A systematic approach to multi-period stress testing of portfolio credit risk

We propose a new method for analysing multi-period stress scenarios for portfolio credit risk more systematically than in current macro stress tests. The plausibility of a scenario is quantified by its distance from an average scenario. For a given level of plausibility, we search systematically for the most adverse scenario. This ensures that no plausible scenario will be missed. We show how this method can be applied to some models already in use by practitioners. While worst case search requires numerical optimisation we show that we can work with reasonably good linear approximations to the portfolio loss function. This makes systematic multi-period stress testing computationally efficient and easy to implement. Applying our approach to data from the Spanish loan register we show that, compared to standard stress test procedures, our method identifies more harmful scenarios that are equally plausible.     

Product market competition and credit risk

This study theoretically and empirically investigates effects of product market competition on credit risk. We first develop a real-options-based structural model in a homogeneous oligopoly and show that credit spreads are positively related to the number of firms in an industry. The disparity of firm size in an industry is relevant to both product market competition and credit risk, and we therefore extend the model to an asymmetric duopoly case. In particular, we demonstrate that credit spreads of relatively small (large) firms within an industry are positively (negatively) related to Herfindahl-Hirschman index, and the relative firm size in an industry is an important determinant of credit risk. The models’ implications are empirically scrutinized by a reduced-form hazard model and generally supported. By performing out-of-sample analyses, the results demonstrate that firm size together with the interaction terms between intra-industry firm size dummies and competition intensity can effectively predict default.     

Trade credit and bank credit: Evidence from recent financial crises

This paper studies the effect of financial crises on trade credit for a sample of 890 firms in six emerging economies. Although the provision of trade credit increases right after a crisis, it contracts in the following months and years. Firms that are financially more vulnerable to crises extend less trade credit to their customers. We argue that the decline in aggregate trade credit ratios is driven by the reduction in the supply of trade credit that follows a bank credit crunch, consistent with the “redistribution view” of trade credit provision, whereby bank credit is redistributed via trade credit from financially stronger firms to weaker firms.     

Stress testing credit risk: The Great Depression scenario

By employing Moody’s corporate default and rating transition data spanning the last 90 years we explore how much capital banks should hold against their corporate loan portfolios to withstand historical stress scenarios. Specifically, we will focus on the worst case scenario over the observation period, the Great Depression. We find that migration risk and the length of the investment horizon are critical factors when determining bank capital needs in a crisis. We show that capital may need to rise more than three times when the horizon is increased from 1 year, as required by current and future regulation, to 3 years. Increases are still important but of a lower magnitude when migration risk is introduced in the analysis. Further, we find that the new bank capital requirements under the so-called Basel 3 agreement would enable banks to absorb Great Depression-style losses. But, such losses would dent regulatory capital considerably and far beyond the capital buffers that have been proposed to ensure that banks survive crisis periods without government support.     

Measuring portfolio credit risk correctly: Why parameter uncertainty matters

Why should risk management systems account for parameter uncertainty? In addressing this question, the paper lets an investor in a credit portfolio face non-diversifiable uncertainty about two risk parameters – probability of default and asset-return correlation – and calibrates this uncertainty to a lower bound on estimation noise. In this context, a Bayesian inference procedure is essential for deriving and analyzing the main result, i.e. that parameter uncertainty raises substantially the tail risk perceived by the investor. Since a measure of tail risk that incorporates parameter uncertainty is computationally demanding, the paper also derives a closed-form approximation to such a measure.     

Correlation in credit risk changes

The current economic climate makes understanding credit risk correlation particularly important. After allowing for a comprehensive set of observable firm-specific, industry, market, and macroeconomic factors, there is an economically significant co-movement in credit default swap spreads that remains to be explained. Including a time dummy completely accounts for the remaining co-movement, confirming the existence of a systematic component that has been previously unaccounted for. Our findings suggest that it may be important to consider unobservable risk factor(s) in credit risk models.     

Information asymmetry and firms’ credit market access: Evidence from Moody's credit rating format refinement

I exploit Moody's 1982 credit rating refinement to examine its effects on firms’ credit market access, financing decisions, and investment policies. While firms’ ex ante yield spread can partially predict the direction of refinement changes, firms with refinement upgrades experience an additional decrease in their ex post borrowing cost compared with firms with downgrades. The former subsequently also issue more debt and rely more on debt financing over equity than the latter. Lastly, upgraded firms have more capital investments, less cash accumulation, and faster asset growth than downgraded firms. These findings show that credit market information asymmetry significantly affects firms’ real outcomes.     

