请参《投资者情绪效应：基于不同行业板块的实证研究》.武汉理工大学学报,2010,(6).
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