Improvements in loss given default forecasts for bank loans

An accurate forecast of the parameter loss given default (LGD) of loans plays a crucial role for risk-based decision making by banks. We theoretically analyze problems arising when forecasting LGDs of bank loans that lead to inconsistent estimates and a low predictive power. We present several improvements for LGD estimates, considering length-biased sampling, different loan characteristics depending on the type of default end, and different information sets according to the default status. We empirically demonstrate the capability of our proposals based on a data set of 69,985 defaulted bank loans. Our results are not only important for banks, but also for regulators, because neglecting these issues leads to a significant underestimation of capital requirements.     

Modeling severity risk under PD–LGD correlation

In this article, a generic severity risk framework in which loss given default (LGD) is dependent upon probability of default (PD) in an intuitive manner is developed. By modeling the conditional mean of LGD as a function of PD, which also varies with systemic risk factors, this model allows an arbitrary functional relationship between PD and LGD. Based on this framework, several specifications of stochastic LGD are proposed with detailed calibration methods. By combining these models with an extension of CreditRisk+, a versatile mixed Poisson credit risk model that is capable of handling both risk factor correlation and PD–LGD dependency is developed. An efficient simulation algorithm based on importance sampling is also introduced for risk calculation. Empirical studies suggest that ignoring or incorrectly specifying severity risk can significantly underestimate credit risk and a properly defined severity risk model is critical for credit risk measurement as well as downturn LGD estimation.     

The Role of Private Knowledge in Reducing the Information Wedge: A Research Note

Abstract:   In this first ever study to examine the marginal importance of collateral level vis‐à‐vis reputation in reducing information asymmetry, we find using unique data for UK business credit, that pre‐existing reputation is the single‐most important determinant in inducing a bank to extend a loan. Moreover, a bank responds positively to higher levels of collateral and negatively to higher credit requests. Similar to Cole (1998) , but controlling for collateral level, we find that it helps to have banked with the lender before. Non‐trivial information search costs imply an important role for reputation in extending credits.     

Forecasting bank loans loss-given-default

With the advent of the new Basel Capital Accord, banking organizations are invited to estimate credit risk capital requirements using an internal ratings based approach. In order to be compliant with this approach, institutions must estimate the loss-given-default, the fraction of the credit exposure that is lost if the borrower defaults. This study evaluates the ability of a parametric fractional response regression and a nonparametric regression tree model to forecast bank loan credit losses. The out-of-sample predictive ability of these models is evaluated at several recovery horizons after the default event. The out-of-time predictive ability is also estimated for a recovery horizon of 1 year. The performance of the models is benchmarked against recovery estimates given by historical averages. The results suggest that regression trees are an interesting alternative to parametric models in modeling and forecasting loss-given-default.     

Variable reduction,sample selection bias and bank retail credit scoring

This paper investigates the effect of including the customer loan approval process to the estimation of loan performance and explores the influence of sample selection bias in predicting the probability of default. The bootstrap variable reduction technique is applied to reduce the variable dimension for a large data-set drawn from a major UK retail bank. The results show a statistically significant correlation between the loan approval and performance processes. We further demonstrate an economically significant improvement in forecasting performance when taking into account sample selection bias. We conclude that financial institutions can obtain benefits by correcting for sample selection bias in their credit scoring models.     

The Effects of Formal and Informal Contracting in Credit Availability

This paper investigates how the use of collateral (formal contracting), along with the market power of banks (which facilitates relational contracts), affects the availability of credit for business firms. Using loan data from the Spanish Credit Register, we show that the average credit quality of borrowers in a provincial market decreases with market concentration and the availability of collateral. Additionally, the marginal effect of each variable decreases with the higher values of the other variable. We also find that credit line interest rates increase with the availability of collateral, although the increase is lower for banks operating in more concentrated credit markets. Therefore, market power (relations) and collateral (formal contracting) act as substitutes to increase the availability of bank finance under asymmetric information.     

贸易融资资产的证券化分析

资产证券化是我国金融市场发展的重要方向之一,而贸易融资资产是商业银行的重要资产之一。在贸易额逐年增加的背景下,促进贸易融资资产的证券化不仅是商业银行进行风险管理的重要方式,也是推进我国资产证券化进程的有效途径。由于供应链融资思想的引入,目前的贸易融资过程与传统的贸易融资相比有了较大的变化。在我国资产证券化市场刚刚出现的背景之下,贸易融资资产的证券化需要解决原始资产的风险管理、证券化模式的选择、中介机构制度的创立、信用评级与增级和机构监管等一系列的制度问题。     

Alternative central bank credit policies for liquidity provision in a model of payments

I explore alternative central bank policies for liquidity provision in a model of payments. I use a mechanism design approach so that agents’ incentives to default are explicit and contingent on the credit policy designed. In the first policy, the central bank invests in costly enforcement and charges an interest rate to recover costs. I show that the second-best solution is not distortionary. In the second policy, the central bank requires collateral. If collateral does not bear an opportunity cost, then the solution is first best. Otherwise, the second best is distortionary because collateral serves as a binding credit constraint.     

