伴随着人民币国际化和国内金融市场深层次建设的加速,债券市场和利率互换市场都越来越受到多元主体的关注。利率债市场是公开利率的风向标之一,利率互换市场则是金融机构风险管理的重要抓手,两个市场受同样的因素影响具有相似的反应机制,彼此之间存在着复杂的动态相依关系,刻画这种关系对于完善金融市场、丰富政策工具和强化风险管理都有重要意义。本文采用t-Copula模型和DCC-GARCH模型,基于一年期和五年期国债收益率、互换利率收益率数据讨论了我国利率债和利率互换之间的动态相依关系和波动溢出效应。本文发现两者之间不仅存在着动态相依关系,还具有显著的交互影响和波动溢出效应。With the acceleration of the internationalization of the Renminbi and the deepening construction of domestic financial markets, both the bond market and the interest rate swap market are increasingly garnering attention from diverse entities. The interest rate bond market serves as one of the barometers for public interest rates, while the interest rate swap market is a crucial mechanism for risk management in financial institutions. Both markets, influenced by similar factors, exhibit akin reaction mechanisms and share a complex dynamic interdependence. Characterizing this interdependence is vital for the refinement of financial markets, the enrichment of policy tools, and the strengthening of risk management. This paper employs the t-Copula model and the DCC-GARCH model to discuss the dynamic interdependence and volatility spillover effects between China’s interest rate bonds and interest rate swaps, using data on one-year and five-year government bond yields and swap rate returns. The findings reveal not only a dynamic interdependence between the two but also significant mutual influences and volatility spillover effects.
随着全球气候变化问题的加剧,把握碳市场与能源市场之间的风险溢出效应对于实现减排目标和推动经济转型具有重要意义。本文采用溢出指数方法和DCC-GARCH模型对我国2014年7月1日至2024年6月28日碳市场和能源市场间的风险溢出效应进行了深入分析。研究发现,不同市场条件下,碳市场和能源市场间的风险溢出水平存在明显差异,且风险溢出水平呈现非对称性;广东碳市场与风能、太阳能和原油市场间风险关联性较小,湖北碳市场与能源市场间的风险关联性较大。本研究不仅丰富了碳市场风险溢出效应的理论框架,而且为政策制定者提供了防范系统性风险、优化市场监管的实证依据,具有重要的理论和实践意义。As the global climate change intensifies, it is very important to understand the risk spillover effect of carbon market and energy market in order to realize emission reduction targets and promote economic transition. This paper uses the spillover index method and the DCC-GARCH model to conduct an in-depth analysis of the risk spillover effects the carbon market and the energy market in China from July 1, 2014 to June 28, 2024. The results show that under different market conditions, there are obvious differences in the risk spillover levels between carbon market and energy market, and the risk spillover levels are asymmetrical. The risk correlation among Guangdong carbon market and wind energy market, solar energy market and crude oil market is small, and the risk correlation between Hubei carbon market and energy market is large. This study not only enriches the theoretical framework of carbon market risk spillover, but also provides policy makers with an empirical basis for preventing systemic risks and optimizing market supervision, which is of great theoretical and practical significance.
本研究运用DCC-GARCH模型,针对中国八大证券公司在2015年7月1日至2023年7月1日期间的股票收益率数据进行了深入分析,旨在揭示这些证券公司间系统性风险的动态关联性。实证分析结果显示,中国这八大证券公司的股票收益率呈现出波动聚集性,并且风险动态相关性为正。鉴于此,证券公司应持续强化其对系统性风险的管理能力,不断完善内部风险防控体系,增强其风险抵御力,以期有效降低风险对公司造成的损失。This paper establishes DCC-GARCH model to study the stock returns of eight major securities companies from July 1, 2015 to July 1, 2023, and finds the dynamic correlation of systemic risk among eight major securities companies in China. Through empirical analysis, it can be found that the stock returns of China’s eight securities companies have the characteristics of volatility clustering, and there is a positive risk dynamic correlation. Securities companies should continuously strengthen their ability to manage systemic risks, adhere to improving their internal risk prevention and control mechanism, and improve their ability to resist risks, so as to reduce the losses brought by risks to securities companies.
