股市收益波动的非对称性研究

随着我国股票市场的逐步发展及证券市场监管体制的逐步完善,股票市场收益波动所呈现的非对称性效应是否会发生逆转引人关注。本文运用不同的GARCH类条件异方差模型(EGARCH、TARCH、PARCH以及非对称CARCH模型),选取1998年1月5日至2006年11月6日上证综指的日收盘价格指数数据,分析和验证了股票收益波动的非对称性效应。结果表明,上海股市股票收益波动仍然具有非对称性,即利空消息对收益波动的冲击效应大于同等程度的利好消息,从而验证了非对称效应的不可逆转性。     

中国股指期货与现货关系的实证研究——基于沪深300股指期货

股指期货与现货的关系一直是一个研究热点。但是这些研究主要基于国外股指期货或沪深300股指期货仿真交易,而对正式推出后的沪深300股指期货的研究很匮乏。文章利用相关性分析和Granger因果检验分析了沪深300股指期货对现货之间的价格发现功能,利用GARCH类模型分析了沪深300股指期货推出对现货波动性的影响。结论显示,沪深300股指期货与现货之间有着很强的相关性,但不构成相互决定关系;沪深300股指期货的推出降低了现货的波动性;同时,该股指期货的推出使现货收益的非对称性显著增强。上述结论与目前已有的对仿真交易沪深300股指期货的研究结论存在着一些不一致。     

基于GARCH模型的认购权证与认沽权证波动率比较研究

波动性是经济和金融研究的热点问题。本文分别采用无条件波动度量方法和条件波动模型对我国权证市场上具有代表性的六支权证的波动性进行估计,得出以下几个结果:1、六支权证基本上都存在不同程度的波动聚类现象。2、认沽权证的市场有效性弱于认购权证。3、认购权证的波动持续性大于认沽权证,说明认沽权证投机性更强,风险更大。4、认购权证的风险收益补偿大概是认沽权证的6倍。最后,结合本文研究,将给广大投资者一些投资建议。     

Research on the time-varying effects among green finance markets in China: A fresh evidence from multi-frequency scale perspective

Green finance is an essential instrument for achieving sustainable development. Objectively addressing correlations among different green finance markets is conducive to the risk management of investors and regulators. This paper presents evidence on the time-varying correlation effects and causality among the green bond market, green stock market, carbon market, and clean energy market in China at multi-frequency scales by combining the methods of Ensemble Empirical Mode Decomposition Method (EEMD), Dynamic Conditional Correlation (DCC) GARCH model, Time-Varying Parameter Vector Autoregression with Stochastic Volatility Model (TVP-VAR-SV), and Time-varying Causality Test. In general, the significant negative time-varying correlations among most green finance markets indicate a prominent benefit of risk hedging and portfolio diversification among green financial assets. In specific, for different time points and lag periods, the green finance market shock has obvious time-varying, positive and negative alternating effects in the short-term scales, while its time delay and persistence are more pronounced in the medium-term and long-term scales. Interestingly, a positive event shock will generate positive connectivity among most green finance markets, whereas a negative event including the China/U.S. trade friction and the COVID-19 pandemic may exacerbate the reverse linkage among green finance markets. Furthermore, the unidirectional causality of “green bond market - carbon market - green stock and clean energy markets” was established during 2018–2019.