随着可再生能源渗透率增加,净负荷波动幅度也随之变大。因此,该文针对净负荷不确定性变化,结合预测误差相关性与条件风险价值(conditional value at risk,CVaR),提出一种综合能源系统灵活爬坡优化调度方法。首先,通过神经网络模型预测...随着可再生能源渗透率增加,净负荷波动幅度也随之变大。因此,该文针对净负荷不确定性变化,结合预测误差相关性与条件风险价值(conditional value at risk,CVaR),提出一种综合能源系统灵活爬坡优化调度方法。首先,通过神经网络模型预测风光荷初始功率,针对预测误差,运用C藤Copula函数构建多元随机变量预测误差的联合概率分布,并据此提出一种灵活爬坡产品设计方法;然后,在考虑净负荷不确定性带来的弃风光和切负荷条件风险价值的基础上,构建考虑灵活爬坡产品风险价值的综合能源系统优化调度模型。仿真结果表明,考虑净负荷预测误差相关性的优化使系统整体经济性提升1.22%,切负荷与弃风光总量减少了17.01%,验证该文方法的有效性。结合不同置信水平下的CVaR值,可为综合能源系统调度提供一定的风险参考。展开更多
为研究我国系统重要性银行的风险溢出,文章基于我国14家系统重要性银行的股票收盘价,采用分位数回归计算的条件在险价值方法与格兰杰因果检验方法,研究了我国系统重要性银行的溢出风险。研究结果表明国有四大行的溢出风险呈逐年下降态势...为研究我国系统重要性银行的风险溢出,文章基于我国14家系统重要性银行的股票收盘价,采用分位数回归计算的条件在险价值方法与格兰杰因果检验方法,研究了我国系统重要性银行的溢出风险。研究结果表明国有四大行的溢出风险呈逐年下降态势,但总体风险仍相对较高;一些股份制银行的波动区间较大,需要特别注意。基于此,文章建议,第一要构建适用于我国金融发展水平的系统性风险监测预警体系;第二是突出重点,强化系统重要性银行与机构的监管;第三是不能忽视中小银行引发系统性风险的可能。To study the risk spillover of China’s systemically important banks, this article is based on the closing stock prices of 14 systemically important banks in China. It employs quantile regression calculations, conditional value-at-risk, and Granger causality tests to investigate the spillover risk of these banks. The research results indicate that the spillover risk from the four major state-owned banks in China has shown a year-on-year decreasing trend, but the overall risk remains relatively high. Some of the commercial banks with different ownership structures exhibit a wider range of volatility, requiring special attention. Based on these findings, the article recommends three main actions: firstly, the need to construct a systemic risk monitoring and early warning system suitable for China’s level of financial development;secondly, emphasizing a focus on and strengthening the regulation of systemically important banks and institutions;and thirdly, not disregarding the potential for smaller banks to trigger systemic risks.展开更多
商业银行作为金融体系的核心机构,对于整个金融体系的稳定与健康发展有着至关重要的作用,然而商业银行的系统性金融风险溢出效应是导致金融危机的主要原因之一。本文选取上市商业银行股价数据,通过在险价值和条件在险价值法,运用GARCH-C...商业银行作为金融体系的核心机构,对于整个金融体系的稳定与健康发展有着至关重要的作用,然而商业银行的系统性金融风险溢出效应是导致金融危机的主要原因之一。本文选取上市商业银行股价数据,通过在险价值和条件在险价值法,运用GARCH-CoVaR模型,研究了单家商业银行以及整个银行业的系统性金融风险溢出效应。通过实证研究发现商业银行的确可以向金融系统外溢金融风险,并且在经济危机时更加明显。据此本文提出有关方面要加强监管和监管合作,建立前瞻性风险预警机制,提高风险管理能力以维护我国金融系统的健康稳定发展。Commercial banks, as the core institutions of the financial system, play a crucial role in ensuring the stability and healthy development of the entire financial system. However, the systemic financial risk spillover effect of commercial banks is one of the main causes of financial crises. This paper selects the stock price data of listed commercial banks and studies the systemic financial risk spillover effect of individual commercial banks and the entire banking industry using value at risk and conditional value at risk methods. Empirical research reveals that commercial banks can indeed transmit financial risks to the financial system, and this effect becomes more pronounced during economic crises. Based on the above, this paper calls for strengthening the following aspects: enhancing regulation and regulatory cooperation, establishing forward-looking risk alert mechanisms, and improving risk management capabilities in order to maintain the healthy and stable development of China’s financial system.展开更多
