Testing time-homogeneity of rating transitions after origination of debt

When modelling rating transitions as continuous-time Markov processes, in practice, time-homogeneity is a common assumption, yet restrictive, in order to reduce the complexity of the model. This paper investigates whether rating transition probabilities change after the origination of debt. Accordingly, we develop a likelihood-ratio test for the hypothesis of time-homogeneity. The alternative is a step function of transition intensities. The test rejects time-homogeneity for rating transitions observed over 7 years in a real corporate portfolio. Especially 1-year transition probabilities increase over the first year after origination. This time effect suggests that banks should manage their credit portfolios with respect to the age of debt.      

Analysis of sectoral credit default cycle dependency with wavelet networks: Evidence from Turkey

In this paper, we investigate the relationship between industrial production and sectoral credit defaults (non-performing loans ratio) cycle by wavelet network analysis in Turkey over the period January 2001–November 2007. We use feedforward neural network based wavelet decomposition to analyze the contemporaneous connection between industrial production cycles and sectoral credit default cycles at different time scales between 2 and 64 months. The main findings for Turkey indicates that industrial production cycles effect the sectoral credit default cycles at different time scales and thus indicate that the creditors should consider the multiscale sectoral cycles in order to minimize credit default rates.     

巴塞尔新资本协议与信用风险模型的监管审查研究

巴塞尔新资本协议鼓励银行采用内部评级法评估信用风险以提取资本准备,但内部评级法必须满足监管审查的要求。基于新资本协议的这一要求,从监管机构的角度出发,建立信用风险模型监管审查框架,讨论了银行建立内部信用风险模型时,为确保其合理性需要满足的条件与要求,从而为我国的监管机构提供参考借鉴。     

预期对我国消费信贷的影响

预期是个人对未来经济发展情形的一种判断,它对我国消费信贷有着重要的影响。虽然我国近年来为了扩大内需,将消费信贷作为一项重要措施推出,但由于受居民预期因素的作用和影响而发展缓慢。因此,政府应从多方面制定政策以解决预期对我国消费信贷的干扰。     

The Interaction between Capital Requirements and Monetary Policy

The interaction between capital requirements and monetary policy is assessed by means of simple rules in a dynamic general equilibrium model featuring a banking sector. In “normal” times, when economic dynamics are driven by supply shocks, an active use of capital requirements generates modest benefits in terms of volatility of the target variables compared to the case in which only the central bank carries out stabilization policies. The lack of cooperation between the two policymakers may result in excessive volatility of the monetary policy rate and capital requirements. The benefits of introducing capital requirements become sizeable when financial shocks, which affect the supply of loans, are important drivers of economic dynamics; the availability of capital requirements as a policy tool yields a significant gain in terms of macroeconomic stabilization, regardless of the type of interaction between monetary and capital requirements policies.     

道德风险视域下职业经理人信用评价体系构建及测度：以重庆市为例

道德风险总是困扰着职业经理人群体,对企业发展产生不利影响。在实践中,作为建立健全社会信用体系的重要环节,职业经理人信用评价是防范职业经理人群体道德风险的基本思路和必要举措。本文基于马克思主义的理论启示,探索职业经理人三个维度的道德关系和道德风险,并围绕三个维度指向的个人信用、职业信用与职务信用等具体信用构成,阐述职业经理人信用评价内涵。进而,结合职业经理人信用评价内涵,构建系统应对道德风险的职业经理人信用评价体系,并以重庆为例进行实证测度。在此基础上,提出促进职业经理人道德意识与信用水平提升、实现新时代职业经理人群体高素质发展的对策建议。     

区块链技术对供应链金融信用风险的影响——基于PSM-DID方法的实证分析

区块链技术作为一项极具颠覆性的新兴技术,为供应链金融风险控制提供了创新性解决方案。基于2017—2020年供应链金融上市公司面板数据,运用倾向得分匹配-双重差分法（PSM-DID）实证分析区块链技术的应用对供应链金融信用风险的影响。研究发现,区块链技术能够显著降低供应链金融信用风险。因此,各企业可积极引入区块链技术,利用区块链的技术优势解决信用风险难题。     

The impact of sovereign credit ratings on Eurobond yields: Evidence from Africa

The importance of sovereign credit ratings and Eurobonds issued by governments have come to the fore in Africa in the last decade. We examine whether changes in sovereign credit ratings impact Eurobond yields in 8 countries over the period of 2014–2019. Our approach reviews rating changes impact on Eurobond yields utilising the event study methodology. Our findings reflect that, on average, close to a third of rating actions directly impact bond yields in African countries. The statistically significant events include the downgrades of South Africa and Namibia to non-investment grade in 2017 reflecting critical transitions and bond investors’ reactions. Overall, the low percentage of a third, relative to previous international studies, suggests that largely rating changes are anticipated, do not have much new information and perhaps the perceived power of credit rating agencies may be overstated. In our view, the results reflect that pre-announcements of rating review dates since 2014 makes rating actions predictable and less impactful to bond yields. In addition, they reflect that bond investors adjust in real time as new information come in, resulting in less reliance on the opinions of CRAs and using their own assessments.     

Optimal probabilistic forecasts: When do they work?

Proper scoring rules are used to assess the out-of-sample accuracy of probabilistic forecasts, with different scoring rules rewarding distinct aspects of forecast performance. Herein, we re-investigate the practice of using proper scoring rules to produce probabilistic forecasts that are ‘optimal’ according to a given score and assess when their out-of-sample accuracy is superior to alternative forecasts, according to that score. Particular attention is paid to relative predictive performance under misspecification of the predictive model. Using numerical illustrations, we document several novel findings within this paradigm that highlight the important interplay between the true data generating process, the assumed predictive model and the scoring rule. Notably, we show that only when a predictive model is sufficiently compatible with the true process to allow a particular score criterion to reward what it is designed to reward, will this approach to forecasting reap benefits. Subject to this compatibility, however, the superiority of the optimal forecast will be greater, the greater is the degree of misspecification. We explore these issues under a range of different scenarios and using both artificially simulated and empirical data.