Regulation of credit rating agencies

Financial regulators recognize certain credit rating agencies for regulatory purposes. However, it is often argued that credit rating agencies have an incentive to assign inflated ratings. This paper studies a repeated principal-agent problem in which a regulator approves credit rating agencies. Credit rating agencies may collude to assign inflated ratings. Yet we show that there exists an approval scheme which induces credit rating agencies to assign correct ratings.     

Variations in sovereign credit quality assessments across rating agencies

We investigate agency variation in credit quality assessment (Standard and Poor’s vs. Moody’s vs. Fitch) employing sovereign ratings data for 129 countries, spanning the period 1990–2006. While we find that the credit rating agencies often disagree about credit quality, it is usually confined to one or two notches on the finer scale. We find that several variables have varying importance in explaining ratings across agencies which leads us to conclude that material heterogeneity exists between them. Also, while watch and outlook procedures are generally strong predictors of rating changes relative to other public data, additional significant variables suggest that it might be possible to augment these agency data to provide better forecasts of future rating changes.     

An economic capital model integrating credit and interest rate risk in the banking book

Banks often measure credit and interest rate risk in the banking book separately and then add the risk measures to determine economic capital. This approach misses complex interactions between the two risk types. We develop a framework where these risks are analysed jointly. Since banking book positions are generally not marked to market, our model is based on book value accounting. Our simulations show that interactions matter, and that ignoring them leads to risk overstatement. The magnitude of the errors depends on the structure of the balance sheet and on the repricing characteristics of assets and liabilities.     

Asymmetric effects of the business cycle on bank credit risk

Prior empirical research on the relation between credit risk and the business cycle has failed to properly investigate the presence of asymmetric effects. To fill this gap, we examine this relation both at the aggregate and the bank level exploiting a unique dataset on Italian banks’ borrowers’ default rates. We employ threshold regression models that allow to endogenously establish different regimes identified by the thresholds over/below which credit risk is more/less cyclical. We find that not only are the effects of the business cycle on credit risk more pronounced during downturns but cyclicality is also higher for those banks with riskier portfolios.     

The delivery option in credit default swaps

Under standard assumptions the reduced-form credit risk model is not capable of accurately pricing the two fundamental credit risk instruments – bonds and credit default swaps (CDS) – simultaneously. Using a data set of euro-denominated corporate bonds and CDS our paper quantifies this mispricing by calibrating such a model to bond data, and subsequently using it to price CDS, resulting in model CDS spreads up to 50% lower on average than observed in the market. An extended model is presented which includes the delivery option implicit in CDS contracts emerging since a basket of bonds is deliverable in default. By using a constant recovery rate standard models assume equal recoveries for all bonds and hence zero value for the delivery option. Contradicting this common assumption, case studies of Chapter 11 filings presented in the paper show that corporate bonds do not necessarily trade at equal levels following default. Our extension models the implied expected recovery rate of the cheapest-to-deliver bond and, applied to data, largely eliminates the mispricing. Calibrated recovery values lie between 8% and 47% for different obligors, exhibiting strong variation among rating classes and industries. A cross-sectional analysis reveals that the implied recovery parameter depends on proxies for the delivery option, primarily the number of available bonds and bond pricing errors. No evidence is found for a direct influence of the bid-ask spread, notional amount, coupon, or rating used as proxies for bond market liquidity.     

Credit rating dynamics in the presence of unknown structural breaks

In many credit risk and pricing applications, credit transition matrix is modeled by a constant transition probability or generator matrix for Markov processes. Based on empirical evidence, we model rating transition processes as piecewise homogeneous Markov chains with unobserved structural breaks. The proposed model provides explicit formulas for the posterior distribution of the time-varying rating transition generator matrices, the probability of structural break at each period and prediction of transition matrices in the presence of possible structural breaks. Estimating the model by credit rating history, we show that the structural break in rating transitions can be captured by the proposed model. We also show that structural breaks in rating dynamics are different for different industries. We then compare the prediction performance of the proposed and time-homogeneous Markov chain models.     