Loss Given Default,Loan Seasoning and Financial Fragility: Evidence from Commercial Real Estate Loans at Failed Banks

Commercial real estate (CRE) loan losses are a recurring contributor to bank failures and financial instability, yet they are not well understood. We examine a unique and proprietary data set of CRE loan defaults at banks that failed and were resolved by the FDIC after the 2008 financial crisis. We build upon an existing literature relating stochastic collateral values to loss given default (LGD). Consistent with model predictions, we show that CRE loans defaulting sooner after origination are more sensitive to declining economic conditions and exhibit LGDs that are more severe. These results are robust to a number of factors, including the declining balance of the loan over time. Our findings point to an inherent fragility associated with high CRE loan growth, even without necessarily a deterioration in lending standards, due to the changing composition of CRE loan seasoning in the industry. This reflects an unexplored risk in the literature concerning rapid and cyclical expansions in CRE credit.

     

Collateralization,Bank Loan Rates,and Monitoring

We show that collateral plays an important role in the design of debt contracts, the provision of credit, and the incentives of lenders to monitor borrowers. Using a unique data set from a large bank containing timely assessments of collateral values, we find that the bank responded to a legal reform that exogenously reduced collateral values by increasing interest rates, tightening credit limits, and reducing the intensity of its monitoring of borrowers and collateral, spurring borrower delinquency on outstanding claims. We thus explain why banks are senior lenders and quantify the value of claimant priority.     

Cyclical default and recovery in stress testing loan losses

We present a macro variable-based empirical model for corporate bank loans’ credit risk. The model captures the well-known positive relationship between probability of default (PD) and loss given default (LGD; i.e., the inverse of recovery) and their counter-cyclical movement with the business cycle. In the absence of proper micro data on LGD, we use a random-sampling method to estimate the annual average LGD. We specify a two equation model for PD and LGD which is estimated with Finnish time-series data from 1989 to 2008. We also use a system of time-series models for the exogenous macro variables to derive the main macroeconomic shocks which are then used in stress testing aggregate loan losses. We show that the endogenous LGD makes a considerable difference in stress tests compared to a constant LGD assumption.     

Bank switching of US small businesses: new methods and evidence

Despite being informationally opaque, small firms often switch from their primary financial institution to transactional lenders, with the relationship banking theory invoking the holdup problem as a culprit explanation. Using US evidence and an estimation strategy that overcomes traditional shortcomings in small business research, our study captures the determinants and, for the first time, the ex post effects of the switching decision. We find that switching is less likely when the primary financial institution is a nearby bank associated with quality services and connected to the firm via other business or social relationships. Small firms become more loyal as they grow in size and pursue nonmortgage credit. Outside the primary relationship, both loan approval and borrowing cost are adversely impacted, however loan maturities are longer. Moreover, the likelihood of pledging collateral remains unaffected, provided that the type of collateral is least sensitive to the borrower’s information environment. Jointly, our findings describe a trade-off inconsistent with the holdup problem, and an opportunity for banks to enhance customer loyalty by improving aspects of the relationship unrelated to the terms of credit.

     

How Low Can House Prices Go? Estimating a Conservative Lower Bound

In risk management, the credit risk and required capital associated with mortgage assets is often estimated through stress testing where the house price path is an important determinant of the severity of the stress test. Specifically, the extent of credit-related losses is a function of how far house prices are above long-term trend and the extent to which they can fall below trend. Focusing on the latter, we develop a theoretically-based statistical technique to identify a conservative lower bound (CLB) for house prices. Leveraging a model based upon investor incentives, the CLB explains the depth of housing market downturns at both the national and state level over a variety of market environments. This approach performs well in several historical back tests and has strong out-of-sample predictive ability. When back-tested, the estimation approach does not understate house price declines in any state over the 1987 to 2001 housing cycle and only understates declines in three states during the most recent financial crisis. This latter result is particularly noteworthy given that the post-2001 estimates are performed out-of-sample. The CLB is attractive because it (1) provides a leading indicator of the severity of future downturns and (2) allows estimates of trough to recover or decrease in magnitude as markets return to baseline conditions. This estimation technique could prove helpful in measuring the credit risk associated with portfolios of mortgage assets as part of evaluating static or designing dynamic stress tests.     

