New Basle Capital Agreement and Risk Management of China＇s Banking Industry

Adjustment of Basle Capital Agreement will influence the risk management and capital arrangement demand of the banks with different scales, operation level and environment. It will have widespread and profound effect on the competition strength of every country＇s banks in the global market. Starting with illustration of the present cond（tion of risk management in China＇s banks, the paper analyzes the major problems existing in the risk management system of China＇s banking industry, then puts forward some clues and suggestions to improve and better the risk management system of China＇s banking industry.

A global perspective on macroprudential policy interaction with systemic risk,real economic activity,and monetary intervention

The study empirically assesses how macroprudential policy interacts with systemic risk,industrial production,and monetary intervention on a global level from January 2006 to December 2018.We adopt the aggregate proxies of these variables,capturing their global effects,and use a novel econometric technique,namely,smooth local projections.The study finds that global macroprudential policy leads the monetary policy,exhibiting a countercyclical pattern concerning industrial production.The latter has an inverse bidirectional linkage with systemic risk.Thus,an ex-ante tight macroprudential policy can indirectly mitigate global systemic risk through its pro-growth effect on industrial production,although no convincing evidence exists for the direct impact of a macroprudential intervention on systemic risk.The study results endure several extensions and a robustness check,which builds on alternative measures of global systemic stress and real economic activity,thereby legitimizing the increased importance attached to the macroprudential policy since the 2007–2009 global financial crisis.

A Knowledge-based System for the Analysis of the Ability of Paying back Loans

This paper describes the development of a knowledgebased system (KBS) for determining whether or not, and under what conditions, a bank Ioan officer should grant a business loan to a company. The prototype system developed focuses on what is bank loans risks management, how to prevent risk by the analysis of the ability of paying back loans. The paper makes the structural analysis involved in the system's decision situation, the structured situation diagram or model, dependency diagram and the document needed by the KBS prototype system thus are developed. Through testing the samples from loan business, the quality for the analysis of the ability of paying back loans can be effectively evaluated by the KBS prototype system.

Minimizing the Environmental Risk from Oil Tanker Grounding Accidents in the High North

To address the high environmental risk related to the increased oil tanker traffic in the High North, the Norwegian Coastal Administration (NCA) manages one of its vessel traffic service (VTS) centers in the town of Vardø, Norway. The fleet of tugboats, controlled by the VTS center operators, patrols the coastline to hook-up with any potential drifting oil tanker in the region of interest, before it runs ashore. Presently, the tugboats are controlled manually, which is not only challenging but less effective. In this paper, we develop two alternative binary integer programming models that give better tugboat policies in less computational time compared to previous work. Promising results with historical data illustrate great potential for optimal environmental risk reduction along the northern coast of

Research on Systemic Risk Spillover Effect of Chinese Listed Commercial Banks——Based on Quantile CoVaR Model

The banking industry plays an important role in China's financial market, and the systemic risk of the banking industry has astrong risk spillover effect. This paper measures the systemic risk spillover effect of Chinese listed commercial banks byconstructing the quantile CoVaR model. The study concluded that when an extreme risk event occurs, the overall risk spillovereffect of a single bank on the banking system is greater than the risk spillover effect of the banking system on a single bank, thevalue of VaR is smaller than the actual risk value when measuring the risk value of commercial banks and the CoVaR model ismore accurate in measuring systemic risk.

Connectedness and systemic risk of the banking industry along the Belt and Road

This paper adopts the tail-event driven network(TENET)framework to explore the connectedness and systemic risk of the banking industry along the Belt and Road(B&R)based on weekly returns of 377 publicly-listed banks from 2014 to 2019.We conduct the connectedness analysis from four levels(i.e.,system,region,country and institution)and identify the systemic risk contribution of banks.We find that the dynamic total connectedness reached its peak during the outbreak of the abnormal fluctuations of Chinese stock market in 2015-2016 and its trough during the Brexit vote,and subsequently experienced several periodic fluctuations at a relatively high position.In the B&R banking system,the intra-regional tail risk spillovers are remarkably stronger than the inter-regional tail risk spillovers during the post-crisis period.In addition,the panel regressions estimated by the least squares dummy variable model show that the cross-border merger and acquisitions(M&As)and the merchandise trade export are important drivers for the tail-connectedness across the B&R countries.Our study provides regulators with insightful implications on the systemic risk supervision of the B&R banking industry.

