Affect Default Risk Research Articles

Multilayer asset association network, green technical cooperation innovation, and default risk: Evidence from China's high energy-consuming industries

High energy-consuming industries are expected to play a significant role in energy conservation and emissions reduction. This study collects data on China's high energy-consuming listed companies from 2009 to 2022. Using the complex network theory, we construct a multilayer asset association network for high energy-consuming enterprises and examine how different layers and totality affect default risk. The results revealed that node-weighted degree centrality in the asset association networks of high energy-consuming enterprises, particularly in the guarantee association network, significantly increased default risk. Further mechanistic analysis reveals that the level of green technical cooperation innovation mitigates the impact of increased weighted degree centrality on the default risk of high energy-consuming enterprises. For high energy-consuming enterprises located in the eastern region, central region or non-heavily polluting industries, the influence of weighted degree centrality in the asset association network on default risk is more significant. This study enriches complex network research and provides guidance for managing default risk in high energy-consuming enterprises. Additionally, these studies align with global trends toward enhanced asset transparency, sustainability, and financial resilience, and contribute emerging markets to the transition toward more sustainable energy practices.

A comparative study of firm value models: Default risk of corporate bonds

This paper presents a regime-switching normal tempered stable (NTS) firm value model for pricing default risk, based on an N-state continuous Markov chain process and an underlying NTS process. The derived regime switching characteristic function enables closed-form expressions for corporate bond credit spreads, with the model’s innovation arising from substituting the characteristic function of the existing NTS firm value model. This approach is assumed to capture hidden factors affecting default risk pricing. Calibration for the term structure of US corporate industrial credit spread demonstrates the model’s superior fit across all credit ratings compared to NTS and Merton firm value models.

Does the threat of takeover affect default risk?

AbstractWe examine the impact of the threat of takeovers on default risk. Using a sample of 50,189 firm‐year observations for US firms over the period 1990–2015, we find that the threat of takeovers has a negative relation with default risk. We use difference‐in‐difference analysis to address potential endogeneity concerns and propensity score matching to control for self‐selection bias. The results are robust to alternative measures of default risk and exclusion of the dot com and financial crisis periods. Our results also hold after controlling for Governance Index and Entrenchment Index. We identify improvement in performance and earnings quality in response to the threat of takeovers as channels underlying our main result. The effect of the threat of takeovers on default risk is more pronounced for firms with opaque information environment and low institutional ownership. Our findings provide important insights for the market for corporate control as a disciplining mechanism in reducing default risk.

Bayesian Behavior Scoring Model

Although many scoring models have been developed in literature to offer financial institutions guidance in credit granting decision, the pur pose of most scoring models are to improve their discrimination ability, not their explanatory ability. Therefore, the conventional scoring models can only provide limited information in the relationship among customer de mographics, default risk, and credit card attributes, such as APR (annual percentage rate) and credit limits. In this paper, a Bayesian behavior scor ing model is proposed to help financial institutions identify factors which truly reflect customer value and can affect default risk. To illustrate the proposed model, we applied it to the credit cardholder database provided by one major bank in Taiwan. The empirical results show that increasing APR will raise the default probability greatly. Single cardholders are less accountable for credit card repayment. High income, female, or cardholders with higher education are more likely to have good repayment ability.

Counterparty Default Risk and Monetary Policy in Unsecured Interbank Lending Markets

Banks bargain over the cost of unsecured loans in a model of interbank lending markets characterized by counterparty default risk. The risk an individual bank defaults depends on both idiosyncratic and aggregate factors and impacts loan rates and participation in the interbank loan market. After a deterioration of the aggregate factor affecting default risk, participation in interbank lending markets declines, and both individual and the average interbank loan rates rise. The model suggests that some policy actions enacted during the late-2000s financial crisis may have reduced participation and increased spreads in unsecured interbank loan markets.

How Does Aggregate Tax Policy Uncertainty Affect Default Risk?