Granularity adjustment for mark-to-market credit risk models

The impact of undiversified idiosyncratic risk on value-at-risk and expected shortfall can be approximated analytically via a methodology known as granularity adjustment (GA). In principle, the GA methodology can be applied to any risk-factor model of portfolio risk. Thus far, however, analytical results have been derived only for simple models of actuarial loss, i.e., credit loss due to default. We demonstrate that the GA is entirely tractable for single-factor versions of a large class of models that includes all the commonly used mark-to-market approaches. Our approach covers both finite ratings-based models and models with a continuum of obligor states. We apply our methodology to CreditMetrics and KMV Portfolio Manager, as these are benchmark models for the finite and continuous classes, respectively. Comparative statics of the GA reveal striking and counterintuitive patterns. We explain these relationships with a stylized model of portfolio risk.     

Equity market information,bank holding company risk,and market discipline

For market discipline to be effective, market factors such as changes in firm equity and debt values and returns, must influence firm decision making. In banking, this can occur directly via bank management or indirectly though supervisory examinations and oversight influencing bank management. In this study, we investigate whether equity market variables can provide timely information and add value to accounting models that predict changes in bank holding company (BOPEC) risk ratings over the 1988–2000 period. Using a variety of equity market indicators, the findings suggest that one-quarter lagged market data adds forecast value to lagged financial statement data and prior supervisory information in the logistic regressions. Furthermore, using extensive out-of-sample testing for the years 2001–2003, we find: (1) that multiple models estimated over different phases of the business and banking cycles are superior to a single model for forecasting BOPEC rating changes; (2) that equity data adds economically significant power in forecasting BOPEC rating upgrades and performs well for identifying no changes; (3) that for downgrades, the accounting model forecasts the best; (4) that modeling the three possible risk ratings categories simultaneously (downgrade, no change and upgrade) minimizes both Type I and Type II classification errors; and (5) that using multiple models to forecast risk ratings enhances the overall percentage of correct classifications.     

A credit scoring model for Vietnam's retail banking market

As banking markets in developing countries are maturing, banks face competition not only from other domestic banks but also from sophisticated foreign banks. Given the substantial growth of consumer credit and increased regulatory attention to risk management, the development of a well-functioning credit assessment framework is essential. As part of such a framework, we propose a credit scoring model for Vietnamese retail loans. First, we show how to identify those borrower characteristics that should be part of a credit scoring model. Second, we illustrate how such a model can be calibrated to achieve the strategic objectives of the bank. Finally, we assess the use of credit scoring models in the context of transactional versus relationship lending.     

Relationship lending,hierarchical distance and credit tightening: Evidence from the financial crisis

This paper examines the firms’ credit availability during the 2007–2009 financial crisis using a dataset of 5331 bank–firm relationships provided by borrowers’ credit folders of three Italian banks. It aims to test whether a strong lender–borrower relationship can produce less credit rationing for borrowing firms even during a credit crunch period. The results show that exclusivity of the relationship can mitigate the firm credit rationing. We also verify the influence of lending organizational structure during crisis. A new measure of distance in lending technologies has been introduced: the hierarchical distance calculated as the distance between the branch that originates the loan and the location of the hierarchical level responsible for financing decision. Our findings document a negative impact of distance on credit availability, consistent with the idea that proximity facilitates the transmission of soft information.     

The market for certification by external parties: Evidence from underwriting and banking relationships

This paper provides evidence that an underwriter is better able to certify an equity issue if it has a lending relationship with the firm. An announcement of being underwritten by the firm’s lending-relationship bank reduces ex post information asymmetry, thereby improving the announcement return. Further, because this reduction in information asymmetry effectively disseminates what was previously the lending bank’s private information, it decreases its affiliated market maker’s information advantage, thus reducing its contribution to price discovery and liquidity. These results provide evidence on the value of information production and transmission by banks, and more generally on the role of external parties in reducing information asymmetry.     

Ownership structure, market discipline, and banks’ risk-taking incentives under deposit insurance

The paper studies the effects of market discipline by creditors and ownership structure on banks’ risk taking in the presence of partial deposit insurance. An agency-cost model explains how the effects of creditor discipline and shareholder control are interdependent, the non-monotonic effect of shareholder control, and the role of leverage. Panel regressions on several hundred banks worldwide 1995-2005 confirm a negative individual risk effect of creditor discipline and the expected convex effect of shareholder control. Increased shareholder control significantly strengthens the negative effect of market discipline on asset risk, but joint effects on overall default risk are limited.     

Capital structure,credit risk,and macroeconomic conditions

This paper develops a framework for analyzing the impact of macroeconomic conditions on credit risk and dynamic capital structure choice. We begin by observing that when cash flows depend on current economic conditions, there will be a benefit for firms to adapt their default and financing policies to the position of the economy in the business cycle phase. We then demonstrate that this simple observation has a wide range of empirical implications for corporations. Notably, we show that our model can replicate observed debt levels and the countercyclicality of leverage ratios. We also demonstrate that it can reproduce the observed term structure of credit spreads and generate strictly positive credit spreads for debt contracts with very short maturities. Finally, we characterize the impact of macroeconomic conditions on the pace and size of capital structure changes, and debt capacity.     

