Pricing default swaps: Empirical evidence

In this paper we compare market prices of credit default swaps with model prices. We show that a simple reduced form model outperforms directly comparing bonds' credit spreads to default swap premiums. We find that the model yields unbiased premium estimates for default swaps on investment grade issuers, but only if we use swap or repo rates as proxy for default-free interest rates. This indicates that the government curve is no longer seen as the reference default-free curve. We also show that the model is relatively insensitive to the value of the assumed recovery rate.     

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.     

The Federal Reserve and the 2007–2009 Financial Crisis: Treating a Virus with Antibiotics? Evidence from the Commercial Paper Market

The two main explanations for the crisis in the commercial paper (CP) market are credit concerns and liquidity issues. The CP market is not homogeneous in terms of credit quality, maturities and types of issues. We find that lower credit‐quality CP suffered more during the crisis. Additionally, we find little evidence that Federal Reserve (Fed) liquidity facilities reduced the impact of the crisis, but that when the Fed became a lender in the CP market, the crisis pressures were dramatically reduced. We conclude that the crisis in the money markets is related more to increases in credit risk. Liquidity is a secondary issue.     

A two-stage dynamic credit scoring model,based on customers’ profile and time horizon

As credit card usage has expanded rapidly worldwide, credit scoring has become a very important task for banks, which can benefit from reducing possible risks of default. Credit scoring models help decision makers to decide whether to issue a credit card to a new applicant on the basis of both financial and nonfinancial criteria. The scope of the current study is to develop a dynamic scoring model that (a) estimates the credit performance of an applicant using generalised linear models and (b) accommodates the changes of a borrower's characteristics after the issuance of the credit card and forecasts the time of default using survival analysis.     

Do Rating Agencies Benefit from Providing Higher Ratings? Evidence from the Consequences of Municipal Bond Ratings Recalibration

We ask whether credit rating agencies receive higher fees and gain greater market share when they provide more favorable ratings. To investigate this question, we use the 2010 rating scale recalibration by Moody's and Fitch, which increased ratings absent any underlying change in issuer credit quality. Consistent with prior research, we find that the recalibration allowed the clients of Moody's and Fitch to receive better ratings and lower yields. We add to this evidence by showing that the recalibration also led to larger fees and to increases in the market shares of Moody's and Fitch. These results are consistent with critics’ concerns about the effects of the issuer‐pay model on the credit ratings market.     

Bond Market Access,Credit Quality,and Capital Structure: Canadian Evidence

We examine the impact of bond market access (measured by having a credit rating) on leverage for Canadian high credit quality (HQ) and low credit quality (LQ) firms, and find that the leverage impact is more pronounced for LQ firms. The results are similar for U.S. firms. Our results are confirmed when we control for the firm's credit quality, examine the change in leverage around rating initiation, and account for the issue size effect. A similar leverage impact for Canadian and U.S. LQ firms suggests that the Canada‐U.S. bond market integration has mitigated the financial constraints for Canadian LQ firms.     

A bridge from ruin theory to credit risk

The structural model uses the firm-value process and the default threshold to obtain the implied credit spread. Merton’s (J Finance 29:449–470, 1974) credit spread is reported too small compared to the observed market spread. Zhou (J Bank Finance 25:2015–2040, 2001) proposes a jump-diffusion firm-value process and obtains a credit spread that is closer to the observed market spread. Going in a different direction, the reduced-form model uses the observed market credit spread to obtain the probability of default and the mean recovery rate. We use a jump-diffusion firm-value process and the observed credit spread to obtain the implied jump distribution. Therefore, the discrepancy in credit spreads between the structural model and the reduced-form model can be removed. From the market credit spread, we obtain the implied probability of default and the mean recovery rate. When the solvency-ratio process in credit risk and the surplus process in ruin theory both follow jump-diffusion processes, we show a bridge between ruin theory and credit risk so that results developed in ruin theory can be used to develop analogous results in credit risk. Specifically, when the jump is Logexponentially distributed, it results in a Beta distributed recovery rate that is close to market experience. For bonds of multiple seniorities, we obtain closed-form solutions of the mean and variance of the recovery rate. We prove that the defective renewal equation still holds, even if the jumps are possibly negative. Therefore, we can use ruin theory as a methodology for assessing credit ratings.      