We examine the impact of aggregate tax policy uncertainty on firm-level default risk. Due to uncertainties associated with tax policies, firms could have difficulties in determining their optimal debt level and use too much debt to increase their values. This can increase firms’ financial risk and default probabilities. At the same time, tax policy uncertainty may lead some firms to take less risk which could lower their use of debt and in turn lower the probability of default. We find that tax policy uncertainty is positively associated with firms’ expected default probabilities. In terms of economic significance, our findings show an increase of 14.83% in expected default probability, on a relative basis. Our results are robust to controlling for conditions of the economy, conditions of the stock market, financial constraints of firms, and credit quality of firms. Our evidence adds to two strands of research: research on taxation and firms’ risk profiles and the impact of policy uncertainty on firms’ decisions.

Determinants of corporate default risk in China: The role of financial constraints

Corporate default risk can affect financial stability and the macroeconomy. However, the determinants of corporate default risk in China are not well defined in the literature. We address this issue by using a rich credit event dataset of 981 Chinese listed firms over the period 1998–2013 and study the factors that affect default risk. We demonstrate that leverage, liquidity, firm size are the key firm-specific factors in determining default risk in China, along with macroeconomic factors like interest rate and stock return. Moreover, ‘Too big to fail’ only applies to non-SOEs, as default risk of SOEs is not affected by the firm size. We further find that high liquidity fails to reduce firms default risk, because small-sized firms which are financially constrained have limited cash to prevent financial distress, whereas large firms with greater cash holdings are able to mitigate their default risk as they are unconstrained.

Assessment of Factors Affecting Default Risk in Project Finance: A Case of Omo Micro Finance, Hawassa Branch

This study assesses factors that Affecting Default Risk in Project Finance: A Case of Omo Micro Finance, Hawassa Branches. Primary data were used in the study. The required data were collected from 338 project finance beneficiaries of Omo Micro Finance institutions and these respondents selected by adopting a simple random sampling technique. Both qualitative and quantitative methods were used. The data collected through questionnaire were analyzed using SPSS software version 20. Descriptive statistics such as frequency and percentage were applied. Furthermore, inferential statistics Chi-square and binary logistic regression were used to identify major factors that affect the default risk. In addition, the data collected through interview were analyzed qualitatively using narrative for triangulation. The findings of the study show that 57% of borrowers in the study area did not repay the amount of money they borrowed as per credit schedules. The major factors that affect the default risk were sex of the borrower, educational level, family size, advisory visit, time lines of loan, repayment period, borrowing experience and training. The study therefore recommends that the stakeholders in the microfinance sector should ensure that the loan borrowers have access to adequate relevant technical training and follow-up in entrepreneurial microfinance businesses. Keywords: Default risk, Institution, Loan, Omo Micro Finance, Project Finance, DOI: 10.7176/RJFA/11-11-02 Publication date: June 30th 2020

Does Threat of Takeover Affect Default Risk?

We examine the impact of the threat of takeover on default risk. Using a sample of 46,236 firm year observations for US firms over the period 1994-2015, we find that the threat of takeover has a negative relation with default risk. We use difference-in-difference analysis to address potential endogeneity concerns and propensity score matching to control for self-selection bias. The results are robust to alternative measures of default risk and exclusion of the dot com and financial crisis periods. We identify improvement in performance and earnings quality in response to the threat of takeover as channels underlying our main result. The effect of the threat of takeover on default risk is more pronounced for firms with low information environment and institutional ownership. Our findings provide important insights for the market for corporate control as a disciplining mechanism in reducing default risk.

Gender effect on the default risk in peer-to-peer lending markets: The case of the largest Chinese platform

Research of gender effect on funding success in peer-to-peer lending markets demonstrates that gender discrimination is a platform-specific phenomenon rather than a common feature. Can we get a similar conclusion about the relationship between gender and credit risk? How do gender differences affect default risk? We try to answer this question using the data of the largest peer-to-peer lending platform RenRenDai spanning from March 2016 to September 2016. In order to avoid the endogeneity problem, this paper first uses the instrumental variable method to conduct a baseline Probit model estimate connecting gender difference to the default rate with several borrowers’ individual characteristics under control. Then the original Probit model and a propensity score matching method aiming to eliminate the effects of divergent observable characteristics are applied to test the robustness of the outcome. Both the baseline estimation and the robustness test show that there is no significant gender effect on the probability of default, ceteris paribus. Therefore, borrowers’ gender is not a good screening device for the P2P lending platform to control the credit risk; other factors should be taken into account to reduce the non-performing loan rate. However, since this paper only investigates the situation of RenRenDai and the data we use is limited, we should be very careful to generalize our findings to other P2P lending platforms. More research on different P2P lending platforms in different regulatory regimes is in necessity

