Innovative Approach for Forecasting Corporate Default Risk

Financial mismatch on corporate debt default risk: Evidence from China

Are short selling threats beneficial to creditors? Insights from corporate default risk

The Market Price of Credit Risk

Short-selling and corporate default risk: Evidence from China

Time-Varying Rating Standards and the Distorted Incentives of Credit Rating Agencies

In this study, inspired by the Credit Portfolio View approach, we intend to develop an econometric credit risk model to estimate credit loss distributions of Turkish Banking System under baseline and stress macro scenarios, by substituting default rates with non-performing loan (NPL) ratios. Since customer number based historical default rates are not available for the whole Turkish banking system’s credit portfolio, we used NPL ratios as dependent variable instead of default rates, a common practice for many countries where historical default rates are not available. Although, there are many problems in using NPL ratios as default rates such as underestimating portfolio losses as a result of totally non-homogeneous total credit portfolios and transferring non-performing loans to asset management companies from banks’ balance sheets, our aim is to underline and limit some ignored problems using accounting based NPL ratios as default rates in macroeconomic credit risk modeling. Developed models confirm the strong statistical relationship between systematic component of credit risk and macroeconomic variables in Turkey. Stress test results also are compatible with the past experiences.

This paper presents a developed java android application for KMV-Merton model in predicting the defaut rate of a firm. Predicting default rate is essential in the risk management area as default risk can be immediately transmitted from one entity to another entity. This is the reason default risk is known as a global risk. Although there are several efforts, instruments and methods used to manage the risk, it is said to be insufficient. To the best of our knowledge, there has been limited innovation in developing the default risk mathematical model into a mobile application. Therefore, through this study, default risk is predicted quantitatively using the KMV-Merton model. The KMV-Merton model has been integrated in the form of java program using the Android Studio Software. The developed java android application is tested by predicting the levels of default risk of the three different rated companies. It is found that the levels of default risk are equivalent to the ratings of the respective companies. This shows that the default rate predicted by the KMV-Merton model using the developed java android application can be a significant tool to the risk mangement field. The developed java android application grants users an alternative to predict level of default risk within less procedure.

In contrast to corporate defaults, regulators typically take a number of statutory actions to avoid the large fiscal costs associated with bank defaults. The distance-to-default, a widely used market-based measure of corporate default risk, ignores such regulatory actions. To overcome this limitation, this paper introduces the concept of distance-to-capital that accounts for pre-default regulatory actions such as those in a prompt-corrective-actions framework. We show that both risk measures can be analyzed using the same theoretical framework but differ depending on the level of capital adequacy thresholds and asset volatility. We also use the framework to illustrate pre-default regulatory actions in Japan in 2001-03.

In contrast to corporate defaults, regulators typically take a number of statutory actions to avoid the large fiscal costs associated with bank defaults. The distance-to-default, a widely used market-based measure of corporate default risk, overlooks such regulatory actions. To overcome this limitation, this paper introduces the concept of distance-to-capital that accounts for pre-default regulatory actions such as those prescribed in a prompt-corrective-actions framework. We show that both risk measures can be analysed using the same theoretical framework but differ depending on the level of capital adequacy thresholds and asset volatility. We also use the framework to illustrate pre-default regulatory actions in Japan in 2001–2003.

An accurate forecast for corporate default risk is crucial for financial institutions to effectively quantify potential expected and unexpected borrower losses. This paper develops a logistic regression model to simultaneously examine the roles of firm-specific fundamentals and economic outlook in predicting corporate default risk. The model is estimated using U.S. listed non-financial firms over the 1997⎼2009 period. The empirical findings suggest that economic outlook captured by recession probability forecast, firm-specific fundamental factors measured by the Z-score and F-score, and the interaction between economic outlook and firm-specific fundamental factors play statistically significant roles in predicting bankruptcy risk. The model exhibits relatively high levels of goodness-of-fit and classification ability, and low levels of forecast error.

Does carbon risk travel along the supply chain? Evidence from corporate default risk

This study explores price dynamics and price relationships in the US housing market with a focus on four regions: Northeast, Midwest, South, and West. It applies a multivariate state-space model to identify the common trends and common cycles in US regional markets. The study finds that the principal source of secular price variability in the Northeast and West markets is due to two common stochastic trends, while a large share of transitional price variability in the Northeast, West and Midwest originates from three common stochastic cycles. The study estimates the relationships between the common unobserved components and economic variables and finds that unemployment, federal funds rate, corporate default risk, economic expansion, unanticipated inflation in the construction market are significant underlying economic phenomena that impact the evolution of the common movements in both the short run and the long run housing dynamics.

Does minority shareholder activism impede corporate default risk? Evidence from China

Along with the increasing uncertainty of the global economy and the spread of the new crown pneumonia epidemic, the risk challenges to economic development have increased significantly, and the risk of corporate debt defaults has become more pronounced. As an important component of the capital market, the bond market also began to experience credit bond defaults during this period. Since 2021 the global bond market has shown a sharp increase in defaults, with the default rate of non-state enterprise bonds significantly higher than the overall market, and the capital market has also ushered in a period of pain and accelerated credit risk release. Enterprises are on the verge of bankruptcy restructuring and urgently need the government to provide a bailout and stabilize the market. Therefore, this paper uses the financial data of Chinese listed companies from 2016-2021, constructs a relief intensity variable using the equity pledge rate of listed companies before the relief (2021), and empirically analyzes the impact of local government relief and financing cost on the default risk of listed companies using an intensity double difference model. The results of this study show that: (1) local government bailout significantly reduces the default rate of listed companies by 13%; (2) the effect of local government bailout varies significantly depending on whether listed companies have connected transactions with financing platform companies, and the increase of bailout intensity increases the return on assets of listed companies with related transactions with financing platform companies by 9.8%, which laterally reduces the default rate of corporate debt; (3) the cost of financing is an important mechanism by which local government bailouts affect the credit default rate of listed companies, with a regression correlation of 0.75; (4) the above effect is more pronounced in regions with a higher degree of marketization, with a 9% increase in the effect. The findings of this paper are important for actively managing the risk of dual corporate debt and credit defaults and enhancing the effectiveness of macroeconomic regulation during the epidemic period.

The article raises the issues of developing a relevant tool for financial regulation and supervision – stress testing. Regulatory authorities use different types of testing to assess possible problems, as well as to model the response of supervised institutions to changes in system parameters. At present, the issues of ensuring financial stability are quite acute, and the search for effective analytical tools is an important managerial task, the solution of which is the focus of this study. The purpose of the article is to substantiate the advantages and limitations of this tool and to identify areas for its improvement. The evolution of the tool has been analyzed, and microprudential, macroprudential, and crisis stress tests investigated. The work is based on the data of the International Monetary Fund, as well as the Central Bank of the Russian Federation, the methods of analyzing regulatory documents and comparative economic analysis have been used. Types of stress tests and main stages of stress testing have been systematized. The authors, considering cross-border nature of financial institutions’ activities, conclude that transformation of supervisory tools is desirable and recommend the inclusion of non-banking financial organizations in stress testing, as well as network interactions between financial institutions as the main areas of improvement.