The Information Content of Ratings: An Analysis of Australian Credit Default Swap Spreads

We examine the information content of Australian credit rating announcements by measuring the abnormal changes in credit default swap (CDS) spreads. CDS spreads provide a direct view of credit quality and thus should impound information quickly when investors receive new credit risk related information via a rating event. Using an event study methodology, we show that watch downs and rating upgrades contain valuable information even after controlling for sources of contamination. We find that watch downs elicit statistically significant market reactions, while subsequent downgrades are anticipated. Upgrades are associated with a significant but small abnormal reduction in CDS spreads, whereas watch ups appear to contain no new information.     

Price discovery of credit spreads in tranquil and crisis periods

In this paper we investigate the price discovery process in single-name credit spreads obtained from bond, credit default swap (CDS), equity and equity option prices. We analyse short term price discovery by modelling daily changes in credit spreads in the four markets with a vector autoregressive model (VAR). We also look at price discovery in the long run with a vector error correction model (VECM). We find that in the short term the option market clearly leads the other markets in the sub-prime crisis (2007–2009). During the less severe sovereign debt crisis (2009–2012) and the pre-crisis period, options are still important but CDSs become more prominent. In the long run, deviations from the equilibrium relationship with the option market still lead to adjustments in the credit spreads observed or implied from other markets. However, options no longer dominate price discovery in any of the periods considered. Our findings have implications for traders, credit risk managers and financial regulators.     

Banks' consumer lending reaction to fintech and bigtech credit emergence in the context of soft versus hard credit information processing

Access to credit information and the ability to process this information effectively determine the conditions of competition in the credit market. Traditionally, local banks have had an advantage in relationship lending (based on soft credit information), whereas foreign banks are considered to base on hard credit information. With the advent of financial technology (or “fintech”) companies (or “fintechs”) and giant technology (or “bigtech”) companies (or “bigtechs”) providing alternative credit, the conditions of competition in the credit market have changed. In this empirical study, we shed light on the nature of the information advantages fintech and bigtech companies have compared to banks and how alternative lenders use them. We analyze competition in the consumer lending segment between banks and fintechs as well as bigtechs providing alternative lending. We used a database combining bank-level characteristics and country-level proxies for 72 countries from 2013 to 2018. We find that in developed markets, the relationships between fintech and bigtech credit providers and banks are similar and competitive in nature. However, banks' consumer lending grows simultaneously with fintech credit market development in emerging economies, but decreases in the aftermath of the emergence of bigtech credit. Fintech credit seems to penetrate market segments not serviced by banks; thus, it plays a complementary role, however only in emerging economies. Bigtech companies compete even more with banks and push some banking offers out of the market, both in emerging and developed economies. Furthermore, we show that domestic and privately-owned banks are more negatively affected by competition from technology-based lending, particularly bigtech, than foreign banks. Thus, bigtech lending may be treated as a serious competition for banks' relationship lending based on soft credit information processing, traditionally provisioned by local banks.     

Liquidity and CDS premiums on European companies around the Subprime crisis

This paper sheds new light on the liquidity dynamics of the credit default swaps (CDS) market in Europe around the Subprime crisis. Based on an original dataset of 94 European companies from 2005 to 2009, we use a panel regression analysis to study the relationship between CDS premiums and liquidity. We measure the level of liquidity, look at liquidity risk, and study the liquidity spillovers from the bond and equity markets to the CDS market. We show that the effect of liquidity on CDS premiums is dominated by the influence of worsening credit conditions and deteriorating investors?? expectations about default risk. Controlling for credit risk, we also find that liquidity risk is priced in the European CDS market and that liquidity spillovers from the bond market matter in determining CDS premiums.     

