Endogenizing exogenous default barrier models: The MM algorithm

In this paper, we propose a Maximization–Maximization (MM) algorithm for the assessment of hidden parameters in structural credit risk models. Step M1 updates the value, volatility, and expected return on the firm’s assets by maximizing the log-likelihood function for the time series of equity prices; Step M2 updates the default barrier by maximizing the equity holders’ participation in the firm’s asset value. The main contribution of the method lies in the M2 step, which allows for ‘endogenizing’ the default barrier in light of actual data on equity prices. Using a large international sample of companies, we demonstrate that theoretical credit spreads based on the MM algorithm offer the lowest CDS pricing errors when compared to other, traditional default barrier specifications: smooth-pasting condition value, maximum likelihood estimate, KMV’s default point, and nominal debt.     

The strategy of professional forecasting

We develop and compare two theories of professional forecasters’ strategic behavior. The first theory, reputational cheap talk, posits that forecasters endeavor to convince the market that they are well informed. The market evaluates their forecasting talent on the basis of the forecasts and the realized state. If the market expects forecasters to report their posterior expectations honestly, then forecasts are shaded toward the prior mean. With correct market expectations, equilibrium forecasts are imprecise but not shaded. The second theory posits that forecasters compete in a forecasting contest with pre-specified rules. In a winner-take-all contest, equilibrium forecasts are excessively differentiated.     

Incorporating the dynamics of leverage into default prediction

A firm’s current leverage ratio is one of the core characteristics of credit quality used in statistical default prediction models. Based on the capital structure literature, which shows that leverage is mean-reverting to a target leverage, we forecast future leverage ratios and include them in the set of default risk drivers. An out-of-sample analysis of default predictions from a hazard model reveals that the discriminative power increases substantially when leverage forecasts are included. We further document that credit ratings contain information beyond the one contained in standard variables but that this information is unrelated to forecasts of leverage ratios.     

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.     

The information content of trade credit

During 1992–2007, suppliers financed almost 10% of the total assets of US listed firms. This intensive usage of trade credit is puzzling in the light of its high (implicit) costs. By arguing that trade credit use provides valuable information to outside investors, we first derive a theoretical model that predicts a positive correlation between trade credit use and the quality of the firm’s investments. Then, using several proxies for firm’s investment quality (Z-score, return on assets, and long-run abnormal returns), we show that this prediction receives strong support from a large sample of US firms.     

The predictability of aggregate returns on commodity futures

This paper provides evidence that aggregate returns on commodity futures (without the returns on collateral) are predictable, both in-sample and out-of-sample, by various lagged variables from the stock market, bond market, macroeconomics, and the commodity market. Out of the 32 candidate predictors we consider, we find that investor sentiment is the best in-sample predictor of short-horizon returns, whereas the level and slope of the yield curve have much in-sample predictive power for long-horizon returns. We find that it is possible to forecast aggregate returns on commodity futures out-of-sample through several combination forecasts (the out-of-sample return forecasting R² is up to 1.65% at the monthly frequency).     

Dispersion in analysts’ earnings forecasts and credit rating

This paper shows that the puzzling negative cross-sectional relation between dispersion in analysts’ earnings forecasts and future stock returns may be explained by financial distress, as proxied by credit rating downgrades. Focusing on a sample of firms rated by Standard & Poor's (S&P), we show that the profitability of dispersion-based trading strategies concentrates in a small number of the worst-rated firms and is significant only during periods of deteriorating credit conditions. In such periods, the negative dispersion–return relation emerges as low-rated firms experience substantial price drop along with considerable increase in forecast dispersion. Moreover, even for this small universe of worst-rated firms, the dispersion–return relation is non-existent when either the dispersion measure or return is adjusted by credit risk. The results are robust to previously proposed explanations for the dispersion effect such as short-sale constraints and leverage.     

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.     