文摘随着可再生能源渗透率增加,净负荷波动幅度也随之变大。因此,该文针对净负荷不确定性变化,结合预测误差相关性与条件风险价值(conditional value at risk,CVaR),提出一种综合能源系统灵活爬坡优化调度方法。首先,通过神经网络模型预测风光荷初始功率,针对预测误差,运用C藤Copula函数构建多元随机变量预测误差的联合概率分布,并据此提出一种灵活爬坡产品设计方法;然后,在考虑净负荷不确定性带来的弃风光和切负荷条件风险价值的基础上,构建考虑灵活爬坡产品风险价值的综合能源系统优化调度模型。仿真结果表明,考虑净负荷预测误差相关性的优化使系统整体经济性提升1.22%,切负荷与弃风光总量减少了17.01%,验证该文方法的有效性。结合不同置信水平下的CVaR值,可为综合能源系统调度提供一定的风险参考。
文摘为研究我国系统重要性银行的风险溢出,文章基于我国14家系统重要性银行的股票收盘价,采用分位数回归计算的条件在险价值方法与格兰杰因果检验方法,研究了我国系统重要性银行的溢出风险。研究结果表明国有四大行的溢出风险呈逐年下降态势,但总体风险仍相对较高;一些股份制银行的波动区间较大,需要特别注意。基于此,文章建议,第一要构建适用于我国金融发展水平的系统性风险监测预警体系;第二是突出重点,强化系统重要性银行与机构的监管;第三是不能忽视中小银行引发系统性风险的可能。To study the risk spillover of China’s systemically important banks, this article is based on the closing stock prices of 14 systemically important banks in China. It employs quantile regression calculations, conditional value-at-risk, and Granger causality tests to investigate the spillover risk of these banks. The research results indicate that the spillover risk from the four major state-owned banks in China has shown a year-on-year decreasing trend, but the overall risk remains relatively high. Some of the commercial banks with different ownership structures exhibit a wider range of volatility, requiring special attention. Based on these findings, the article recommends three main actions: firstly, the need to construct a systemic risk monitoring and early warning system suitable for China’s level of financial development;secondly, emphasizing a focus on and strengthening the regulation of systemically important banks and institutions;and thirdly, not disregarding the potential for smaller banks to trigger systemic risks.
文摘商业银行作为金融体系的核心机构,对于整个金融体系的稳定与健康发展有着至关重要的作用,然而商业银行的系统性金融风险溢出效应是导致金融危机的主要原因之一。本文选取上市商业银行股价数据,通过在险价值和条件在险价值法,运用GARCH-CoVaR模型,研究了单家商业银行以及整个银行业的系统性金融风险溢出效应。通过实证研究发现商业银行的确可以向金融系统外溢金融风险,并且在经济危机时更加明显。据此本文提出有关方面要加强监管和监管合作,建立前瞻性风险预警机制,提高风险管理能力以维护我国金融系统的健康稳定发展。Commercial banks, as the core institutions of the financial system, play a crucial role in ensuring the stability and healthy development of the entire financial system. However, the systemic financial risk spillover effect of commercial banks is one of the main causes of financial crises. This paper selects the stock price data of listed commercial banks and studies the systemic financial risk spillover effect of individual commercial banks and the entire banking industry using value at risk and conditional value at risk methods. Empirical research reveals that commercial banks can indeed transmit financial risks to the financial system, and this effect becomes more pronounced during economic crises. Based on the above, this paper calls for strengthening the following aspects: enhancing regulation and regulatory cooperation, establishing forward-looking risk alert mechanisms, and improving risk management capabilities in order to maintain the healthy and stable development of China’s financial system.
