中国沪深股市结构性波动的政策性影响因素

摘要/Abstract

摘要： 本文利用划分均值和方差变点的迭代累积平方和算法(ICSS:MV)对上证综指和深证成指1996年12月16日至2010年12月31日的日收益率序列进行结构变点的检验,通过将结构变点与重大事件对应选取影响沪深股市结构性波动的政策性事件,并根据选取的事件将样本区间分成13个子区间。为了避免参数模型中模型误设的缺陷,利用非参数GARCH模型估计样本区间的波动率;最后利用N-W核回归估计对非参数GARCH估计的波动率与收益率进行回归,分析股市结构性波动产生的政策性影响因素。通过分析发现央行调整存贷款基准利率和存款准备金率、国有股的减持、允许保险公司等机构投资者买卖证券投资基金、调整印花税等政策性因素是造成我国股市变结构波动的重要原因。

关键词: 股市波动性, 政策性因素, ICSS：MV算法, 非参数GARCH模型, N-W核回归估计

Abstract: In this paper, ICSS: MV algorithm is used to detect structural breakpoints of daily return series of Shanghai composite index and Shenzhen component index from Dec 12, 1996 to Dec 31, 2010. By corresponding structural breakpoints and major events, all the policy events among the major events are selected, and then according to these policy events, the sample period is divided into thirteen sub-intervals. In order to avoid the shortfalls caused by misspecification using parametric models, nonparametric GARCH model is used to estimate the volatility. Finally, N-W kernel regression of the volatility and the daily return is conducted, and furthermore the policy factors that cause the structural volatility of stock market are analyzed. It is concluded that the adjustment of the benchmark interest rate of deposit and loan as well as the deposit reserve ratio, the reduction of the state-owned shares, the permission of institutional investors to trade mutual funds, the adjustment of the stamp duty and so on are policy impact factors that cause structural volatility of Shanghai and Shenzhen stock market.

Key words: stock market volatility, policy factors, ICSS：MV algorithm, nonparametric GARCH model, N-W kernel regression

中图分类号:

F830.91

杨继平, 陈晓暄, 张春会. 中国沪深股市结构性波动的政策性影响因素[J]. 中国管理科学, 2012, 20(6): 43-51.

YANG Ji-ping, CHEN Xiao-xuan, ZHANG Chun-hui. Policy Impact Factors on the Volatility of Shanghai and Shenzhen Stock Market in China[J]. Chinese Journal of Management Science, 2012, 20(6): 43-51.

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