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The Impact of the Shanghai-Hong Kong and Shenzhen-Hong Kong Stock Connect Programmes on Stock Market Resilience
在中国经济转型与金融开放不断深化的背景下,外部冲击对我国股票市场的影响日益增强,提升股票市场韧性成为维护市场稳定的重要内容。韧性指系统抵御外部冲击并在压力下恢复至稳定状态的能力,在股票市场中体现为个股与指数在遭受负面冲击后维持稳定并恢复的能力。与股价异质性波动、股价崩盘风险等传统静态稳定性指标不同,市场韧性更加关注市场吸收冲击并重建稳定状态的动态能力,是衡量市场动态稳定性的重要维度。本文将股票市场韧性具象化为股票价格波动率韧性与股票成交量韧性,运用ARMA-EGARCH模型和蒙特卡洛模拟方法,测度个股股价波动率与换手率在遭受负向冲击后恢复到冲击前水平所需时间,首次构建了A股上市公司微观层面的波动率韧性与成交量韧性指标。基于中国A股上市公司数据,本文考察了资本市场开放的重要举措——沪深港通交易制度对股票市场韧性的影响。研究发现:沪深港通显著增强了标的证券的波动率韧性和成交量韧性,发挥了稳定股价、活跃交易的市场稳定效应;股票流动性提升和股票交易中信息不对称程度下降分别是沪深港通增强波动率韧性和成交量韧性的重要因果中介机制;沪深港通对两类韧性的增强效应在人民币汇率走强、国际股票市场上行以及境内投资者避险情绪较高时更加明显。本文的贡献在于:第一,从韧性视角为金融开放与金融稳定的关系讨论提供了来自中国的经验证据;第二,识别了沪深港通增强股票市场韧性的因果中介机制,厘清了流动性、信息不对称与韧性之间的关系;第三,考察了沪深港通对不同类型股票和不同市场环境下韧性的差异化影响,有助于理解金融开放政策影响股票市场韧性的经济规律;第四,为微观层面考察股票市场韧性提供了方法思路,并首次构建了A股上市公司波动率韧性与成交量韧性数据集,为后续研究提供了数据基础。
Abstract
As China's economic transition and financial liberalisation continue to deepen, the influence of external shocks on the Chinese stock market has progressively intensified. Enhancing the stock market's resilience to negative shocks has therefore become an essential component of strengthening overall market stability. Resilience refers to a system's ability to withstand external disturbances and return to a stable state under stress. In the stock market context, it reflects the capacity of market indices and individual stocks to maintain stability following adverse events. Unlike traditional static indicators of stock market stability – such as idiosyncratic volatility and stock price crash risk – market resilience focuses more on the system's ability to absorb shocks and restore stability during and after disruptive events, rendering it an indispensable measure for assessing dynamic stability. However, the stock market's recovery capacity remains unexplored through the lens of resilience, and the role of financial openness in enhancing it constitutes a significant open question. To investigate this empirically, this paper operationalises stock market resilience through the resilience performance of stock price volatility and trading volume. Applying an autoregressive moving average – exponential generalised autoregressive conditional heteroscedasticity (ARMA – EGARCH) model and Monte Carlo simulation, it measures the time required for stock price volatility and turnover rates to recover to pre-shock levels following a negative shock. This yields a precise, micro-level measurement of volatility resilience and trading volume resilience for individual stocks. Analysing data from China's A-share listed companies, this paper examines the impact of the Shanghai – Hong Kong and Shenzhen – Hong Kong Stock Connect programmes – a pivotal financial opening-up policy – on stock market resilience. The main findings are as follows. First, the Stock Connect programmes significantly enhance both the volatility and trading volume resilience of eligible stocks, indicating their role in stabilising prices and invigorating trading, thereby contributing to market stability. Second, improvements in stock liquidity and reductions in information asymmetry in stock trading serve as important causal mediating mechanisms through which the Stock Connect enhances volatility resilience and trading volume resilience, respectively. Furthermore, the strengthening effect of the Stock Connect on both forms of resilience is more pronounced during periods of a stronger RMB exchange rate, an upward trend in global stock markets, and higher risk aversion of domestic investors. This study contributes to the literature in four key aspects. (i) It provides evidence from a resilience perspective for the discussion on the relationship between financial openness and financial stability. (ii) It identifies the causal mediating mechanisms through which the Stock Connect programmes enhance stock market resilience, clarifying the intrinsic linkages between liquidity, information asymmetry and resilience. (iii) By exploring how the impact of the Stock Connect varies across different types of stocks and market environments, it helps to reveal the economic principles through which financial opening-up policies affect stock market resilience and, by extension, overall market stability. (iv) It offers a methodological entry point for examining stock market resilience at the micro level and, for the first time, constructs datasets on volatility resilience and trading volume resilience for A-share listed companies, thereby establishing a data foundation for future research. Consequently, this research provides a robust framework for evaluating the effects of financial liberalisation, with direct implications for policymakers aiming to enhance capital market stability through institutional openness.
沪深港通显著提升标的证券的波动率韧性
基准回归中SC系数为-0.169,在5%水平显著,表明纳入沪深港通标的显著降低了波动率受冲击后恢复时间,增强了股价吸收冲击并恢复稳定的能力。
沪深港通显著提升标的证券的成交量韧性
基准回归中SC系数为-0.534,在1%水平显著,说明沪深港通显著缩短了换手率受冲击后的恢复时间,增强了交易活跃度的韧性。
流动性提升是沪深港通增强波动率韧性的因果机制
因果中介分析显示,流动性机制的ACME占总效应比例为16.2%,且在5%水平显著,表明沪深港通通过提升股票流动性增强了波动率韧性。
信息不对称下降是沪深港通增强成交量韧性的因果机制
因果中介分析显示,信息不对称机制的ACME占总效应比例至少为27%,说明降低知情交易概率是沪深港通增强成交量韧性的重要因果渠道。
沪深港通韧性提升效应在市场环境有利时更明显
异质性分析表明,在人民币汇率走强、国际股票市场上行及境内投资者避险情绪较高时期,沪深港通对波动率和成交量韧性的增强效应更为显著。
核心解释变量
沪深港通虚拟变量(SC),当个股在t年末为沪股通或深股通标的时取1,否则为0
被解释变量
波动率韧性(Vol_Res)与成交量韧性(Turnover_Res),基于ARMA-EGARCH模型和蒙特卡洛模拟测度负向冲击后的恢复时间
样本与数据
2010-2022年中国A股上市公司年度数据,剔除ST、*ST、财务数据不足及多次纳入调出标的后的3166家公司非平衡面板数据
识别方法 / 模型设定
采用交错双重差分模型,通过控制公司与年份固定效应、高维固定效应、倾向得分匹配及Goodman-Bacon分解排除干扰,借助因果中介分析(Imai et al., 2010)识别机制
内生性及稳健性检验
控制高维固定效应、Goodman-Bacon分解、倾向得分匹配估计、动态效应检验、剔除参数不显著样本、改变冲击幅度、剔除QFII交叉影响样本等,结论稳健
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