新型货币政策担保品框架的绿色效应

本文以2018年6月我国央行开始接受绿色信贷资产作为MLF合格担保品这一事件为准自然实验,运用双重差分模型分析我国新型货币政策的担保品扩容对绿色信贷企业融资的影响。研究结果表明:第一,将绿色信贷资产纳入央行合格担保品范围增加了绿色信贷企业的信贷可得性,并降低了绿色信贷企业的信贷成本;第二,企业的异质性分析表明,民营绿色信贷企业在融资可得性方面对政策反应更显著,国有绿色信贷企业在融资成本方面对政策反应更显著;第三,分行业的扩展性检验表明,央行合格担保品扩容政策对于环保行业的绿色信贷企业主要通过提高融资可得性发挥作用,而对于重污染行业的绿色信贷企业则主要作用于其信贷融资成本。基于以上实证结果,本文认为央行担保品扩容具有绿色效应,可综合运用央行担保品框架和借贷便利类货币政策工具,加强我国新型货币政策的定向调控功能。     

Self-fulfilling dynamics: The interactions of sovereign spreads,sovereign ratings and bank ratings during the euro financial crisis

During the euro-area financial crisis, interactions among sovereign spreads, sovereign credit ratings, and bank credit ratings appeared to have been characterized by self-generating feedback loops. To investigate the existence of feedback loops, we consider a panel of five euro-area stressed countries within a three-equation simultaneous system in which sovereign spreads, sovereign ratings and bank ratings are endogenous. We estimate the system using two approaches. First we apply GMM estimation, which allows us to calculate persistence and multiplier effects. Second, we apply a new, system time-varying-parameter technique that provides bias-free estimates. Our results show that sovereign ratings, sovereign spreads, and bank ratings strongly interacted with each other during the euro crisis, confirming strong doom-loop effects.     

What influences banks’ choice of credit risk management practices? Theory and evidence

Banks use different risk management practices with varying levels of sophistication. This paper examines the factors that determine the choice of risk-management practices. In a theoretical model, we identify two main determinants for the choice of risk management tools: bank competition and sector concentration in the loan market. We empirically test the predictions of our model using hand-collected data on the credit risk management of 249 German savings banks. The results are in line with our theory: Competition pushes banks to implement advanced risk management practices. Sector concentration in the loan market promotes credit portfolio modeling, but it inhibits credit risk transfer.     

Economic value,competition and financial distress in the European banking system

In this paper we examine the impact of a large number of factors at the bank level (liquidity and credit risks, asset size, income diversification and market power), at the industry level (banking concentration) and macro-level (real GDP growth) on bank financial distress using an unbalanced panel of 308 European commercial banks between 1996 and 2009. The observations falling below a given threshold of the empirical distribution of the Shareholder Value Ratio proxy bank financial distress. We employ a panel probit regression and, given the presence of overlapping data giving rise to residual autocorrelation, we use the Bertschek and Lechner (1998) robust estimator of the covariance matrix of parameters. We show that credit risk, liquidity risk and bank market power are the most influential determinants of distressed Shareholder Value Ratio. Finally we evaluate the model out-sample forecasting performance over the 2008–2009 crisis period.     

关于商业银行公司金融业务发展战略的若干问题探讨（下）

调整经济结构已成为我国宏观经济运行的主旋律,在银行间接融资占主导的背景下,产业结构调整又与银行信贷结构调整密不可分。本文讨论了经济结构、产业结构以及由此引起的信贷结构调整,既是商业银行公司金融业务发展的重大机遇,也构成了前所未有的挑战。我国商业银行必须依托经营环境的变化,制定切合实际、满足可持续发展要求的公司金融业务战略。     

Predictive regression: An improved augmented regression method

This paper proposes three modifications to the augmented regression method (ARM) for bias-reduced estimation and statistical inference in the predictive regression. They are in relation to improved bias-correction, stationarity-correction, and the use of matrix formulae for bias-correction and covariance matrix estimation. The improved ARM parameter estimators are unbiased to the order of n^− 1, and always satisfy the condition of stationarity. With the matrix formulae, the improved ARM can easily be implemented for a high order model with multiple predictors. From an extensive Monte Carlo experiment, it is found that the improved ARM delivers substantial gain in parameter estimation, statistical inference, and out-of-sample forecasting in small samples. As an application, the improved ARM is applied to monthly US stock return data to evaluate the predictive power of dividend yield in univariate and bivariate predictive models.     

关于商业银行公司金融业务发展战略的若干问题探讨（上）

调整经济结构已成为我国宏观经济运行的主旋律,在银行间接融资占主导的背景下,产业结构调整又与银行信贷结构调整密不可分。本文讨论了经济结构、产业结构以及由此引起的信贷结构调整,既是商业银行公司金融业务发展的重大机遇,也构成了前所未有的挑战。我国商业银行必须依托经营环境的变化,制定切合实际、满足可持续发展要求的公司金融业务战略。