Multiple-days-ahead value-at-risk and expected shortfall forecasting for stock indices,commodities and exchange rates: Inter-day versus intra-day data

In order to provide reliable Value-at-Risk (VaR) and Expected Shortfall (ES) forecasts, this paper attempts to investigate whether an inter-day or an intra-day model provides accurate predictions. We investigate the performance of inter-day and intra-day volatility models by estimating the AR(1)-GARCH(1,1)-skT and the AR(1)-HAR-RV-skT frameworks, respectively. This paper is based on the recommendations of the Basel Committee on Banking Supervision. Regarding the forecasting performances, the exploitation of intra-day information does not appear to improve the accuracy of the VaR and ES forecasts for the 10-steps-ahead and 20-steps-ahead for the 95%, 97.5% and 99% significance levels. On the contrary, the GARCH specification, based on the inter-day information set, is the superior model for forecasting the multiple-days-ahead VaR and ES measurements. The intra-day volatility model is not as appropriate as it was expected to be for each of the different asset classes; stock indices, commodities and exchange rates.The multi-period VaR and ES forecasts are estimated for a range of datasets (stock indices, commodities, foreign exchange rates) in order to provide risk managers and financial institutions with information relating the performance of the inter-day and intra-day volatility models across various markets. The inter-day specification predicts VaR and ES measures adequately at a 95% confidence level. Regarding the 97.5% confidence level that has been recently proposed in the revised 2013 version of Basel III, the GARCH-skT specification provides accurate forecasts of the risk measures for stock indices and exchange rates, but not for commodities (that is Silver and Gold). In the case of the 99% confidence level, we do not achieve sufficiently accurate VaR and ES forecasts for all the assets.     

Corporate fraud and bank loans: Evidence from china

Receiving punishment from regulators for corporate fraud can affect financing contracts between a firm and its bank, as both the firm’s credit risk and information risk increase after punishment. By focusing on Chinese firms’ borrowing behavior after events of corporate fraud, we find that firms’ bank loans after punishment are not only significantly lower, but are also less than those for non-fraudulent firms. In addition, loan interest rates after punishment are not only higher than before, but also higher than those for their non-fraudulent counterparts. In addition, we find that corporate fraud indirectly destabilizes the “performance-bank loan” relationship. Our results suggest that corporate fraud negatively affects a firm’s ability to source debt financing, which provides new evidence about the economic consequences of fraud.     

Bank ownership and lending patterns during the 2008–2009 financial crisis: Evidence from Latin America and Eastern Europe

This paper examines the impact of bank ownership on credit growth in developing countries before and during the 2008–2009 crisis. Using bank-level data for countries in Eastern Europe and Latin America, we analyze the growth of banks’ total gross loans as well as the growth of corporate, consumer, and residential mortgage loans. While domestic private banks in Eastern Europe and Latin America contracted their loan growth rates during the crisis, there are notable differences in foreign and government-owned bank credit growth across regions. In Eastern Europe, foreign bank total lending fell by more than domestic private bank credit. These results are primarily driven by reductions in corporate loans. Furthermore, government-owned banks in Eastern Europe did not act counter-cyclically. The opposite is true in Latin America, where the growth of government-owned banks’ corporate and consumer loans during the crisis exceeded that of domestic and foreign banks. Contrary to the case of foreign banks in Eastern Europe, those in Latin America did not fuel loan growth prior to the crisis. Also, there are less pronounced and robust differences in the behavior of foreign and domestic banks during the crisis in Latin America.     

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.     

Does freezing a defined benefit pension plan affect firm risk?

This paper examines the impact of a defined benefit (DB) pension plan freeze on the sponsoring firm's risk and risk-taking activities. Using a sample of firms declaring a hard freeze on their DB plans between 2002 and 2007, we observe an increase in total risk (proxied by the standard deviation of EBITDA and asset beta), equity risk (standard deviation of returns), and credit risk following a DB-plan freeze. The increase in credit risk is reflected in a decline in credit ratings and an increase in bond yields for freezing firms. When we examine investment strategies, we observe a shift in investment from capital expenditures before the freeze to more-risky R&D projects after the freeze, and an increase in leverage. These strategies (increased focus on R&D and higher leverage) increase the operating and financial risk the firm faces. Overall, we observe an increase in risk-taking following DB plan freezes, consistent with theories that DB plans act as “inside debt” that aligns managers’ interests with bondholders’.     

Using the credit spread as an option-risk factor: Size and value effects in CAPM

This paper takes an option-theoretic approach to explain why pricing anomalies are observed when traditional CAPM is used. By extending CAPM to incorporate the option-risk factor of stocks, we show that stockholders’ limited liability can explain Fama and French’s size and value effects. We use bonds’ excess credit spread as a proxy for stocks’ default risk to control for the changing non-diversifiable option-risk characteristic of stocks. Because sensitivity to the excess credit spread becomes smaller as size increases and as value decreases, excess credit spread explains the CAPM anomalies in a fashion similar to the Fama–French factors. While the excess credit spread is significant in explaining Fama and French’s size and value effects, adding the Fama–French factors does not improve the performance of our model. Our revised model resembles conditional CAPM, but it offers a more intuitive explanation for the size and value effects.     