Does corporate governance quality affect default risk? The role of growth opportunities and stock liquidity

A series of defaults, a distinctive corporate environment and inconclusive findings in literature make Australia an interesting case in which to investigate the association between corporate governance and default risk. Using a large panel of 1086 non-financial firms from 2001 to 2013, we find that better governed firms are strongly associated with a lower level of default risk, and that the association is stronger among firms with more growth opportunities. Moreover, empirical evidence supports the role of stock liquidity as a channel of the relationship. Overall these findings have practical implications for the stakeholders in Australia.

Does the source of debt financing affect default risk?

We examine whether the source of debt financing is important for assessments of firms' default risk. This study reveals that during the 2007–2010 financial crisis, firms that depend mainly on financing from banks suffer higher increases in default risk than do firms with no such dependence. Conversely, firms that rely solely on financing from public debt markets do not experience significant increases in default risk. These findings suggest that the bank supply shock theory explains the transmission of financial shocks to the real economy. Finally, firms that depend on bank financing cannot offset the adverse impacts of bank lending shocks by substituting bank loans with publicly traded debt.

The Role of Dispersed Information in Pricing Default: Evidence from the CDS Market

Starting in September 2007 the banking system worldwide was turned upside down; both level and volatility of banks' CDS spreads experienced an eightfold increase that can hardly be motivated by changes in fundamentals. The recent Global Games literature proposes a theory that explains banks' default without resorting to panics. We assess the empirical relevance of this literature and find that dispersion of beliefs plays a key role in affecting default risk. More precise information greatly amplifies the reaction of CDS spreads to market expectations; for highly leveraged banks, this sensitivity is four times larger if the market receives precise signals instead of imprecise ones. These findings suggest that dispersed information and higher order beliefs are essential to understand what may look like an overreaction of market participants to news. Moreover, we document a strong direct impact of dispersion of beliefs on default risk: when news is bad enough, a one standard deviation decrease in dispersion of beliefs leads to an increase in CDS spreads of 120 basis points, which is half of its standard deviation in times of crisis. Finally, we address concerns of endogeneity of market expectations by introducing a novel set of instruments whose validity requires very mild assumptions on the agents' learning process.

Why Can Margin Requirements Increase Volatility and Benefit Margin Constrained Investors?

Margin requirements have long been implemented in almost all financial markets and are often used as an important regulatory tool for improving market conditions. However, their economic impact beyond affecting default risk is still largely unknown. We propose a tractable and flexible equilibrium model to examine how margin requirements on both long and short stock positions affect asset prices, market volatility, market liquidity and market participants' welfare. Unlike the existing literature, all investors are subject to margin requirements in our model. This difference yields important new insights about the impact of margin requirements. Most of our main results are obtained in closed-form. Contrary to one of the main regulatory goals, we find that even though margin requirements restrict borrowing and shorting, they can significantly increase market volatility. In addition, margin requirements can reduce market liquidity (as measured by price impact) and lead to a greater return reversal. Moreover, margin requirements can make margin constrained investors better off. Our analysis also provides new empirically testable implications.

Monetary policy and corporate bond yield spreads

Firm characteristics, economic conditions and policy regimes are the key determinants that most researchers have used to explain corporate bond yield spreads. In this article, we examine whether monetary policy shocks are also important determinants given their ability to affect default risk, risk aversion and liquidity premiums. Using a Vector Autoregression (VAR) with long-run monetary neutrality, we find that monetary policy shocks do, in fact, account for a large portion of the variation in corporate bond yield spreads.

