A simulation study of Basel II expected loss distributions for a portfolio of credit cards

Credit scoring models have been used traditionally as the basis of decisions to reject or accept credit applications. They are also used to categorize applicants or existing accounts into risk groups. Based on estimates of probability of default (PD), the risk groups may seem well separated. However, by considering distributions on risk elements such as model estimation uncertainty, exposure at default and loss given default, a simulation approach is used to compute Basel II expected loss distributions for a portfolio of credit cards. These show that discrimination between risk groups is not as clear as is immediately suggested simply by PD estimates. Based on these distributions, we also show that measuring extreme credit risk with Value at Risk can lead to considerable underestimation if distributions on these risk elements are not entered into the computation.     

The effect of credit guarantees on credit availability and delinquency rates

We use new data to examine whether credit guarantees affect economic incentives and whether they affect the credit available to small- and medium-size enterprises (SMEs). We find that firms that have both guaranteed and non-guaranteed loans are 1.67% more likely to miss payments on their guaranteed loans, but are not more likely to default on these loans. These findings suggest that guarantees affect firms’ incentives to repay loans but not their long-term performance. We also find that firms selected into the guarantee programs are 1.17% more likely to default on their loans compared with similar firms that borrow without guarantees. Since we find evidence that long-term performance is not affected by guarantees, the higher default rates among firms selected into the guarantee programs must be the consequence of adverse selection. We also find that credit guarantees increase the aggregated amount of credit; in particular, one additional dollar of guarantees increases the total credit for SMEs by US$ 0.65.     

Contagion models a la carte: which one to choose?

We propose a copula contagion mixture model for correlated default times. The model includes the well-known factor, copula, and contagion models as its special cases. The key advantage of such a model is that we can study the interaction of different models and their pricing impact. Specifically, we model the default times of the underlying names in a reference portfolio to follow contagion intensity processes with exponential decay coupled with a copula dependence structure. We also model the default time of the counterparty and its dependence structure with the reference portfolio. Numerical tests show that correlation and contagion have an enormous joint impact on the rates of CDO tranches and the corresponding credit value adjustments are extremely high to compensate for the wrong-way risk.     

The differential impact of leverage on the default risk of small and large firms

We analyse a sample of 6 million firm-year observations of large corporations and small and medium sized enterprises (SMEs) spanning 6 European countries from 2005 to 2015, to determine the impact of leverage and different sources of funding on default risk. We find that financial leverage has a greater impact on the probability of default of SMEs than of large corporations. The difference in default probability between the top and bottom leverage quartiles is 1.24% for large firms and 2.87% for SMEs. This difference may be explained by the greater exposure of SMEs to short-term debt and their consequently higher refinancing risk. Indeed, we find that SMEs that recover from the state of insolvency may have similar leverage to defaulted SMEs; however their liability structure is significantly altered towards long-term debt and away from short-term debt. Our findings have important implications not only for bank regulators and policy-makers but also for credit risk modelling.     

Modelling default contagion using multivariate phase-type distributions

We model dynamic credit portfolio dependence by using default contagion in an intensity-based framework. Two different portfolios (with ten obligors), one in the European auto sector, the other in the European financial sector, are calibrated against their market CDS spreads and the corresponding CDS-correlations. After the calibration, which are perfect for the banking portfolio, and good for the auto case, we study several quantities of importance in active credit portfolio management. For example, implied multivariate default and survival distributions, multivariate conditional survival distributions, implied default correlations, expected default times and expected ordered default times. The default contagion is modelled by letting individual intensities jump when other defaults occur, but be constant between defaults. This model is translated into a Markov jump process, a so called multivariate phase-type distribution, which represents the default status in the credit portfolio. Matrix-analytic methods are then used to derive expressions for the quantities studied in the calibrated portfolios.     

