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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.

This article surveys available research on the contingent‐claims approach to risky debt valuation. The author describes both the structural and reduced form versions of contingent claims models and summarizes both the theoretical and empirical research in this area. Relative to the progress made in the theory of risky debt valuation, empirical validation of these models lags far behind. This survey highlights the increasing gap between the theoretical valuation and the empirical understanding of risky debt.

This paper estimates the conditional hazard baseline (term-structure) of the hazard rate to default at the time of bonds’ issuance by using two hazard models–one ignoring and another allowing unobserved heterogeneity (UH) in the hazard rate. Following Diamond (1989) one can predict a declining hazard rate to default due to adverse selection and moral hazard. After controlling for UH caused by adverse selection and time-series shocks, the hazard rate shows to be increasing over time and hence the moral hazard effect cannot be confirmed.

The authors analyse the determinants of loan defaults in micro, small and medium enterprises (MSME) loans in India from the survival duration perspective to draw inferences that have implications for lenders and policymakers.

The authors use the Kaplan–Meier survivor function and the Cox Proportional Hazard model to analyse 4.29 lakhs MSME loan account data originated by a large bank having a national presence from 1st January 2016 to 31st December 2020.

The estimated Kaplan–Meier survival function by various categories of loan and socio-demographic characteristics reflects heterogeneity and identifies the trigger points for actions. The authors identify the key identified default drivers. The authors find that the subsidy amount is more effective at the lower level and its effectiveness diminishes significantly beyond an optimum level. The simulated values show that the effects of rising interest rates on survival rates vary across industries and types of loans.

The identified points of inflection in the default dynamics would help banks to initiate actions to prevent loan defaults. The default drivers identified would foster more nuanced lending decisions. The study estimation of the survival rate based on the simulated values of interest rate and subsidy provides insight for policymakers.

This study is the first to investigate default drivers in MSME loans in India using micro-data. The study findings will act as signposts for the planners to guide the direction of the interest rate to be charged by banks in MSME loans, interest subvention and tailoring subsidy levels to foster sustainable growth.

The purpose of this paper is to investigate how the 401(k) auto-enrollment rate influences the size of elected contribution rates in defined contribution plans for new, young enrollees.

The authors survey 324 undergraduate students at a mid-sized Midwestern university, and compare the elected contribution rates for two groups who were randomly given two default rates: 3 and 15 percent.

The results indicate widespread evidence of the anchoring and adjusting heuristic in regards to the provided auto-enrollment rate, as the 3 percent default rate group selects a contribution rate of approximately 2 percent less than the group that was provided with the 15 percent default rate. The results also provide support to the benefits of financial education: those who were taking or had already taken a college-level finance course provide higher contribution rates by about 1.7 percent overall. Additionally, individuals with the lowest critical thinking skills elect approximately 2 percent less in annual contributions overall than those who demonstrate higher critical thinking skills.

Interestingly, all groups seem to be susceptible to the anchoring and adjustment heuristic, as the default rate plays a significant role in the elected contribution rate, regardless of an individual’s financial sophistication or critical thinking skill level. The authors hope that these findings prompt benefit plan administrators and policy-makers to reconsider default rates in their retirement plans that would allow for maximum savings and participation rates. The findings also speak in favor of developing programs that would assist enrollees with financial education and critical thinking skills that would yield better retirement savings decisions when asked to make their employee benefit selections.

Credit migration correlation is a critical assumption for the integration of market risk and credit risk within enterprise‐wide risk management. This article describes hypothesis testing performed on credit migration correlation, based on two models: 1) a factor model and 2) an asset‐value model. These tests involve both the correlation between obligors and the correlation between credit migration events and systematic market risk factors. The author concludes from the test results that over shorter risk horizons (e.g., biweekly or monthly) where all relevant underlying processes are distributed multi‐variate normal, non‐zero positive correlation weights overestimate risk capital requirements, on average.

This paper aims to investigate the determinants of default mortgage in China and the factors affecting the mortgage amount granted by Chinese banks.

This paper employs the credit scoring model to investigate the determinants of default mortgage in China and the factors affecting the mortgage amount granted by Chinese banks.