Sovereign credit spreads

The paper develops a structural credit risk model to study sovereign credit risk and the dynamics of sovereign credit spreads. The model features endogenous default and recovery rates that both depend on the interaction between domestic output fluctuations and global macroeconomic conditions. We show that sovereigns choose to default at higher levels of economic output once global macroeconomic conditions are bad. This yields to default rates and credit spreads that are substantially higher compared to normal times. We derive closed-form expressions for sovereign debt values and default times and focus on the dynamics of sovereign credit spreads. As opposed to standard theories of sovereign debt, this paper’s structural model generates much richer default patterns and non-linearities through regime-shifts in the global macroeconomic environment. Moreover, changes in the global environment reveal the interconnectedness of the financial system.     

Consumer expectations and short-horizon return predictability

Lettau and Ludvigson [Lettau, M., Ludvigson, S, 2001. Consumption, aggregate wealth and expected stock returns. Journal of Finance 56, 815–849] argue that fluctuations from the equilibrium ratio of consumption to wealth (cây) reflect changing expectations of asset returns and document significant short-horizon predictability based on cây. This paper further explores the role of consumer expectations in modeling time variation of expected equity returns by considering two measures of consumer expectations: (i) consumer behavior as reflected in cây, and (ii) a more-direct measure of expectations captured by the Index of Consumer Sentiment (ICS). We report strong regression-based evidence of return predictability based on cây, which remains evident even after accounting for various sources of estimation risk. However, the regression-based evidence of predictability does not necessarily imply that shifts in aggregate consumption and the components of aggregate wealth give rise to economically significant investment signals. The survey-based measure of expectations (ICS) is shown to complement the behavioral measure (cây) but has no apparent stand-alone predictive value in forecasting equity returns.     

Consumer Attitudes and Their Forecasting Power for Consumer Spending

The University of Michigan's Surveys of Consumers is summarized with principal components of consumer attitudes with respect to income and wealth, prices, and interest rates and credit availability. These summary measures contain information beyond that captured by the Index of Consumer Sentiment. The summary measures have forecasting power for aggregate consumption behavior, even when controlling for economic fundamentals. These measures also help to improve significantly upon Survey of Professional Forecasters, Blue Chip Consensus, and Federal Reserve Board's forecasts of consumption and other real activity measures, consistent with their predictive ability conditioned upon a broader set of fundamentals and forecasters’ judgment.     

A comparative study of the probability of default for global financial firms

This article presents a modification of Merton’s (1976) ruin option pricing model to estimate the implied probability of default from stock and option market prices. To test the model, we analyze all global financial firms with traded options in the US and focus on the subprime mortgage crisis period. We compare the performance of the implied probability of default from our model to the expected default frequencies based on the Moody’s KMV model and agency credit ratings by constructing cumulative accuracy profiles (CAP) and the receiver operating characteristic (ROC). We find that the probability of default estimates from our model are equal or superior to other credit risk measures studied based on CAP and ROC. In particular, during the subprime crisis our model surpassed credit ratings and matched or exceeded KMV in anticipating the magnitude of the crisis. We have also found some initial evidence that adding off-balance-sheet derivatives exposure improves the performance of the KMV model.     

Contagion risk in the Australian banking and property sectors

The Australian banking system emerged from the global crisis virtually unhurt, with most banks still profitable, adequately capitalized, and with AA credit ratings. Are there any risks or vulnerabilities in this success story? This paper analyzes Australia’s systemic banking risk and attempts to determine if this risk increased with the recent global crisis and whether this risk is related to the downturn experienced in the real estate market. We use extreme value theory to measure banks’ and property firms’ univariate Value at Risk, as well as multivariate intra-sector and inter-sector contagion risks. Of the 13 sectors analyzed, we find that the property sector exhibits the highest level of extremal dependence with the banking sector. The credit crisis significantly increased the probability of a bank or property firm crashing. Moreover, contagion risks significantly increased not only within the banking and property sectors, but also between those sectors.     

Credit card interchange fees

We build a model of credit card pricing that explicitly takes into account credit functionality. In the model a monopoly card network always selects an interchange fee that exceeds the level that maximizes consumer surplus. If regulators only care about consumer surplus, a conservative regulatory approach is to cap interchange fees based on retailers’ net avoided costs from not having to provide credit themselves. This always raises consumer surplus compared to the unregulated outcome, sometimes to the point of maximizing consumer surplus.