包商银行事件对我国上市银行系统性风险的影响——基于Vine Copula SCCA半参数模型

为研究包商银行这类区域性商业银行的风险暴露对我国上市银行系统性风险的影响,本文提出VineCopulaSCCA半参数模型,基于2013—2019年我国上市银行数据构建银行业整体及三大类银行机构的联合预期损失分布,并计算联合预期亏损作为系统性风险度量指标。该模型融入R-Vine Copula函数和半参数建模思想,放宽了传统SCCA模型关于风险相依结构和边际分布的假设,提升了国内银行业系统性风险测度的适应性,从而更加科学地测度我国银行业系统性风险的演变特征。研究发现,相较于传统SCCA模型,Vine Copula SCCA半参数模型成功捕捉到包商银行两次延期披露年报和被接管所预示的潜在风险暴露危机,能更好地刻画上市银行系统性风险的演变轨迹。本文给出更加合理的系统性风险测度模型,为我国区域性商业银行的高质量发展、风险防控以及相关监管政策的制定提供借鉴参考。

Risk Assessment Index System of Natural Gas Industrial Chain in China

This paper establishes a risk assessment index system for the natural gas industrial chain. China＇s natural gas industrial chain is entering a stage of rapid growth. In order to guarantee healthy development of the natural gas industrial chain, it is urgent to establish a risk alert system, which is based on a risk assessment index system. First of all, the risks of the natural gas industrial chain are defined in the paper; then the risk factors are analyzed according to the present status of the natural gas industrial chain, and five categories of risk factors are summarized： resource risk, transport risk, marketing risk, risk of unbalanced chain links, and environment risk. The paper presents the principles of the risk assessment index system. The natural gas industrial chain risk assessment index system is established with four levels and forty-six risk indices.

Intelligent Decision Support System for Bank Loans Risk Classification

Intelligent Decision Support System (IISS) for Bank Loans Risk Classification (BLRC), based on the way of integration Artificial Neural Network (ANN) and Expert System (ES), is proposed. According to the feature of BLRC, the key financial and non-financial factors are analyzed. Meanwhile, ES and Model Base (MB) which contain ANN are designed . The general framework,interaction and integration of the system are given. In addition, how the system realizes BLRC is elucidated in detail.

Systemic Risk of Conventional and Islamic Banks: Comparison with Graphical Network Models

The main aim of this paper is to compare the stability, in terms of systemic risk, of conventional and Islamic banking systems. To this aim, we propose correlation network models for stock market returns based on graphical Gaussian distributions, which allows us to capture the contagion effects that move along countries. We also consider Bayesian graphical models, to account for model uncertainty in the measurement of financial systems interconnectedness. Our proposed model is applied to the Middle East and North Africa (MENA) region banking sector, characterized by the presence of both conventional and Islamic banks, for the period from 2007 to the beginning of 2014. Our empirical findings show that there are differences in the systemic risk and stability of the two banking systems during crisis times. In addition, the differences are subject to country specific effects that are amplified during crisis period.

经济政策不确定性、投资者情绪与银行系统性风险传染

面对经济政策不确定性和投资者情绪,银行业需承担应对经济衰退、化解银行风险和实现经济高质量稳定增长的责任。本文利用MVMQ-CAViaR模型测度了2008—2021年所有上市银行的系统性风险,构建面板门限回归模型和面板平滑转换模型,研究在投资者情绪转换作用下经济政策不确定性影响银行系统性风险多重传染的边际效应结构变化。研究表明:投资者情绪具有显著的区制转换效应,使经济不确定性影响银行系统性风险多重传染的净边际效应,以指数转换模式发生结构变化。据此提出正确处理经济政策不确定性与银行系统性风险的关系,投资者要保持理性情绪以及监管部门要加强监管的建议。