Using a proprietary dataset from branches of the Construction Bank of China containing information on all mortgages offered to borrowers from 2004 to 2009 1st quarter, the paper documents that borrower rating, mortgage rate and mortgage duration are significantly related to default rate and mortgage amount. These findings suggest that Chinese banks' mortgage lending are based on commercial basis. This helps to reduce the likelihood of a real estate bubble in China.

The findings in this paper argued that a good credit scoring model has the ability to detect bad loans; this could help the bank to reduce the loan losses from loan default. Consequently, it can improve the profitability and the financial stability of the bank.

This research would benefit both lender and borrowers. Lenders can apply an objective evaluation technique with a standard process and criteria to appraise their customer's credit risks and creditworthiness. A good credit risk management tool can effectively control risk selection, manage credit losses, evaluate new loan programs, improve loan approval processing time, and ensure that existing credit criteria are sound and consistently applied.

Investors in commercial paper (CP) markets include money market mutual funds, corporate treasurers, state and local governments, and commercial banks and their trust departments. The obligors in the market are predominantly large and highly creditworthy corporations. The credit risks faced by CP investors have been minimal historically. However, the general decline in corporate credit quality that began in the first half of the 1980s set the stage for the spate of credit problems and defaults that took place in many CP markets beginning in 1987. While the incidence of default has decreased since 1991, the credit risks faced by commercial paper investors have not subsided to pre‐1987 levels. This analysis addresses concerns generated by this surge in credit risk.

The purpose of this paper is to propose a debt rating index system for small industrial enterprises that significantly distinguishes the default state. This debt rating system is constructed using the F-test and correlation analysis method, with the small industrial enterprise loans of a Chinese commercial bank as the data sample. This study establishes the weighting principle for the debt scoring model: “the more significant the default state, the larger is the weight.” The debt rating system for small industrial enterprises is constructed based on the standard “the higher the debt rating, the lower is the loss given default.”

In this study, the authors selected indexes that pass the homogeneity of variance test based on the principle that a greater deviation of the default sample’s mean from the whole sample’s mean leads to greater significance in distinguishing the default samples from the non-default samples. The authors removed correlated indexes based on the results of the correlation analysis and constructed a debt rating index system for small industrial enterprises that included 23 indexes.

Among the 23 indexes, the weights of 12 quantitative indexes add up to 0.547, while the weights of the remaining 11 qualitative indexes add up to 0.453. That is, in the debt rating of the small industry enterprises, the financial indexes are not capable of reflecting all the debt situations, and the qualitative indexes play a more important role in debt rating. The weights of indexes “X17 Outstanding loans to all assets ratio” and “X59 Date of the enterprise establishment” are 0.146 and 0.133, respectively; both these are greater than 0.1, and the indexes are ranked first and second, respectively. The weights of indexes “X6 EBIT-to- current liabilities ratio,” “X13 Ratio of capital to fixed” and “X78 Legal dispute number” are between 0.07 and 0.09, these indexes are ranked third to fifth. The weights of indexes “X3 Quick ratio” and “X50 Per capital year-end savings balance of Urban and rural residents” are both 0.013, and these are the lowest ranked indexes.

The data of index i are divided into two categories: default and non-default. A greater deviation in the mean of the default sample from that of the whole sample leads to greater deviation from the non-default sample’s mean as well; thus, the index can easily distinguish the default and the non-default samples. Following this line of thought, the authors select indexes that pass the F-test for the debt rating system that identifies whether or not the sample is default. This avoids the disadvantages of the existing research in which the standard for selecting the index has nothing to do with the default state; further, this presents a new way of debt rating. When the correlation coefficient of two indexes is greater than 0.8, the index with the smaller F-value is removed because of its weaker prediction capacity. This avoids the mistake of eliminating an index that has strong ability to distinguish default and non-default samples. The greater the deviation of the default sample’s mean from the whole sample’s mean, the greater is the capability of the index to distinguish the default state. According to this rule, the authors assign a larger weight to the index that exhibits the ability to identify the default state. This is different from the existing index system, which does not take into account the ability to identify the default state.