Credit Scoring and the Availability of Small Business Credit in Low‐ and Moderate‐Income Areas

This paper estimates that credit scoring is associated with about a $3,900 increase in small business lending per sample banking organization, per low‐ and moderate‐income (LMI) area served, and this effect is roughly equivalent to that estimated for higher‐income areas. For our sample, this corresponds to a $536 million increase in small business credit in LMI areas in 1997 than otherwise would have been the case. This effect appears to be driven by increased out‐of‐market lending by banking organizations, as in‐market lending generally declines. Overall, it does not appear that credit scoring has a disparate impact on LMI areas.     

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.     

Measuring Integrated Market and Credit Risk in Bank Portfolios: An Application to a Set of Hypothetical Banks Operating in South Africa

The banking crises of the ‘90s emphasize the need to model the connections between financial environment volatility and the potential losses faced by financial institutions resulting from correlated market and credit risks. Due to the number of variables that must be modeled and the complexity of the relationships an analytical solution is not feasible. We present here a numerical solution based on a simulation model that explicitly links changes in the relevant variables that characterize the financial environment and the distribution of possible future bank capital ratios. This forward looking quantitative risk assessment methodology allows banks and regulators to identify potential risks before they materialize and make appropriate adjustments to bank portfolio credit qualities, sector and region concentrations, and capital ratios on a bank by bank basis. It also has the potential to be extended so as to assess the risks of correlated failures among a group of financial institutions (i.e., systemic risk analyses). This model was applied by the authors to the study of the risk profile of the largest South African Banks in the context of the Financial System Stability Assessment program undertaken by the IMF in 1999. In the current study, we apply the model to various hypothetical banks operating in the South African financial environment and assess the correlated market and credit risks associated with business lending, mortgage lending, asset and liability maturity matches, foreign lending and borrowing, and direct equity, real estate, and gold investments. It is shown to produce simulated financial environments (interest rates, exchange rates, equity indices, real estate price indices, commodity prices, and economic indicators) that match closely the assumed parameters, and generate reasonable credit transition probabilities and security prices. As expected, the credit quality and diversification characteristics of the loan portfolio, asset and liability maturity mismatches, and financial environment volatility, are shown to interact to determine bank risk levels. We find that the credit quality of a bank's loan portfolio is the most important risk factor. We also show the risk reduction benefits of diversifying the loan portfolio across various sectors and regions of the economy and the importance of accounting for volatility shocks that occur periodically in emerging economies. Banks with high credit risk and concentrated portfolios are shown to have a high risk of failure during periods of financial stress. Alternatively, banks with lower credit risk and broadly diversified loan portfolios across business and mortgage lending are unlikely to fail even during very volatile periods. Asset and liability maturity mismatches generally increase bank risk levels. However, because credit losses are positively correlated with interest rate increases, banks with high credit risk may reduce overall risk levels by holding liabilities with longer maturities than their assets. Risk assessment methodologies which measure market and credit risk separately do not capture these various interactions and thus misestimate overall risk levels.     

基于拒绝推论的小企业信用评分模型研究

在小企业信用评分模型的构建中,因数据缺失和样本选择性偏差可能导致模型参数估计有偏,对模型的预测能力和应用会有很大影响。本文利用从万德数据库中筛选出的小企业信息资料,模拟银行信贷筛选,产生带有缺失数据的模拟信贷样本,利用Heckman二阶段模型预测新的信用评分模型,将其结果与忽略缺失数据的审查模型和基于完全信息的标准模型进行比较。结果显示,Heckman二阶段模型的表现优于直接忽略缺失样本数据的审查模型,更接近标准模型的结果。这表明拒绝推论能够有效解决信用评分建模中数据缺失导致的样本选择偏差,提高信用评分模型的有效性和预测能力。     

The Slope of the Credit Yield Curve for Speculative-Grade Issuers

Many theoretical bond pricing models predict that the credit yield curve facing risky bond issuers is downward-sloping. Previous empirical research (Sarig and Warga (1989), Fons (1994)) supports these models. Our study examines sets of bonds issued by the same firm with equal priority in the liability structure, but with different maturities, thus holding credit quality constant. We find, counter to prior research, that risky bonds typically have upward-sloping credit yield curves. Moreover, when we combine our matched sets of bonds (no longer controlling credit quality), the estimated slope is negative, indicating a sample selection bias problem associated with maturity.     

