From equity to default correlation with taxes

For fixed income investment, the preponderant risk is the clustering of defaults in the portfolio. Accurate prediction of such clustering depends on the knowledge of default correlation. We develop models with exogenous debt and endogenous debt to predict default correlations from equity correlations based on a self-consistent structural framework. We also examine how taxes affect the prediction of default correlations based on the two models. The empirical analysis shows that the corporate taxes tend to decrease default correlations, while personal taxes could increase or decrease default correlations. Our default correlation model with exogenous debt does a better job of predicting default correlations for high quality bonds, while the one with endogenous debt predicts more accurately for lower rated bonds. Our studies not only theoretically improve the modeling of default correlation in the structural setting but also shed new light on various aspects of default correlations and thereby help financial practitioners price credit derivatives more accurately and formulate more effective strategies to manage default risk of credit portfolios.     

Credit Risk in Private Debt Portfolios

Default, loss severity, and average loss rates for a large sample of privately placed bonds are presented and compared with loss experience for publicly issued bonds. The chance of very large portfolio losses is estimated and some determinants of such losses are analyzed. Results show ex ante riskier classes of private debt perform better on average than public debt. Both diversification and the riskiness of individual portfolio assets influence the bad tail of the portfolio loss distribution. Private placements are similar to corporate loans in that both are monitored private debt. The results are thus relevant to management and securitization of private debt portfolios generally.     

Distressed debt prices and recovery rate estimation

This paper has two purposes. First, it uses distressed debt prices to estimate recovery rates at default. In this regard, estimates are obtained for three recovery rate models: recovery of face value, recovery of Treasury, and recovery of market value. We show that identifying the “economic” default date, as distinct from the recorded default date, is crucial to obtaining unbiased estimates. The economic default date is defined to be the first date when the market prices the firm’s debt as if it has defaulted. An implication is that the standard industry practice of using 30-day post default prices to compute recovery rate yields biased estimates. Second, we construct and estimate a distressed debt pricing model. We use this model to implicitly estimate the parameters of the embedded recovery rate process and to price distressed debt. Our distressed debt pricing model fits market prices well, with an average pricing error of less than one basis point.      

Cyclical correlations, credit contagion, and portfolio losses

We model aggregate credit losses on large portfolios of financial positions contracted with firms subject to both cyclical default correlation and direct default contagion processes. Cyclical correlation is due to the dependence of firms on common economic factors. Contagion is associated with the local interaction of firms with their business partners. We provide an explicit normal approximation of the distribution of portfolio losses. We quantify the relation between the variability of global economic fundamentals, strength of local firm interaction, and the fluctuation of losses. We find that cyclical oscillations in fundamentals dominate average losses, while local interaction causes additional fluctuations of losses around their average. The strength of the contagion-induced loss variability depends on the complexity of the business partner network.     

Rollover Risk and Credit Risk

Our model shows that deterioration in debt market liquidity leads to an increase in not only the liquidity premium of corporate bonds but also credit risk. The latter effect originates from firms' debt rollover. When liquidity deterioration causes a firm to suffer losses in rolling over its maturing debt, equity holders bear the losses while maturing debt holders are paid in full. This conflict leads the firm to default at a higher fundamental threshold. Our model demonstrates an intricate interaction between the liquidity premium and default premium and highlights the role of short‐term debt in exacerbating rollover risk.     

The Default Premium and Corporate Bond Experience

The development of organized markets for speculative-grade corporate debt has provided financial researchers with an opportunity to examine the pricing of default risk. By incorporating previous work on the default experience of low-rated corporate debt, this paper presents an introduction to risk-neutral models of risky-bond pricing and uses these to examine the relationship between the default premium embodied in bond yields and actual default rates. The contribution of macroeconomic information to the default premium is also examined. The author finds that holders of low-grade bonds have, on average, been compensated for losses due to default.     

FINANCIAL REPORTING BY FOUR UK CLEARING BANKS: A CASH FLOW EXIT PRICE (CaFE) APPROACH

This paper examines the published accounts of the four main UK clearing banks during the 1980s and investigates some of the economic factors with which the banks had to contend. A particular focus concerns less developed country (LDC) debt, provisions against losses on the clearing banks' LDC debt portfolios and factors which might influence the timing of provisions. We find a significant and positive association between share returns and future changes in cash flow plus adjustment for exit price changes, and suggest that this measure may be more closely associated with market expectations than changes in reported profit.     

