This paper creates default-probability-(PD)-implied credit ratings for Chinese firms following the S&P global rating standard. The domestic credit rating agency (DCRA) ratings are higher than the PD-implied ratings by ten notches on average for the identical level of default risk, implying that the domestic ratings are significantly inflated. The PD-implied ratings outperform the DCRA ratings in detecting defaults and complement the latter in predicting yield spreads. The PD-implied ratings draw information from operating efficiency-related variables; in contrast, the DCRA ratings pay attention to scale-based firm characteristics in credit risk assessment.

The goal of this paper is to discuss how we establish the “Hammer (CAFÉ) Credit System” by applying Gibbs sampling algorithm under the framework of bigdata approach to extract features in depicting bad or illegal behaviors by following the “five step principle” applying international credit rating standards. In particular, we will show that our Hammer (CAFÉ) Credit System is able to resolve three problems of the current credit rating market in China which rate: “1) the rating is falsely high; 2) the differentiation of credit rating grades is insufficient; and 3) the poor performance of predicting early warning and related issues”. In addition the Hammer (CAFÉ) credit is supported by clearly defining the "BBB" as the basic investment level with annualized rate of default probability in accordance with international standards in the practice of financial industries, and the credit transition matrix for “AAA-A” to “CCC-C” credit grades.

This paper uses a loan transactions dataset from China to identify whether shadow loans cost more than formal bank loans even with collateral. This motivates us to explore the reasons as to why a listed firm would opt for such loans. Using propensity-score matched data, we find that privately-owned firms with shadow loans are forced to obtain these loans since they are politically discriminated following a regulation change in 2009 that favoured state-owned firms. However, state-owned firms obtain shadow loans due to their inferior firm characteristics. Further, we employ a Difference-in-Differences methodology to uncover that privately-owned firms experience a decline in their performance, investment growth and an increase in default probability following their high dependence on shadow loans when they are excluded from the formal loan market. The above results survive various robustness checks, including doubly-robust inverse-probability weighted Difference-in-Differences regressions.

This study documents a pervasive inverse relationship between asset growth rates and bond performance among non-investment and low-investment grade bonds. We argue such inverse relation holds ex ante considering a high growth rate in firm total assets results in growth in tangible assets and lowers bond default probabilities. Our empirical finding supports this hypothesis. Tangible asset growth of poorly rated bonds is negatively associated with contemporaneous bond performance and expected default probability. The finding is robust to different economic conditions and investment sentiments.

ABSTRACT：As an important derivative instrument, CDO is playing a crucial role in the financial crisis. With complicated structure, we have developed many pricing models, which all relay on complicated mathematical model. The paper, firstly, introduces the mainstream pricing model----structural model and reduced form model. Then we introduced the Hybrid Models based on two formal models, by discussing the parameter of pricing i.e. default probability, default free risk and default correlation. In this paper, we give the hybrid model by Monte Carlo simulation based on copula function. Finally, we consider the pricing sensitivity on various parameters. According to the result of simulation, the relationship between the tranches price and pricing parameters is various. For the equity tranche and mezzanine tranche, the price and recovery rate have a positive correlation, while the case is inverse for the senior tranche. We also can conclude that, higher default correlation can lower the price of equity tranche, and have an opposite effect on the senior tranche. The influence on the mezzanine tranche isn’t certain. Furthermore, by comparing two different copula function model, we can get that marginal distribution has different effect on the tranches price.

In this article, we consider a regulated market and explore the default events. By using a so-called reflected Ornstein-Uhlenbeck process with two-sided barriers to formulate the price dynamics, we derive the expression on the conditional default probability. In the cases of single observation and multiple observations, the conditional default probabilities are explicitly expressed in terms of the inverse Laplace transforms. Finally, we present a numerical simulation associated with the conditional default probability.

In this paper, we examine the cost of equity capital for politically connected firms. After controlling for several firm- and country-level determinants, our results show that politically connected firms have a lower cost of equity capital than their nonconnected peers. Our results are robust to alternative measures and proxies for the cost of equity capital. We thus provide strong evidence that investors require a lower cost of capital for politically connected firms, suggesting that these firms are generally considered to be less risky than non-connected firms. Our findings imply that the benefits of political connections outweigh their costs. We conjecture that this perception is fueled by the soft budget constraints generally enjoyed by politically connected firms, and by their lower default probability, given the assurance of corporate bailout in the event of financial downturns.

This is the first study that uses Merton’s (1974) option pricing model to compute default measures for individual firms and assess the effect of default risk on equity returns. The size effect is a default effect, and this is also largely true for the book-to-market (BM) effect. Both exist only in segments of the market with high default risk. Default risk is systematic risk. The Fama-French (FF) factors SMB and HML contain some default-related information, but this is not the main reason that the FF model can explain the cross-section of equity returns.

Stationary-leverage-ratio models of modelling credit risk based on constant target leverage ratios cannot generate probabilities of default which replicate empirically observed default rates. This paper presents a structural model to address this problem. The main feature of the model is that a firm’s leverage ratio is mean-reverting to a time-dependent target leverage ratio. The time-dependent target leverage ratio reflects the firm’s intention of moving its initial target ratio toward a long-term target ratio over time. We derive a closed-form solution of the probability of default based on the model as a function of the firm value, liability and short term interest rate. The numerical results calculated from the solution with simple time-dependent functions of the target leverage ratios show that the model is capable of producing term structures of probabilities of default that are consistent with some empirical findings. This model could provide new insight for future research on corporate bond analysis and credit risk measurement.