定向降准、贷款可得性与小微企业商业信用——基于断点回归的经验证据

小微企业在我国经济发展中起到了重要作用,但由于长期面临融资约束问题,使其不得不诉诸非正式制度(如商业信用)来缓解融资困难。党的十九届五中全会明确提出,支持小微企业成长为创新重要发源地,完善促进小微企业发展的政策体系。其中,实施“精准滴灌”式的货币政策,对小微企业成长尤为重要,是金融服务实体经济的必然要求。我国央行的定向降准政策激励银行向小微企业提供贷款,有利于疏通小微企业通过正式制度(如银行贷款)进行融资的渠道。本文基于定向降准这一自然实验,采用断点回归设计,评估贷款可得性对小微企业商业信用的影响。研究发现:第一,正式制度对于非正式制度存在明显的替代效应,即小微企业贷款可得性上升以后,对商业信用的需求显著下降。第二,不同的模型设定与稳健性检验,均得到一致的结论。第三,贷款可得性提高对小微企业商业信用的影响因企业异质性而有所差异。本文研究为银行贷款与商业信用之间的替代关系提供了来自中国小微企业的证据,有助于理解定向降准政策对小微企业融资决策的影响,为扶持小微企业发展的政策制定提供参考。     

Gender bias in access to trade credit: Firm-level evidence from emerging markets

How do small and medium-sized enterprises (SMEs) led by women fare with respect to obtaining trade credit? While both trade credit and bank credit have long been viewed as potentially important financing instruments for SMEs, there is considerable ambiguity in the existing literature as to whether they complement or substitute each other from the perspective of credit-seeking SMEs. This is even more important for Women-Led Businesses (WLBs) in emerging markets and developing economies (EMDEs) who tend to face higher severity of credit constraints relative to their male counterparts. Given this context, using firm-level data on 95 EMDEs over 2009–2020, we contribute to the literature on gender bias and credit access by examining three specific questions: First, is there a gender bias in obtaining inter-firm trade credit? Second, if there is one, can those WLBs with access to traditional bank finance use it as a signal to obtain trade credit? Third, how does this relationship hold for SMEs that are women-led? After tackling potential endogeneity bias, our empirical findings show that WLBs are less likely to obtain inter-firm trade credit relative to their male counterparts, although we observe that this bias tends to disappear when WLBs have received an institutional source of financing. We establish robustly that bank credit can act as a signaling device enabling the accessibility of inter-firm trade credit, suggesting a complementary relationship between trade credit and bank credit for WLBs.     

IRB法下公司敞口组合的风险驱动因子计量研究

巴塞尔银行监管委员会针对防范信贷组合信用风险所需要的资本制定的内部评级法,通过风险驱动因子的变化来反映组合回报的变化,并根据风险权重函数,通过风险加权资产转化为与每一项信用风险敞口更准确匹配的资本要求.本文对违约概率、违约损失率、违约敞口、期限因素以及违约相关性等信贷组合信用风险的风险驱动因子的度量进行了综合研究.     

A framework to measure integrated risk

A framework underlying various models that measure the credit risk of a portfolio is extended in this paper to allow the integration of credit risk with a range of market risks using Monte Carlo simulation. A structural model is proposed that allows interest rates to be stochastic and provides closed-form expressions for the market value of a firm's equity and its probability of default. This model is embedded within the integrated framework and the general approach illustrated by measuring the risk of a foreign exchange forward when there is a significant probability of default by the counterparty. For this example moving from a market risk calculation to an integrated risk calculation reduces the expected future value of the instrument by an amount that could not be calculated using the common pre-settlement exposure technique for estimating the credit risk of a derivative.     