The impact of central clearing on counterparty risk,liquidity, and trading: Evidence from the credit default swap market

This paper examines the impact of central clearing on the credit default swap (CDS) market using a sample of voluntarily cleared single-name contracts. Consistent with central clearing reducing counterparty risk, CDS spreads increase around the commencement of central clearing and are lower than settlement spreads published by the central clearinghouse. Furthermore, the relation between CDS spreads and dealer credit risk weakens after central clearing begins, suggesting a lowering of systemic risk. These findings are robust to controls for frictions in both CDS and bond markets. Finally, matched sample analysis reveals that the increased post-trade transparency following central clearing is associated with an improvement in liquidity and trading activity.     

Influence of disclosure and governance on risk of US financial services firms following Sarbanes-Oxley

This study finds significant changes in capital market measures of risk following the passage of Sarbanes-Oxley for US financial services firms. Shorter-term measures of risk shifts are positive, on average, and consistent with the mandatory nature of the disclosure and governance provisions. Longer-term total and unsystematic risk shifts are negative, on average, and consistent with reductions in investor uncertainty as transparency improved. We find that the changes in shorter-term and longer-term risk measures vary inversely with the strength of disclosure and governance characteristics. The financial market rewarded (punished) firms with stronger (weaker) disclosure and stronger (weaker) governance.     

The pernicious effects of contaminated data in risk management

Banks hold capital to guard against unexpected surges in losses and long freezes in financial markets. The minimum level of capital is set by banking regulators as a function of the banks’ own estimates of their risk exposures. As a result, a great challenge for both banks and regulators is to validate internal risk models. We show that a large fraction of US and international banks uses contaminated data when testing their models. In particular, most banks validate their market risk model using profit-and-loss (P/L) data that include fees and commissions and intraday trading revenues. This practice is inconsistent with the definition of the employed market risk measure. Using both bank data and simulations, we find that data contamination has dramatic implications for model validation and can lead to the acceptance of misspecified risk models. Moreover, our estimates suggest that the use of contaminated data can significantly reduce (market-risk induced) regulatory capital.     

Concentrated control,institutions, and banking sector: An international study

Using a broad sample of listed commercial banks in East Asia and Western Europe, this paper investigates the relations among concentrated control, a set of bank operating characteristics, and legal and regulatory regimes. We find that banks with concentrated control exhibit poorer performance, lower cost efficiency, greater return volatility, and higher insolvency risk, relative to widely held ones. We also document that legal institutions and private monitoring effectively reduce the detrimental effects of concentrated control and that official disciplinary power plays a weak governance role, whereas government intervention exacerbates the adverse effects. Further evidence shows that the relations between control concentration and bank operating characteristics are curvilinear and vary according to the types of controlling owners. Overall, our findings support the contention that country-level institutions play important roles in constraining insider expropriation, and that private monitoring mechanisms are more effective than are public rules and supervision in governing banks.     

Uninsurable risk and financial market puzzles

We compare the empirical performances of three risk-sharing arrangements involving idiosyncratic skill shocks: (a) where individuals are unable to directly insure their consumption against individual-specific shocks, (b) where agents strike long-term insurance contract with financial intermediaries involving a truth revelation constraint as in Kocherlakota and Pistaferri (2009), (c) full risk sharing. Based on the widely accepted assumption of cross-sectional log-normality of individual consumption levels, we work out closed form expressions of the pricing kernels for (a) and (b). We put these three models to test four financial market anomalies, namely the equity premium, currency premium, risk-free rate, and consumption-real exchange rate puzzles simultaneously in an integrated framework. We find that the pricing kernel associated with (a) outperforms the other two models in terms of the produced estimates of the agent’s preference parameters and the model ability to predict the equity and currency premia, the risk-free rate, and the log growth in the exchange rate. However, the predictive ability is still far from satisfactory for all three models under scrutiny.     

Business credit information sharing and default risk of private firms

We investigate whether and how business credit information sharing helps to better assess the default risk of private firms. Private firms represent an ideal testing ground because they are smaller, more informationally opaque, riskier, and more dependent on trade credit and bank loans than public firms. Based on a representative panel dataset that comprises private firms from all major industries, we find that business credit information sharing substantially improves the quality of default predictions. The improvement is stronger for older firms and those with limited liability, and depends on the sharing of firms’ payment history and the number of firms covered by the local credit bureau office. The value of soft business credit information is higher the smaller the firms and the lower their distance from the local credit bureau office. Furthermore, in spatial and industry analyses we show that the higher the value of business credit information the lower the realized default rates. Our study highlights the channel through which business credit information sharing adds value and the factors that influence its strength.