资本账户自由化、信贷扩张与系统性银行危机风险*

本文研究在资本账户自由化下，信贷扩张与资本流入对于系统性银行危机风险的影响。利用89个国家1973—2016年的长面板数据，并控制影响银行危机风险多项因素后，研究发现资本账户自由化有助于降低银行危机风险。进一步研究发现，FDI流入能显著降低银行危机风险；适量的股权投资流入有助于增强银行业稳定性；但当股权投资大量流入时，伴随着信贷过度扩张和资产泡沫，银行危机风险急剧增加；较低的债权投资流入对银行业稳定性无显著影响，但当超过一定规模时，银行危机风险显著增加。       

Model risk in credit risk

We provide sharp analytical upper and lower bounds for value‐at‐risk (VaR) and sharp bounds for expected shortfall (ES) of portfolios of any dimension subject to default risk. To do so, the main methodological contribution of the paper consists in analytically finding the convex hull generators for the class of exchangeable Bernoulli variables with given mean and for the class of exchangeable Bernoulli variables with given mean and correlation in any dimension. Using these analytical results, we first describe all possible dependence structures for default, in the class of finite sequences of exchangeable Bernoulli random variables. We then measure how model risk affects VaR and ES.     

Access to credit and heterogeneous effects on agricultural technology adoption: Evidence from large rural surveys in Ethiopia

Modern agricultural technologies hold huge potential for increasing productivity and reducing poverty in developing countries. However, adoption levels of these technologies have remained disappointingly low in Africa. This paper analyzes the effect of access to credit on the likelihood of adoption and use intensity of chemical fertilizers using data from large rural surveys in Ethiopia. Using a heteroscedasticity-based identification strategy to address the endogenous nature of access to credit, we find that access to credit has significant positive effects on adoption and intensity of use of chemical fertilizers. However, important heterogeneities are observed. Credit obtained from formal sources is more important for the intensity of use than for the decision to adopt chemical fertilizers. Credit taken with the primary purpose of financing agricultural inputs is more likely to promote adoption of chemical fertilizers than credit taken per se. Furthermore, reported credit effects are larger when estimated against the sample of credit-constrained non-users as compared with the pool of the whole sample of credit non-users. The results remain robust to several sensitivity analyses. Our results yield useful implications for the design, promotion, and targeting of credit services to leverage their effect on adoption of agricultural technologies.     

国内外企业信用领域研究进展及热点的可视化分析

企业信用是社会信用体系的重要部分,是国民经济可持续发展的必要保障。我们以Web of Science、CNKI为数据源,运用CiteSpace软件,从发文量、国家(地区)及机构、代表作者、关键词等方面对企业信用研究领域的主要文献成果进行可视化分析,并系统探讨企业的信用评估、信用风险、征信体系等研究热点。分析发现:该领域国内外发文量总体保持稳定增长,近年来小微企业的信用问题受到学者们的广泛关注,新兴信息技术和供应链金融模式为解决企业信用管理难题提供了契机。     

财务战略影响公司商业信用融资能力吗？

以2007—2016年中国A股上市公司为样本，实证检验了公司财务战略定位上的异质性特征对公司商业信用融资能力的影响。研究发现，偏离行业平均水平的异质性财务战略显著降低了公司商业信用融资能力；收益波动程度增加和通过操纵性应计项目实施的盈余管理程度增强所引发的盈余质量降低，是偏离行业平均水平的异质性财务战略影响公司商业信用融资能力的中介路径，发挥了部分中介效应；考虑产权性质的调节作用后发现，相比非国有企业，国有企业加剧了财务战略定位上的异质性特征对公司商业信用融资能力的负面影响。     

Robust XVA

We introduce an arbitrage‐free framework for robust valuation adjustments. An investor trades a credit default swap portfolio with a risky counterparty, and hedges credit risk by taking a position in defaultable bonds. The investor does not know the exact return rate of her counterparty's bond, but she knows it lies within an uncertainty interval. We derive both upper and lower bounds for the XVA process of the portfolio, and show that these bounds may be recovered as solutions of nonlinear ordinary differential equations. The presence of collateralization and closeout payoffs leads to important differences with respect to classical credit risk valuation. The value of the super‐replicating portfolio cannot be directly obtained by plugging one of the extremes of the uncertainty interval in the valuation equation, but rather depends on the relation between the XVA replicating portfolio and the closeout value throughout the life of the transaction. Our comparative statics analysis indicates that credit contagion has a nonlinear effect on the replication strategies and on the XVA.     

Volatility spillovers among the U.S. and Asian stock markets: A comparison between the periods of Asian currency crisis and subprime credit crisis

This paper examines the changing nature of volatility spillovers among the U.S. and eight East Asian stock markets between two financial crises: the Asian currency crisis and the U.S. subprime credit crisis. Our empirical results suggest that volatility is not always spilled over from the directly affected markets to surrounding markets in crisis periods. The East Asian markets who directly suffered from the Asian currency crisis are the ones to which volatility is spilled over from other markets during the Asian currency crisis period, whereas uni-directional volatility spillovers from the U.S. market to other markets are observed during both crisis periods. This difference can be explained by a pre-determined hierarchy in which volatility spillovers tend to start from the U.S. market regardless of the geographical origin of the crisis. Furthermore, our results reveal that the markets in three major Asian financial hubs, i.e., Japan, Hong Kong and Singapore, are the markets to which volatility is spilled over uni-directionally from several other countries during the subprime credit crisis period, but not during the Asian currency crisis period. We attribute this difference to crisis-specific (currency or credit crisis), market-specific (credit derivatives market participation and foreign currency reserves), and time-specific (more integrated global market) factors.     

Biogeography based optimization for mining rules to assess credit risk

Financial institutions, by and large, rely on the use of machine learning techniques to improve the classic credit risk assessment model for reduction of costs, delivery of faster decisions, guaranteed credit collections, and risk mitigations. As such, several data mining and machine learning approaches have been developed for computation of credit scores over the last few decades. Moreover, the existing rule-based classification algorithms tend to generate a number of rules with a large number of conditions in the antecedent part. However, these algorithms fail to demonstrate high predictive accuracy while balancing coverage and simplicity. Thus, it becomes quite a challenging task for the researchers to generate an optimal rule set with high predictive accuracy. In this paper, we present an effective rule based classification technique for the prediction of credit risk using a novel Biogeography Based Optimization (BBO) method. The novel BBO in the context of rule mining is named as locally and globally tuned biogeography based rule-miner (LGBBO-RuleMiner). This is applied for discovering optimal rule set with high predictive accuracy from the dataset containing both the categorical and continuous attributes. The performance of the proposed algorithm is compared against a variety of rule-miners such as OneR (1R), PART, JRip, Decision Table, Conjunctive Rule, J48, and Random Tree, along with some meta-heuristic based rule mining techniques by considering two credit risk datasets obtained from University of California, Irvine (UCI) repository. It is found from the comparative study that the proposed rule miner in ten independent runs of ten-fold cross validation outperforms all of the aforesaid algorithms in terms of predictive accuracy, coverage, and simplicity.     

信贷政策调整和房地产价格的动态关系--基于VEC模型的分析

文章从理论角度分析了银行信贷同房产价格间的关系和作用机制,并在此基础上利用2010年1月-2019年6月全国房产价格月度数据建立VEC模型进行实证研究。结果表明,银行信贷和房产价格具有双向因果关系:房价波动对信贷波动具有显著影响,而信贷波动对房价波动影响相对有限。文章认为房价波动通过短期信贷、抵押物价值和银行资本金三种渠道来影响信贷供给。因此,政府在调整信贷政策时需要考虑房价波动的影响。