‘Credit crunch’ and Small- and Medium-sized Enterprises: Aspects affecting survival

Small- and Medium-sized Enterprises (SMEs) are major contributors to the economy of most countries, but under the ‘credit crunch’ it has been suggested that many SMEs are facing a range of difficulties. In this context, it is increasingly important to consider the factors influencing the survival of SMEs. However, the research on SME default is surprisingly limited. We reviewed the media accounts of SME performance under the current economic downturn. We suggest that it may not be the ‘credit crunch’ and the restriction of credit itself that has an impact on SME survival, but rather the consequences arising from the recession. The difficulties may lie with downturn in trade leading to reduction in cash flow and turnover, and this may be exacerbated by a slowdown in the rate of payments for all businesses. These aspects feed through to the higher risk premium that may be charged to SMEs. The review of related literature on modelling SME default and their performance in previous recessions identifies aspects that are important for survival.     

Valuation of Portfolio Credit Derivatives with Default Intensities Using the Vasicek Model

We present a methodology for valuing portfolio credit derivatives under a reduced form model for which the default intensity processes of risk assets follow the one-factor Vasicek model. A closed-form solution of joint survival time distribution is obtained. The solution is applied to value credit derivatives of a credit default swap index and collateralized debt obligation. The limitation of methods using the Vasicek model is discussed. We propose that the method is valid and efficient for a portfolio with small-scale correlated risk assets, for which the acceptable size is much greater than for the traditional method. Numerical examples and parameter analysis are also presented.     

基于担保机制的网络联保融资模式创新

中小企业因经营规模小、管理不完善、信息披露机制不健全等原因使银企之间出现信息不对称,导致商业银行在贷款时出于风险的考虑不愿意向中小企业放款。网络联保贷款为解决中小企业融资难和降低银行贷款风险提供了一条新路径。但在内外部约束不够强烈的条件下,网络联保运行机制会出现失效,企业倾向于选择策略性违约而给银行带来损失。为进一步降低风险,将担保制度引入到网络联保融资模式中,可以有效降低企业策略性违约的概率。     

Modelling the distribution of credit losses with observable and latent factors

This paper proposes a dynamic model to estimate the credit loss distribution of the aggregate portfolio of loans granted in a banking system. We consider a sectoral approach distinguishing between corporates and households. The evolution of their default frequencies and the size of the loans portfolio are expressed as functions of macroeconomic conditions as well as unobservable credit risk factors, which capture contagion effects between sectors. In addition, we model the distributions of the Exposures at Default and the Losses Given Default. We apply our framework to the Spanish banking system, where we find that sectoral default frequencies are not only affected by economic cycles but also by a persistent latent factor. Finally, we identify the riskier sectors, perform stress tests and compare the relative risk of small and large institutions.     

Heterogeneous effects of credit constraints on SMEs’ employment: Evidence from the European sovereign debt crisis

This paper takes advantage of access to detailed matched bank-firm data to investigate whether and how employment decisions of SMEs have been affected by credit constraints during the European sovereign debt crisis. Variability in banks’ financial health following the 2008 crisis is used as an exogenous determinant of firms’ access to credit. Findings, relative to the Belgian economy, clearly highlight that credit matters. They show that SMEs borrowing money from pre-crisis financially less healthy banks were significantly more likely to be affected by a credit constraint and, in turn, to adjust their labour input downwards than pre-crisis clients of more healthy banks. These results are robust across types of loan applications that were denied credit, i.e. applications to finance working capital, debt or new investments. Yet, estimates also show that credit constraints have been essentially detrimental for employment among SMEs experiencing a negative demand shock or facing strong product market competition. In terms of human resources management, credit constraints are not only found to foster employment adjustment at the extensive margin but also to increase the use of temporary layoff allowances for economic reasons. This outcome supports the hypothesis that short-time compensation programmes contribute to save jobs during recessions.     

The search for relative value in bonds

Comparing asset swap spreads across bonds is a widely used tool for measuring relative value. This approach leads portfolio managers to increase their risk exposure in ways that are not transparent. Credit default swaps are utilized to demonstrate that viewing wide asset swaps as an indicator of relative value is a mirage. The paper documents the empirical regularities in the term structure of credit spreads and spread volatilities that make this result possible. In addition, we present empirical evidence of the imprint made on corporate bond returns by the widespread use of the asset swaps data.     