金融中介机构竞争的市场反应--来自信用评级机构的证据北大核心

目前已有研究认为金融中介机构竞争会带来市场效率的提高,本文利用2012-2017年债券市场的微观数据研究“发行人付费”模式评级机构之间的竞争对评级结果的影响。研究发现,评级机构竞争会导致评级结果膨胀与评级质量下降。进一步研究发现,当评级竞争加剧时,“发行人付费”模式的评级机构会对有较多业务联系的企业放松评级标准,给予更高信用评级。我们的研究也发现评级机构的外资背景、承销商的良好声誉和媒体关注均有助于减小“发行人付费”模式下评级机构竞争的负面影响。同时,债券市场评级竞争还存在对股票市场的溢出效应,评级竞争导致的评级质量下降也降低了股票市场的信息效率。这说明,“发行人付费”模式下的评级机构竞争会降低资本市场的信息效率,“投资者付费”模式的推广和评级行业的对外开放有助于改善国内评级行业的评级质量。本文的研究也为国内债券市场进一步发挥双评级、多评级以及不同模式评级的交叉验证作用提供了一定证据支持。     

Intensified Competition and The Impact on Credit Ratings in the RMBS market

In this paper, we empirically investigate the impact of intensified competition on rating quality in the credit rating market for residential mortgage-backed securities (RMBS) in the period 2017–2020. We provide evidence that competition between large credit rating agencies (CRAs) (Moody's and Standard & Poor's) and newer smaller ones (Dominion Bond Rating Service Morningstar and Kroll Bond Rating Agency) creates credit rating inconsistencies in the RMBS market. While a credit rating should solely represent the underlying credit risk of a RMBS, irrespective of the competition in the market, our results show that this is not the case. When competitive pressure is higher, both large and small CRAs tend to adjust their rating standards (smaller CRAs react to large CRAs and vice versa).     

The Co‐movement of Credit Default Swap,Bond and Stock Markets: an Empirical Analysis

We analyse the relationship between credit default swap (CDS), bond and stock markets during 2000–2002. Focusing on the intertemporal co‐movement, we examine monthly, weekly and daily lead‐lag relationships in a vector autoregressive model and the adjustment between markets caused by cointegration. First, we find that stock returns lead CDS and bond spread changes. Second, CDS spread changes Granger cause bond spread changes for a higher number of firms than vice versa. Third, the CDS market is more sensitive to the stock market than the bond market and the strength of the co‐movement increases the lower the credit quality and the larger the bond issues. Finally, the CDS market contributes more to price discovery than the bond market and this effect is stronger for US than for European firms.     

On the Term Structure of Default Premia in the Swap and LIBOR Markets

Existing theories of the term structure of swap rates provide an analysis of the Treasury–swap spread based on either a liquidity convenience yield in the Treasury market, or default risk in the swap market. Although these models do not focus on the relation between corporate yields and swap rates (the LIBOR–swap spread), they imply that the term structure of corporate yields and swap rates should be identical. As documented previously (e.g., in Sun, Sundaresan, and Wang (1993)) this is counterfactual. Here, we propose a model of the default risk imbedded in the swap term structure that is able to explain the LIBOR–swap spread. Whereas corporate bonds carry default risk, we argue that swap contracts are free of default risk. Because swaps are indexed on "refreshed"-credit-quality LIBOR rates, the spread between corporate yields and swap rates should capture the market's expectations of the probability of deterioration in credit quality of a corporate bond issuer. We model this feature and use our model to estimate the likelihood of future deterioration in credit quality from the LIBOR–swap spread. The analysis is important because it shows that the term structure of swap rates does not reflect the borrowing cost of a standard LIBOR credit quality issuer. It also has implications for modeling the dynamics of the swap term structure.