民营企业债务违约是内因驱动吗？——基于短贷长投和多元化经营视角的分析

不同于以往从外部因素的角度关注民营企业债务问题,本文从企业自身行为出发分析了民企债务违约是否由内因驱动。具体地,本文考察了短贷长投和多元化经营对民营企业债务违约的影响。结果发现,总体上短贷长投以及多元化程度提高了民企债务违约的可能性。从传导机制上看,短贷长投和多元化降低了企业的盈利水平、提高了过度负债、增加了代理成本,并通过以上三个渠道提高了企业债务违约的可能性。从异质性结果来看,信贷紧缩会加大短贷长投对债务违约的促进作用。对于政府支持的行业而言,短贷长投和多元化引发的债务违约问题更严重。最后,更多的短贷长投和多元化在决策得当情况下不会引发债务违约风险。本文的结果表明,民营企业债务违约主要是由内因驱动,即由企业在“求大”“上层次”的心理下实施的粗放式发展模式驱动。本文对于追溯民企违约的根源、精准施策进而更好地支持民企发展具有一定的启示。     

A Macrofinance View of U.S. Sovereign CDS Premiums

Premiums on U.S. sovereign credit default swaps (CDS) have risen to persistently elevated levels since the financial crisis. We examine whether these premiums reflect the probability of a fiscal default—a state in which a balanced budget can no longer be restored by raising taxes or eroding the real value of debt by increasing inflation. We develop an equilibrium macrofinance model in which the fiscal and monetary policy stances jointly endogenously determine nominal debt, taxes, inflation, and growth. We show that the CDS premiums reflect the endogenous risk-adjusted probabilities of fiscal default. The calibrated model is consistent with elevated levels of CDS premiums but leaves dynamic implications quantitatively unresolved.     

Identifying the determinants of mortgage default in Colombia between 1997 and 2004

This paper examines the relationship between mortgage default decisions and relevant observable variables in Colombia between 1997 and 2004. We estimate a discrete choice model of default using a panel of individual mortgage characteristics and payment information. We show that home prices and debt balances are the main determinants of mortgage default. We account for the presence of unobserved heterogeneity using Survey data and simulation techniques. Including controls for the distribution of income shows that income was not important but helps clarifying the relevance of mortgage leverage in the determination of the observed default rates.     

Copula‐Based Formulas to Estimate Unexpected Credit Losses (The Future of Basel Accords?)

The model used to estimate the capital required to cover unexpected credit losses in financial institutions (Basel II) has some drawbacks that reduce its ability to capture potential joint extreme losses in downturns. This paper suggests an alternative approach based on Copula Theory to overcome such flaws. Similarly to Basel II, the suggested model assumes that defaults are driven by a latent variable which varies as a response to an unobserved factor. On the other hand, the use of copulas allows the identification of asymmetric dependence between defaults which has been registered in the literature. As an example, a specific copula family (Clayton) is adopted to represent the association between the latent variables and a formula to estimate potential unexpected losses at a certain level of confidence is derived. Simulations reveal that, in most of the cases, the alternative model outperforms Basel II for portfolios with right‐tail‐dependent probabilities of default (supposedly, a good representation for real loan portfolios).     

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.     

Forecasting forward defaults: a simple hazard model with competing risks

A forward default prediction method based on the discrete-time competing risk hazard model (DCRHM) is proposed. The proposed model is developed from the discrete-time hazard model (DHM) by replacing the binary response data in DHM with the multinomial response data, and thus allowing the firms exiting public markets for different causes to have different effects on forward default prediction. We show that DCRHM is a reliable and efficient model for forward default prediction through maximum likelihood analysis. We use actual panel data-sets to illustrate the proposed methodology. Using an expanding rolling window approach, our empirical results statistically confirm that DCRHM has better and more robust out-of-sample performance than DHM, in the sense of yielding more accurate predicted number of forward defaults. Thus, DCRHM is a useful alternative for studying forward default losses on portfolios.     

