Search results

This study aims to investigate whether managerial short-termism affects the expected default probability for a sample of Chinese-listed firms.

To capture default, we utilize the expected default probability measure developed by Bharath and Shumway (2008). Textual analysis and machine learning techniques are used to construct the index of managerial myopia. We conduct ordinary least squares regression and employ a large sample of 33,164 firm-year observations from Chinese A-share listed firms spanning the years 2001–2021 to test our theoretical hypotheses. We further conduct mediation tests, moderating analysis, textual features analysis and analysis of actual default firms. In addition, we employ change regression, entropy-balanced/propensity score/closest assets matching analysis, two-stage least squares regression, two-stage residual intervention method and alternative estimation methods to address endogeneity concerns.

First, there is a positive and statistically significant relationship between managerial myopia and expected default probability. Second, the mediation tests indicate that managerial myopia increases the expected default probability through operational risk and opportunistic agency channels. Third, the cross-sectional tests reveal that the positive association is less pronounced for firms with effective internal control systems, higher audit quality and more financial analyst coverage.

Our study reveals the need for comprehensive early warning mechanisms in the corporate bond market in China, in particular, through enhanced transparency of managerial incentive schemes and more rigorous disclosure requirements regarding short-term managerial decision-making. Furthermore, the findings of our study suggest the necessity of taking an integrated approach in developing regulatory frameworks that enable market intermediaries – including rating agencies, financial analysts and external auditors – to execute their monitoring functions with greater effectiveness.

Prior research has examined the impact of managers’ demographic characteristics on a range of corporate organizational outcomes; however, there have been few studies investigating the influence of managerial myopia on corporate financial risks. This study advances the literature on the determinants of default probability. It contributes to the limited and emerging studies on the role of managerial myopia by being the first to examine the effect of managerial myopia on expected default probability.

In fraudulent conveyance cases, plaintiffs allege that by entering into a complex leverage transaction, such as an LBO, a firm’s former owners ensured its subsequent collapse. Proving that the transaction rendered the firm insolvent may allow debtors (or their proxies) to claw back transfers made to former shareholders and others as part of the transaction.

Courts have recently questioned the robustness of the solvency evidence traditionally provided in such cases, claiming that traditional expert analyses (e.g., a discounted flow analysis) may suffer from hindsight (and other forms of) bias, and thus not reflect an accurate view of the firm’s insolvency prospects at the time of the challenged transfers. To address the issue, courts have recently suggested that experts should consider market evidence, such as the firm’s stock, bond, or credit default swap prices at the time of the challenged transaction. We review market-evidence-based approaches for determination of solvency in fraudulent conveyance cases.

We compare different methods of solvency determination that rely on market data. We discuss the pros and cons of these methods and illustrate the use of credit default swap spreads with a numerical example. Finally, we highlight the limitations of these methods.

If securities trade in efficient markets in which security prices quickly impound all available information, then such security prices provide an objective assessment of investors’ views of the firm’s future insolvency prospects at the time of challenged transfer, given contemporaneously available information. As we explain, using market data to analyze fraudulent conveyance claims or assess a firm’s solvency prospects is not as straightforward as some courts argue. To do so, an expert must first pick a particular credit risk model from a host of choices which links the market evidence (or security price) to the likelihood of future default. Then, to implement his chosen model, the expert must estimate various parameter input values at the time of the alleged fraudulent transfer. In this connection, it is important to note that each credit risk model rests on particular assumptions, and there are typically several ways in which a model’s key parameters may be empirically estimated. Such choices critically affect any conclusion about a firm’s future default prospects as of the date of an alleged fraudulent conveyance.

Simply using market evidence does not necessarily eliminate the question of bias in any analysis. The reliability of a plaintiff’s claims regarding fraudulent conveyance will depend on the reasonableness of the analysis used to tie the observed market evidence at the time of the alleged fraudulent transfer to default prospects of the firm.

There is a large body of literature in financial economics that examines the relationship between market data and the prospects of a firm’s future default. However, there is surprisingly little research tying that literature to the analysis of fraudulent conveyance claims. Our paper, in part, attempts to do so. We show that while market-based methods use the information contained in market prices, this information must be supplemented with assumptions and the conclusions of these methods critically depend on the assumption made.

The purpose of this paper is to, first, analyse to what extent the default probability based on structural models provides additional information and that accounting ratios do not contemplate. Second, to design hybrid models by including the default probability from structural models as explanatory variable, in addition to accounting ratios, in order to evaluate the differences in the accuracy of default predictions using an accounting‐based model and a hybrid model.

The authors calculated the scores from the accounting models annually during the period from 2003 to 2007 and estimated several structural models.