Analyzing the impact of credit migration in a portfolio setting

Credit migration is an essential component of credit portfolio modeling. In this paper, we outline a framework for gauging the effects of credit migration on portfolio risk measurements. For a typical loan portfolio, we find credit migration can explain as much as 51% of volatility and 35% of economic capital. We compare through-the-cycle migration effects, implied by agency rating transitions, with point-in-time migration, implied by EDF? (Expected Default Frequency) transitions, and find that migration of point-in-time credit quality accounts for a greater fraction of total portfolio risk when compared with through-the-cycle dynamics. In a stylized analytic setting, we show that, when controlling for PD term structure effects, higher likelihood of moving away from the current credit state does not necessarily imply greater risk. Finally, we review methods for generating high-frequency transition matrices, needed for analyzing instruments with cash flows or contingencies whose frequencies are asynchronous to an available transition matrix. We further demonstrate that the naïve application of such methods can result in material deviations to portfolio analytics.     

Predicting unlisted SMEs' default: Incorporating market information on accounting-based models for improved accuracy

The risk associated with lending to small businesses has become more important since regulations started obliging banks to use separate procedures in assessing SMEs' credit worthiness. However, current accounting-based models for SMEs do not account for the impact of market information on default prediction. We fill this gap in the literature by introducing a hybrid default prediction model for unlisted SMEs that uses market information of listed SMEs (comparable approach) alongside existing accounting information of unlisted SMEs. Our results suggest that the accuracy of this default prediction modelling approach in the hold-out sample, during the period of the financial crisis 2007-09 and for the entire sample-period, improves considerably. We conclude that the proposed hybrid model is a good replacement for existing standard accounting-based methods on SMEs' default prediction.     

Pricing Sovereign Credit Risk of Poland: Evidence from the CDS Market

We analyze the market assessment of sovereign credit risk using a reduced-form model to price the credit default swap (CDS) spreads, thus enabling us to derive values for the probability of default (PD) and loss given default (LGD) from the quotes of sovereign CDS contracts. We compare different specifications of the models allowing for both fixed and time-varying LGD, and we use these values to analyze the sovereign credit risk of Polish debt throughout the period of a global financial crisis. Our results suggest the presence of a low LGD and a relatively high PD during a recent financial crisis.     

Credit cycles and macro fundamentals

We use an intensity-based framework to study the relation between macroeconomic fundamentals and cycles in defaults and rating activity. Using Standard and Poor's U.S. corporate rating transition and default data over the period 1980–2005, we directly estimate the default and rating cycle from micro data. We relate this cycle to the business cycle, bank lending conditions, and financial market variables. In line with earlier studies, the macro variables appear to explain part of the default cycle. However, we strongly reject the correct dynamic specification of these models. The problem is solved by adding an unobserved dynamic component to the model, which can be interpreted as an omitted systematic credit risk factor. By accounting for this latent factor, many of the observed macro variables loose their significance. There are a few exceptions, but the economic impact of the observed macro variables for credit risk remains low. We also show that systematic credit risk factors differ over transition types, with risk factors for downgrades being noticeably different from those for upgrades. We conclude that portfolio credit risk models based only on observable systematic risk factors omit one of the strongest determinants of credit risk at the portfolio level. This has obvious consequences for current modeling and risk management practices.     

Bilateral credit valuation adjustment for large credit derivatives portfolios

We obtain an explicit formula for the bilateral counterparty valuation adjustment of a credit default swaps portfolio referencing an asymptotically large number of entities. We perform the analysis under a doubly stochastic intensity framework, allowing default correlation through a common jump process. The key insight behind our approach is an explicit characterization of the portfolio exposure as the weak limit of measure-valued processes associated with survival indicators of portfolio names. We validate our theoretical predictions by means of a numerical analysis, showing that counterparty adjustments are highly sensitive to portfolio credit risk volatility as well as to the intensity of the common jump process.