Systemic risk contributions: A credit portfolio approach

We put forward a framework for measuring systemic risk and attributing it to individual banks. Systemic risk is coherently measured as the expected loss to depositors and investors when a systemic event occurs. The risk contributions are calculated so as to ensure a full risk allocation among institutions. Applying our methodology to a panel of 54–86 of the world’s major commercial banks for a 13-year time span with monthly frequency not only allows us to closely match the list of G-SIBs; we can also use individual risk contributions to compute bank-specific surcharges: systemic capital charges as well as countercyclical buffers. We therefore address both dimensions of systemic risk – cross-sectional and time-series – in a single integrated approach. As the analysis of risk drivers confirms, the main focus of macroprudential supervision should be on a solid capital base throughout the financial cycle and de-correlation of banks’ asset values.     

Regime dependent determinants of credit default swap spreads

Credit default swap (CDS) spreads display pronounced regime specific behaviour. A Markov switching model of the determinants of changes in the iTraxx Europe indices demonstrates that they are extremely sensitive to stock volatility during periods of CDS market turbulence. But in ordinary market circumstances CDS spreads are more sensitive to stock returns than they are to stock volatility. Equity hedge ratios are three or four times larger during the turbulent period, which explains why previous research on single-regime models finds stock positions to be ineffective hedges for default swaps. Interest rate movements do not affect the financial sector iTraxx indices and they only have a significant effect on the other indices when the spreads are not excessively volatile. Raising interest rates may decrease the probability of credit spreads entering a volatile period.     

Credit rating dynamics and Markov mixture models

Despite mounting evidence to the contrary, credit migration matrices, used in many credit risk and pricing applications, are typically assumed to be generated by a simple Markov process. Based on empirical evidence, we propose a parsimonious model that is a mixture of (two) Markov chains, where the mixing is on the speed of movement among credit ratings. We estimate this model using credit rating histories and show that the mixture model statistically dominates the simple Markov model and that the differences between two models can be economically meaningful. The non-Markov property of our model implies that the future distribution of a firm’s ratings depends not only on its current rating but also on its past rating history. Indeed we find that two firms with identical current credit ratings can have substantially different transition probability vectors. We also find that conditioning on the state of the business cycle or industry group does not remove the heterogeneity with respect to the rate of movement. We go on to compare the performance of mixture and Markov chain using out-of-sample predictions.     

Asset financing with credit risk

This paper develops a model for the unified valuation of all forms of real asset financing, such as bank loans, leases, securitization vehicles, and credit guarantees, secured by assets that generate a stochastic service flow to the operator, or a rental stream to the lessor, and depreciate over a finite economic life to their scrap value. Examples include mobile equipment, such as aircraft, railroad equipment, ships, trucks and trailers, as well as energy generation assets, heavy factory equipment and construction equipment. In the event of obligor default, after a repossession delay and incurring costs of repossession, maintenance, re-marketing and re-deployment, the lender repossesses the asset and sells it on the secondary market and is, thus, subject to the risk of decline in the market value of the asset. The model we develop in this paper treats all forms of asset financing in a unified fashion as contingent claims on the collateral asset and the credit of the borrower. As an application, we estimate the collateral asset model on historical secondary market data for aircraft values and calibrate the financing model to the Enhanced Equipment Trust Certificates (EETCs) issued in 2007 by Continental Airlines and secured by a fleet of new aircraft. We then apply the calibrated model to value private market financing, including bank loans, leases, and credit guarantees, consistently with the capital market financing, and assess the impact of repossession delays on credit spreads. This analysis leads to a policy insight suggesting that bankruptcy laws limiting asset repossession delays lead to lower costs of asset financing.     

Asymmetric benchmarking in bank credit rating

This study proposes an information asymmetry hypothesis to examine why bank credit ratings vary among countries even when bank financial ratios remain constant. Countries are divided among those with low and high information asymmetry. The former include high-income countries, those in North America and West Europe regions, and those with strong institutional environment quality, whereas the latter group possess the opposite characteristics. This study hypothesizes that the influences of financial ratios on ratings are enhanced in low information asymmetry countries but reduced in countries with high information asymmetry. The sample includes the long-term credit ratings issued by Standard and Poor's from 86 countries during 2002-2008. The estimated results show that the effects of financial ratios on ratings are significantly affected by information asymmetries. Countries wishing to improve the credit ratings of their banks thus should reduce information asymmetry.     

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.     

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.     