“一带一路”共建国家银行业系统性风险的测度研究

有效识别“一带一路”共建国家的系统性风险及其关键驱动因素对平稳实现各国经济金融的深度融合具有重大的现实意义。基于150多万条银行微观股票数据和财务数据,通过构建压力时期回归模型的客观方法获得系统性风险三因素权重,在同一框架下利用规模、杠杆、关联性3个因子测算了银行、国家、“一带一路”共建国家系统3个层次的银行业系统性风险指数。研究结果表明,从系统性风险表现来看,“一带一路”共建国家整体的银行业系统性风险受全球宏观金融环境波动影响显著。此外,“一带一路”共建国家也会因为自身问题而出现银行业系统性风险上升的情形。印度、越南、印度尼西亚等国家是系统重要性国家,其银行业系统性风险水平较高;匈牙利、克罗地亚、罗马尼亚等国家的银行业系统性风险水平较低。银行业系统性风险较高的国家主要在于其有较高系统性风险贡献水平的银行,且各行业经济发展状况以及经济增长对国家层面系统性风险有显著的影响。从风险驱动因素看,关联性因子是驱动银行业系统性风险水平变化的主要因素,其次为规模因子和杠杆因子。

“双支柱”调控框架与影子银行风险溢出:抑制缓释还是累积加剧

如何搭建货币政策和宏观审慎政策“双支柱”调控框架,有效防范化解重大风险,是我国现阶段的重要任务。基于我国上市银行数据,本文采用CoVaR方法衡量影子银行导致的银行系统性风险,系统考察“双支柱”调控框架对影子银行风险溢出的影响。结果显示,针对借款人和银行信贷的宏观审慎政策工具与货币政策配合,对影子银行风险溢出起到显著的“抑制缓释”作用;影子银行规模是“累积加剧”和“抑制缓释”效应的渠道,流动性分层则是“累积加剧”效应的渠道。结合银行性质、房地产周期与经济周期的异质性分析结果显示,在不同情景下,“双支柱”调控框架对影子银行风险溢出的有效性存在较大差异。本文结论对于“防风险”目标下“双支柱”调控框架的完善具有一定的指导意义。

基于不完全信息静态博弈的工控系统风险评估方法

针对目前大多数工业控制系统风险评估方法未思考防御者策略以及攻防两者之间的对抗问题,提出一种基于博弈模型的风险评估方法。通过攻击防御图模型,计算攻击收益和防御收益;建立静态贝叶斯攻防博弈模型,计算混合策略贝叶斯纳什均衡,获得攻防两者最优策略概率分布。根据信息安全风险评估的计算方法,以防御者收益和攻击者最优策略选择概率分布为基础进行风险评估计算。通过一个实例证明了该方法的可行性和有用性。

收入分配差距与银行信用风险累积——基于企业部门杠杆的视角

改善收入分配状况、推进共同富裕是否有助于防范化解金融风险?立足于企业部门杠杆视角,构建包含家庭异质性、企业债务违约和银行破产特质的实际经济周期(RBC)模型,研究居民收入分配差距对银行信用风险的影响。理论模型预测显示,收入分配差距扩大会提高企业部门杠杆率,增加银行信用风险累积。其作用机制在于,收入分配差距扩大导致消费投资比下降,为企业部门加杠杆创造条件,但消费率和杠杆率的反向变动会造成企业实际收益率降低和违约风险上升,银行贷款信用风险敞口扩大。基于中国银行业数据的实证分析提供了上述理论推演成立的经验证据与微观基础。此外,本文还发现收入分配差距的影响存在地区性差异。上述结论隐含共同富裕目标的实现有利于守住不发生系统性风险底线,两个重大目标的内在逻辑自洽一致。

银企信贷复杂网络下的银行业系统性风险研究——基于高碳行业视角

碳减排压力下,高碳企业向低碳转型内生的“转型风险”可能成为引发下一场系统性金融风险的“绿天鹅”事件。基于2013-2022年14个高碳行业的银企贷款数据,首先采用“银企”二分网络法,以高碳企业预期违约率作为风险传染强度指标,纵向度量“银企”的风险传导路径。研究发现银企间网络规模逐年扩大,尾部风险突出集中于化工行业,且主要由股份制商业银行承受。其次运用“银银”映射网络法,以银行间共同风险敞口作为风险传染强度指标,横向度量“银银”的风险传导路径。研究发现城市商业银行与农村商业银行日渐成为系统重要性银行,风险承担愈加凸显;国有控股大型商业银行自身输出较大银行间尾部风险,其对风险的扩散或防御至关重要。最后基于复杂网络筛选出系统重要性银行与风险传染性银行,运用动态CoVaR法度量尾部溢出的系统性风险贡献强度,全面捕捉风险从高碳企业到金融机构间“自下而上的风险测度逻辑”,从而为监管部门构建“自上而下的风险监管逻辑”提供现实依据。在“双碳”战略下,应出台专门的信贷支持政策推动重点行业实施节能减排,立足“银企”信贷网络的全局开展差异化管理和全面风险评估,在逆周期缓冲资本监管框架的挂钩变量中引入高碳行业尾部风险的新视角。