Incorporating Collateral Value Uncertainty in Loss Given Default Estimates and Loan-to-value Ratios

We present a model of risky debt in which collateral value is correlated with the possibility of default. The model is then used to study the expected loss given default, primarily as a function of collateral. The results obtained could prove useful for estimating losses given default in many popular models of credit risk which assume them constant. We also examine the problem of determining sufficient collateral to secure a loan to a desired extent. In addition to bank practitioners, regulators might find our analysis useful in reviewing banks’ lending standards relative to current collateral values. In particular, the current proposals for The New (Basel) Capital Accord involve options for the use of banks’ own loss given default estimates which might benefit from the analysis in this paper.     

Efficient hybrid methods for portfolio credit derivatives

In this paper we discuss the computation of basket credit default swaps and collateralized debt obligation squared transactions. We suggest two hybrid algorithms for these two portfolio credit derivatives. The method combines the analytic approximation to the loss distribution of conditionally independent heterogeneous portfolios with the Monte Carlo simulation. The efficiency and accuracy of the algorithms are illustrated with examples.     

Tranching and Rating

In this paper we analyse the source and magnitude of marketing gains from selling structured debt securities at yields that reflect only their credit ratings, or specifically at yields on equivalently rated corporate bonds. We distinguish between credit ratings that are based on probabilities of default and ratings that are based on expected default losses. We show that subdividing a bond issued against given collateral into subordinated tranches can yield significant profits under the hypothesised pricing system. Increasing the systematic risk or reducing the total risk of the bond collateral increases the profits further. The marketing gain is generally increasing in the number of tranches and decreasing in the rating of the lowest rated tranche.     

Leverage Choice and Credit Spreads when Managers Risk Shift

We model the debt and asset risk choice of a manager with performance‐insensitive pay (cash) and performance‐sensitive pay (stock) to theoretically link compensation structure, leverage, and credit spreads. The model predicts that optimal leverage trades off the tax benefit of debt against the utility cost of ex‐post asset substitution and that credit spreads are increasing in the ratio of cash‐to‐stock. Using a large cross‐section of U.S.‐based corporate credit default swaps (CDS) covering 2001 to 2006, we find a positive association between cash‐to‐stock and CDS rates, and between cash‐to‐stock and leverage ratios.     

Creating Fama and French Factors with Style

This paper utilizes Frank Russell style portfolios to create useful proxies for the Fama and French (1992) factors. The proxy‐mimicking portfolios are shown to represent a pervasive source of exposure across U.S. industry portfolios and to generally possess similar properties to those utilized in the finance literature. Further, a set of multivariate asset‐pricing tests of the three‐factor Fama and French asset‐pricing (FF) model based on the proxy factors fails to reject the model. However, these tests do not reveal strong evidence of significantly positive risk premiums, particularly in the case of the size and book‐to‐market factors.     

Settling Defaults in the Era of Bond Finance

Comparisons of the debt crises of the 1930s and 1980s emphasizethe greater incidence of default and the greater ease of restructuringhalf a century ago. The difficulty developing-country debtorshave had in putting the current crisis behind them, it is argued,is due to the more systematic involvement of creditor-countrygovernments and intergovernment agencies. This article reviewsthe negotiating strategies of the debtors and creditors of the1930s, the terms of settlement, and the realized rates of returnon U.S. and U.K. foreign bonds. It shows that rather than beingsharp and complete, default in the 1930s was often partial andintermittent. Uncertainty about debt, trade, and export creditslingered on. Often many years passed before final settlementswere achieved. Creditor-country governments were intimatelyinvolved in the settlement process, although their influencewas not always to the benefit of the bondholders.     

Precautionary Savings with Risky Assets: When Cash Is Not Cash

U.S. industrial firms invest heavily in noncash, risky financial assets such as corporate debt, equity, and mortgage‐backed securities. Risky assets represent 40% of firms’ financial portfolios, or 6% of total book assets. We present a formal model to assess the optimality of this behavior. Consistent with the model, risky assets are concentrated in financially unconstrained firms holding large financial portfolios, are held by poorly governed firms, and are discounted by 13% to 22% compared to safe assets. We conclude that this activity represents an unregulated asset management industry of more than $1.5 trillion, questioning the traditional boundaries of nonfinancial firms.