The results show that the market information obtained from the structural models includes additional information not reflected in the accounting information. Also, it can be concluded that including default probability from structural models as an explanatory variable allows the out‐sample predictive capacity of accounting‐based models to be improved.

The study highlights the importance of combining a structural model with an accounting model rather than expending energy on determining which of the two provides a greater predictive capacity. In fact, recent literature demonstrates no superiority of one approach over the other because both approaches capture different aspects related to the risk of bankruptcy in companies and they should be combined to improve credit risk management.

This study expands on the existing literature on the probability of business failure in the real estate sector. The authors present a comparative analysis of the accuracy of default predictions using accounting‐based models and hybrid models which will consider the default probability implicit in market information.

This study aims to shed more light on the relationship between probability of default, investment horizons and rating classes to make decision-making processes more efficient.

Based on credit default swaps (CDS) spreads, a methodology is implemented to determine the implied default probability and the implied rating, and then to estimate the term structure of the market-implied default probability and the transition matrix of implied rating. The term structure estimation in discrete time is conducted with the Nelson and Siegel model and in continuous time with the Vasicek model. The assessment of the transition matrix is performed using the homogeneous Markov model.

The results show that the CDS-based implied ratings are lower than those based on Thomson Reuters approach, which can partially be explained by the fact that the real-world probabilities are smaller than those founded on a risk-neutral framework. Moreover, investment and sub-investment grade companies exhibit different risk profiles with respect of the investment horizons.

The originality of this study consists in determining the implied rating based on CDS spreads and to detect the difference between implied market rating and the Thomson Reuters StarMine rating. The results can be used to analyze credit risk assessments and examine issues related to the Thomson Reuters StarMine credit risk model.

The purpose of this paper is to determine optimal pooling strategies from the perspective of an insurer's shareholders underlying a default probability driven premium loading and convex price-demand functions.

The authors use an option pricing framework for normally distributed claims to analyze the net present value for different pooling strategies and contrast multiple risk pools structured as a single legal entity with the case of multiple legal entities. To achieve the net present value maximizing default probability, the insurer adjusts the underlying equity capital.

The authors show with the theoretical considerations and numerical examples that multiple risk pools with multiple legal entities are optimal if the equity capital must be decreased. An equity capital increase implies that multiple risk pools in a single legal entity are generally optimal. Moreover, a single risk pool for multiple risk classes improves in relation to multiple risk pools with multiple legal entities whenever the standard deviation of the underlying claims increases.

The authors extend previous research on risk pooling by introducing a default probability driven premium loading and a relation between the premium level and demand through a convex price-demand function.

Liquidity risk, i.e., the likelihood that a swap can be “sold” (i.e., assigned) may affect swap prices. This article addresses the importance of liquidity risk as a factor in the valuation of swaps, which are subject to default risk. The author presents a model for pricing these swaps by incorporating a proxy for liquidity risk. Using the model, the author finds that the effects of liquidity risk may partially offset the effects of default risk.

The purpose of this paper is to consider borrower-specific characteristics to understand the factors affecting both the probability and quantum of loan default by individual borrowers under Islamic and conventional banking.

Borrower-specific characteristics that explain the probability of default may not necessarily be similar factors that determine the quantum of default. The authors therefore apply a Box-Cox double hurdle model to treat both the probability and quantum of default in a two-step approach. The authors also explain the differences in default risk and quantum of default between Islamic and conventional banking borrowers from their behavioral perspectives following the Sharia principles in financial transactions between lenders and borrowers. The authors use borrower-specific information of two separate bank branches of the United Arab Emirates that solely deal with either Islamic or conventional banking products.

The paper demonstrates that the probability of default and the quantum of default appear to be influenced by different set of client-specific factors. The results suggest that the probability of default does not vary significantly between Islamic and conventional banking borrowers. The evidence also shows that Islamic banking defaulters, compared to those in conventional banking, repay a large quantum of overdue when their financial leverage improves. However, they do not tend to reduce their outstanding quantum of overdue faster than conventional banking defaulters.

Availability of data from only two bank branches may limit the explanatory power of empirical findings.

The study findings will enable the Islamic and conventional banks to appropriately address Basel Capital requirements based on the borrowers’ behavior.

The study findings have the potential for Islamic and conventional financing institutions to be more flexible with equity in their lending practices.

Religious beliefs are crucial in borrower’s default behavior in Islamic banking.

This article discusses factor models for portfolio credit. In these models, correlations between individual defaults are driven by a few systematic factors. By conditioning on these factors, defaults observed within are independent. This allows a greater degree of analytical tractability in the model with a realistic dependency structure.