Financial Distress in Chinese Industry:Microeconomic, Macroeconomic and Institutional Infuences

We study the impact of both microeconomic factors and the macroeconomy on the financial distress of Chinese listed companies over a period of massive economic transition, 1995 to 2006. Based on an economic model of financial distress under the institutional setting of state protection against exit, and using our own firm-level measure of distress, we find important impacts of firm characteristics, macroeconomic instability and institutional factors on the hazard rate of financial distress. The results are robust to unobserved heterogeneity at the firm level, as well as those shared by firms in similar macroeconomic founding conditions. Comparison with related studies for other economies highlights important policy implications

Financial Distress in Chinese Industry:Microeconomic, Macroeconomic and Institutional Influences

We study the impact of both microeconomic factors and the macroeconomy on the financial distress of Chinese listed companies over a period of massive economic transition, 1995 to 2006. Based on an economic model of financial distress under the institutional setting of state protection against exit, and using our own firm-level measure of distress, we find important impacts of firm characteristics, macroeconomic instability and institutional factors on the hazard rate of financial distress. The results are robust to unobserved heterogeneity at the firm level, as well as those shared by firms in similar macroeconomic founding conditions. Comparison with related studies for other economies highlights important policy implications

POSSIBILITIES OF IMPROVING THE METHODS AND TECHNIQUES USED IN THE SURVEILLANCE OF CREDIT RISK MANAGEMENT

Through their daily activities, credit institutions are subject to various risks which could affect both the bank and the whole banking system, national and transnational. The activity field of the banks, marked by volatility, by the internationalization and liberalization of the financial markets, is in a continuous change. The contagion effect, as it has been proved by the spread of the financial crisis' effects, determines the surveillance authorities to pay increased attention to the financial risks and implicitly to the systemic risk. In this study, to start with, there shall be presented some aspects regarding the banking rating systems used by the surveillance authorities and then some ways of improving the models of managing credit risk in banks. In the end, there will be demonstrated that the risk profile of the banking institution has a determining role in the management of the credit portfolio.banking system, banking risk, surveillance, rating systems, credit portfolio, investment.

An Alternative Methodology for Estimating Credit Quality Transition Matrices

This study presents an alternative way of estimating credit transition matrices using a hazard function model. The model is useful both for testing the validity of the Markovian assumption, frequently made in credit rating applications, and also for estimating transition matrices conditioning on firm-specific and macroeconomic covariates that influence the migration process. The model presented in the paper is likely to be useful in other applications, though we would hesitate to extrapolate numerical values of coefficients outside of our application. Transition matrices estimated this way may be an important tool for a credit risk administration system, in the sense that with them a practitioner can easily forecast the behavior of the clients´ratings in the future and their possible changes of stateFirms; macroeconomic variables; firm-specific covariates; hazard function; transition intensities. Classification JEL: C4; E44; G21; G23; G38.

Hybrid model using logit and nonparametric methods for predicting micro-entity failure

Following the calls from literature on bankruptcy, a parsimonious hybrid bankruptcy model is developed in this paper by combining parametric and non-parametric approaches.To this end, the variables with the highest predictive power to detect bankruptcy are selected using logistic regression (LR). Subsequently, alternative non-parametric methods (Multilayer Perceptron, Rough Set, and Classification-Regression Trees) are applied, in turn, to firms classified as either “bankrupt” or “not bankrupt”. Our findings show that hybrid models, particularly those combining LR and Multilayer Perceptron, offer better accuracy performance and interpretability and converge faster than each method implemented in isolation. Moreover, the authors demonstrate that the introduction of non-financial and macroeconomic variables complement financial ratios for bankruptcy prediction

Credit Risk Drivers: Evaluating the Contribution of Firm Level Information and of Macroeconomic Dynamics

Understanding why some firms default, while others do not, is an important issue for the assessment of financial stability. In this domain, it may be interesting to understand if credit risk is driven mostly by idiosyncratic firm characteristics or by systematic factors, which simultaneously affect all firms. In order to empirically examine the determinants of loan default, we begin by exploring the links between credit risk and macroeconomic developments at an aggregate level. The results obtained seem to confirm the hypothesis that in periods of economic growth, which are sometimes accompanied by strong credit growth, there may be some tendency towards excessive risk-taking, even though the imbalances created in such periods only become apparent when economic growth slows down. After examining the determinants of credit risk at an aggregate level, we focus our attention on an extensive dataset with detailed financial information for more than 30.000 firms. The results obtained suggest that default probabilities are influenced by several firm-specific characteristics, such as their financial structure, profitability and liquidity, as well as by their recent sales performance or their investment policy. When time-effect controls or macroeconomic variables are taken into account together with the firms’ characteristics, the results seem to improve substantially. Hence, though the firms’ financial and operational situation has a central role in explaining default probabilities at the micro level, overall macroeconomic conditions are also very important when assessing default probabilities over time.