The Economics of Bank Restructuring: Understanding the Options

Based on a simple framework, this note clarifies the economics behind bank restructuring and evaluates various restructuring options for systemically important banks. The note assumes that the government aims to reduce the probability of a bank's default and keep the burden on taxpayers at a minimum. The note also acknowledges that the design of any restructuring needs to take into consideration the payoffs and incentives for the various key stakeholders (i.e., shareholders, debt holders, and government). If debt contracts can be renegotiated easily, the probability of default can be reduced without any government involvement by a debt-for-equity swap. Such a swap, if appropriately designed, would not make equity holders or debt holders worse off. However, such restructurings are hard to pull off in practice because of the difficulty of coordinating among many stakeholders, the need for speed, and the concerns of the potential systemic impact of rewriting debt contracts. When debt contracts cannot be changed, transfers from the taxpayer are necessary. Debt holders benefit from a lower default probability. Absent government transfers, their gains imply a decrease in equity value. Shareholders will therefore oppose the restructuring unless they receive transfers from taxpayers. The required transfer amounts vary across restructuring plans. Asset sales are more costly for taxpayers than asset guarantees or recapitalizations. This is because sales are not specifically targeted to reduce the probability of default. Guarantees or recapitalizations affect default risk more directly. Transfers can also be reduced if the proceeds of new issues are used to buy back debt. Depending on the options chosen, restructuring may generate economic gains. These gains should be maximized. Separating out bad assets can help managers focus on typical bank management issues and thereby increases productivity. Because government often lacks the necessary expertise to run a bank or manage assets, it should utilize private sector expertise. Low up-front transfers can help prevent misuse of taxpayer money. Moreover, the design of bank managers' compensation should provide incentives to maximize future profits. If participation is voluntary, a restructuring plan needs to appeal to banks. Bank managers often know the quality of their assets better than the market does. This means banks looking for new financing will be perceived by the market to have more toxic assets and, as a result, face higher financing costs. Banks will therefore be reluctant to participate in a restructuring plan and demand more taxpayer transfers. A restructuring that uses hybrid instruments - such as convertible bonds or preferred shares - mitigates this problem because it does not signal that the bank is in a dire situation. In addition, asset guarantees that are well designed can be more advantageous to taxpayers than equity recapitalizations. A compulsory program, if feasible, would obviously eliminate any signaling concerns. Information problems can also be mitigated if the government gathers and publicizes accurate information on banks' assets. In summary, systemic bank restructuring should combine several elements to address multiple concerns and trade-offs on a case-by-case basis. In any plan, the costs to taxpayers and the final beneficiaries of the subsidies should be transparent. To forestall future financial crises, managers and shareholders should be held accountable and face punitive consequences. In the long run, various frictions should be reduced to make systemic bank restructuring quicker, less complex, and less costly.

High-Yield Bond Default and Call Risks

This paper empirically investigates high-yield bond default and call behavior using a competing risks hazard model that simultaneously estimates the impact of bond age, issue-specific characteristics and business conditions on both events. Results reveal nonmonotonic aging effects: default rates increase and then drop while call rates first increase and then level off. Rating and coupon size affect default risk, while maturity and issue size impact only call rates. Defaults are more likely when economic conditions have worsened and no improvement is anticipated. Calls are more likely when interest rates have decreased but are expected to rise.

A statistical approach to modeling the behavior of bond raters

Since the early 1970s the literature concerning statistical models of bond ratings has burgeoned. The thrust of these studies has been the attempt to predict as accurately as possible the rating assigned to a particular firm’s bond issue based on readily available data concerning that firm’s financial characteristics.’ In concentrating on accurate prediction, however, these studies have tacitly assumed that the bond rater’s assessment of default risk is perfectly accurate. As a result, those variables that are theoretically important in directly affecting default risk are the ones employed as predictors, and the statistical model judged as best is the one having the highest percentage of correct ratings predictions. We have no objection to this approach per se; correctly predicting bond ratings is clearly important, and these studies have contributed dramatically to our understanding of the bond-rating process. Perhaps because of their interest in accurate prediction, however, these studies have paid little attention to several questions of interest and potential importance both to rating agencies and to the firms whose debt is rated. These questions are as follows: What variables significantly affect a rater’s assessment of a bond’s quality?* What is the relative importance of each of these variables in determining the position of the bond in the rater’s implicit quality hierarchy? What is the magnitude of the effect of an incremental change in a particular financial variable on the probability of a firm’s issue receiving a given rating? Answers to these questions should be of interest to the financial manager of a debt-issuing company to the extent that the ability to control key financial variables implies some ability to control the rating assigned to its bonds. Likewise, answers to these questions should be of interest to rating agencies for establishing objective norms for their raters.3