摘要
本文对我国证券市场行业指数收益率的极值联动关系及其决定因素进行了实证研究。较以往的研究,本文在研究方法和内容方面作了如下拓展:1)引入联合极值点(Coexceedances)概念来分析行业间收益率的非线性极值联动关系;2)运用多项选择模型,估计和推断行业间收益率极值联动的影响因素。研究发现:1)证券市场行业间收益率的正(负)极值联动与市场的波动率正相关;2)经济景气指数和无风险利率对行业正(负)收益率极值联动影响不同,经济景气指数仅对行业间正的极值联动有显著影响,无风险利率仅与行业间收益率负的极值联动显著正相关;3)波动的持续性对行业间收益率正(负)的极值联动无显著影响。本文研究结果为组合投资者的风险控制和市场管理者的政策制定提供参考依据。
Many investors use the mean variance efficient portfolio frontier theory to allocate their asset investment.The application of this theory has greatly reduced the non-systematic risks of investment portfolio and increased the returns of investment security for investors.However,the equity market is changing rapidly.There exists a large number of coexceedances among industry indexes in today's equity market.This new change has undermined the usefulness of the traditional thinking of spreading risks through sectoral asset allocation.Managers and scholars of market risks have expressed their concerns regarding how to accurately describe the coexceedances and their formation mechanisms in the equity market.This study chooses to analyze the extreme industry co-movement of Chinese stock markets using negative and positive coexceedance variables that count the number of large negative or large positive returns on a given day from January 4,2000 to October 31,2008.A multinominal logit model is adopted to investigate which variables are related to the coexceedance variables.Hypotheses are proposed to assess the effect of five variables on the dynamics of equity market: information asymmetry and heterogeneity,volatility persistence,short-term liquidity shocks,product market shocks,and coexceedance asymmetry.Our findings show that the effects differ not only between negative and positive coexceedance variables but also among those factors related to the coexceedance variables in the Chinese equity market.Information asymmetry and heterogeneity are the causes of coexceedances among different industry asset prices,which may be explained by the herd effects and reputation effects.However,volatility persistence does not significantly affect negative and positive coexceedance variables.Product market shocks and short-term liquidity shocks have asymmetric effects on coexceedance variables.Product market shocks have a statistically significant effect on positive coexceedance variables,but offer little or no support for the correlation with negative coexceedance variables.Investors can reduce the required risk premium for the other(industry) asset investment risk aversion because of the wealth effect(decreasing absolute risk aversion) or compensation programs during an economic boom.The probability of positive coexceedance variables increases because investors will increase capital investment in other industries.Short-term liquidity shocks have a statistically significant effect on negative coexceedance variables,but offer little or no support for the correlation with positive coexceedance variables.The risk preference theory asserts that the behavior of investors depends on the relative risk aversion coefficient.The increase in short-term interest raises investors' cost of investment.In the event of loss of assets in an industry,short selling,lending restrictions and wealth constraints will make investors liquidate assets of other industries.Although the fundamentals of market in an industry have not changed,the natural response to asset loss can lead to the increase in asset price volatility and negative coexceedances.In summary,the risk diversification strategy has become less effective to cope with dynamic environmental changes.Investors' heterogeneity and information asymmetry have significant effects on positive and negative coexceedances.Short-term liquidity shock has significant effects on negative exceedances.Product market shocks also have significant effects on positive coexceedances.A clear understanding of coexceedances among industries and above mentioned factors can help investors make effective asset allocation and risk control decisions.
出处
《管理工程学报》
CSSCI
北大核心
2011年第1期40-48,共9页
Journal of Industrial Engineering and Engineering Management
关键词
多项选择模型
联合极值点
联动效应
行业效应
相关性
Multinomial Logit Model(MNLM)
coexceedances
co-movement
sector effects
correlation