The impact of credit rating announcements on credit default swap spreads

We document the ability of the credit default swap (CDS) market to anticipate favorable as well as unfavorable credit rating change (RC) announcements based on more extensive samples of credit rating events and CDS spreads than previous studies. We obtain four new results. In contrast to prior published studies, we find that corporate RC upgrades do have a significant impact on CDS spreads even though they are still not as well anticipated as downgrades. Second, CreditWatch (CW) and Outlook (OL) announcements, after controlling for prior credit rating events, lead to significant CARs at the time positive CW and OL credit rating events are announced. Third, we extend prior results by showing that changes in CDS spreads for non-investment-grade credits contain information useful for estimating the probability of negative credit rating events. Fourth, we find that the CDS spread impact of upgrades but not downgrades is magnified during recessions and that upgrades and downgrades also differ as to the impact of simultaneous CW/OL announcements, investment-grade/speculative-grade crossovers, current credit rating, market volatility, and industry effects.     

Capital requirements under the credit risk-based framework

This work aims to study the hypothesis of lower capitalization of banks under the risk-based rules introduced in Basel II. In this sense, an assessment of the impact of these rules on the capital requirements for non-financial firms’ credit risk is performed. A comparison with Basel I is presented and intervals of variation for the risk drivers such that capital requirements exceed the ones under Basel I are established. Data for a European country supports the hypothesis of a smaller capitalization of banks under the risk-based framework, as far as credit risk in concerned.     

The evolution of cost-productivity and efficiency among US credit unions

Advances in information-processing technology have eroded the advantages of small scale and proximity to customers that traditionally enabled small lenders to thrive. Nonetheless, the membership and market share of US credit unions have increased, though their average size has also risen. We investigate changes in the efficiency and productivity of US credit unions during 1989–2006 by benchmarking the performance of individual firms against an estimated order-α quantile lying “near” the efficient frontier. We construct a cost analog of the Malmquist productivity index, which we decompose to estimate changes in cost and scale efficiency, and changes in technology. We find that cost-productivity fell on average across all credit unions but especially among smaller credit unions. Smaller credit unions confronted a shift in technology that increased the minimum cost required to produce given amounts of output. All but the largest credit unions also became less scale efficient over time.     

A framework for assessing the systemic risk of major financial institutions

In this paper we propose a framework for measuring and stress testing the systemic risk of a group of major financial institutions. The systemic risk is measured by the price of insurance against financial distress, which is based on ex ante measures of default probabilities of individual banks and forecasted asset return correlations. Importantly, using realized correlations estimated from high-frequency equity return data can significantly improve the accuracy of forecasted correlations. Our stress testing methodology, using an integrated micro–macro model, takes into account dynamic linkages between the health of major US banks and macro-financial conditions. Our results suggest that the theoretical insurance premium that would be charged to protect against losses that equal or exceed 15% of total liabilities of 12 major US financial firms stood at $110 billion in March 2008 and had a projected upper bound of $250 billion in July 2008.     

Financial guarantors’ executive compensation,charter value and risk-taking

Financial guarantees have been extensively used recently as part of rescue packages to bail out troubled institutions and governments around the world. We propose a new incentive compensation model for studying agency conflict between the shareholders and the manager of a typical financial guarantor. In our model, the manager chooses the guarantor's risk level, with disutility to reduce risk (i.e., reducing the risk of the guarantor incurs a direct cost to the manager). Moral hazard causes the manager to select a level of risk that is higher than the level chosen in an otherwise first-best environment with no conflict of interest between the shareholders and the manager. However, in our proposed framework, charter value plays a self-disciplining role on the manager's appetite for risk, therefore it helps mitigate the extent of the deviation from first best with agency conflict found previously (e.g., 0055, 0015 and 0020). This suggests that researchers should study charter value, managerial compensation and risk decisions within a unified framework and not separately, as all studies have done in the past.     

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.     

Hedging structured credit products during the credit crisis: A horse race of 10 models

Pricing and hedging structured credit products poses major challenges to financial institutions. This paper puts several valuation approaches through a crucial test: How did these models perform in one of the worst periods of economic history, September 2008, when Lehman Brothers went under? Did they produce reasonable hedging strategies? We study several bottom-up and top-down credit portfolio models and compute the resulting delta hedging strategies using either index contracts or a portfolio of single-name CDS contracts as hedging instruments. We compute the profit-and-loss profiles and assess the performances of these hedging strategies. Among all 10 pricing models that we consider the Student-t copula model performs best. The dynamical generalized-Poisson loss model is the best top-down model, but this model class has in general problems to hedge equity tranches. Our major finding is however that single-name and index CDS contracts are not appropriate instruments to hedge CDO tranches.