地方产业链政策创新与企业风险承担——来自产业链“链长制”的证据

产业链“链长制”是推动我国产业链供应链现代化的制度创新,能否锻造链上企业韧性进而提升企业风险承担水平备受学界与业界关注。基于2013—2021年中国A股上市公司数据,采用渐进式双重差分法实证检验“链长制”的企业风险治理效应及机制,研究发现,“链长制”显著提升企业风险承担水平,主要通过缓解企业融资约束、提升价值链权力及强化信息透明度发挥作用,且“链主”对非“链主”存在溢出效应。进一步研究发现,上述政策效果在行政等级更高和营商环境更好的城市中更明显,且对资本密集型企业和非“链主”的风险承担提升效果更显著。研究不仅提供了“链长制”助力企业高质量发展的微观经验证据,同时为地方优化产业链政策提供了决策参考。

金融监管与非银行金融部门系统性风险传染

近年来,中国系统性金融风险呈现跨部门传导效应,尤其是非银行金融部门风险传染可能成为威胁金融市场稳定的重要挑战。本文基于非银行金融部门的微观数据,采用弹性网分位数回归构建尾部风险网络,利用复杂网络分析方法动态捕捉非银行金融机构系统性风险溢出水平的演变特征,研究金融监管对非银行金融部门系统性风险传染的政策效应。研究结果显示:第一,金融部门的系统性风险溢出总水平主要来自非银行金融部门的系统性风险溢出水平,其中多元金融部门的系统性风险溢出尤为突出,证券部门和多元金融部门存在较为密切的双向系统性风险溢出;第二,2017年金融监管改革后,金融公司之间的风险网络结构密度有所降低,跨部门系统性风险溢出水平显著降低;第三,金融监管对非银行金融部门系统性风险溢出水平的影响具有明显的时变性特征,2016—2017年金融监管明显降低了系统性风险溢出水平,2018年后政策效果因受到外部冲击而有所弱化;第四,不同非银行金融部门的系统性风险溢出水平对政策冲击的响应存在差异,金融监管政策在短期内降低多元金融部门和证券部门的系统性风险溢出水平效果更为明显。本文的研究结论对完善中国金融风险防范体系、防止金融资本“脱实向虚”和健全相应的风险监管制度具有一定的参考价值。

中国的银行体系稳定与宏观政策协同调控研究——基于服务实体经济与防范金融风险的双重视角

基于支撑服务能力和风险抵御能力两个层面界定银行体系稳定内涵,运用混频动态因子模型与马尔科夫区制转移模型分别实现中国银行体系稳定的指数拟合与演变特征分析,进一步构建时变参数因子增广向量自回归模型考察宏观政策对银行体系稳定的调控效果。研究发现,新常态以来银行体系支撑服务能力经历了V型探底后企稳回升的演变路径,风险抵御能力则由高位大幅震荡转变为低位小幅波动;银行体系支撑服务能力和风险抵御能力存在典型的周期错位现象,两者的联动关系既有恶性螺旋区间也有良性循环阶段;相较于宏观审慎政策,财政政策和数量型货币政策对银行体系稳定的调控效应尤为凸显,价格型货币政策的调控效率正持续提升,且多数政策工具会面临顾此失彼的两难调控困境;反事实分析表明,财政、货币与宏观审慎政策协同调控有利于节省政策空间并降低政策缺位引致的机会成本,是引导银行体系实现稳增长和防风险动态平衡的占优策略。研究从统筹服务实体经济与防范金融风险的双重视角丰富了中国式银行体系稳定的理论内涵,为健全中国特色的金融监管体制和宏观调控架构提供了政策启示。