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Commodity price volatility and small variations in climate conditions may have an important impact on the creditworthiness of any agricultural project. The evolution of such risk factors is vital for the credit risk analysis of a rural bank. The purpose of this paper is to determine the importance of price volatility and climate factors within a default risk model.

The authors estimate a generalized linear model (GLM) based on a structural default risk model. With the estimated factor loadings, the authors simulate the loss distribution of the portfolio and perform stress test to determine the impact of the relevant risk factors on economic capital.

The results indicate that both the price volatility and climate factors are statistically significant; however, their economic significance is smaller compare to other factors that the authors control for: macroeconomic conditions for the agricultural sector and intermediate input prices.

The analysis of non-systemic risk factors such as price volatility and climate conditions requires statistical methods focussed on measuring causal effects at higher quantiles, not just at the conditional mean, this is, however, a current limitation of GLMs.

The authors provide a design of a portfolio credit risk model, that is more suited to the special characteristics of a rural bank, than commercial credit risk models.

The paper incorporates agricultural-specific risk factors in a default risk model and a portfolio credit risk model.

The authors investigate the implications of environmental, social and governance (ESG) practices of firms for the pricing of their credit default swaps (CDS). In doing so, the authors compare European and US firms and consider nonlinear and indirect effects. This complements the previous literature focusing on linear and direct effects using bond yields and credit ratings of US firms.

For this purpose, the authors apply fixed effects regressions on a comprehensive panel data set of US and European firms. Further, nonlinear and indirect effects are investigated utilizing quantile regressions and a path analysis.

The evidence indicates that higher ESG ratings mitigate credit risks of US and European firms from 2007 to 2019. The risk mitigation effect is U-shaped across ESG quantiles, which is consistent with opposing effects of growing stakeholder influence capacity and diminishing marginal returns on ESG investments. The authors further reveal a mediating indirect volatility channel that substantially amplifies the direct effect of ESG on credit risk. A one-standard-deviation improvement in ESG ratings is estimated to reduce CDS spreads of low, medium and high ESG firms by approximately 4%, 8% and 3%, respectively.

This is the first study to examine whether credit markets reflect regional differences between Europe and the US with regard to the ESG-CDS-relationship. In addition, this paper contributes to the existing literature by investigating differences in the response of CDS spreads across ESG quantiles and to study potential indirect channels connecting ESG and CDS spreads using structural credit risk variables.

The purpose of this article is to discuss a Black‐Scholes‐Merton (BSM)‐based market approach to quantify the default risk of publicly‐listed individual companies.

Using the contingent claim approach, a framework is presented to optimally use stock market and balance sheet information of the company to predict its probability of failure as well as ordinal risk ranking over a horizon of one year.

By applying the methodology, yearly estimates of the risk neutral and real probability of default for 150 Indian corporates from 1998 to 2005 were constructed, that give up‐to‐date point‐in‐time perspective of their risk assessment. It was found that option model can provide ordinal ranking of companies on the basis of their default risk which also has good early warning predictability.

The option‐based default probability estimation may be an innovative approach for measuring and managing credit risk even in the emerging market economy. The asset value model developed in this paper based on the BSM model can facilitate the Indian banks as well as investors to get an early warning signal about the company's default status.

This study investigates the influence of theoretical determinants on the Korea sovereign CDS spreads from January 2007 to September 2009 based on structural credit risk model. For the analysis of determinants on the sovereign CDS spread, this study adopts interest swap rate as reference interest rate, and decomposes yields curve into two components, ie, interest level and slope. Considering multivariate regression in level and difference variables, Stock returns and Interest rates have a significant effect on the CDS spreads among the theoretical determinants of structural credit risk models. CDS spreads may behave quite differently during volatile regime compared with their behavior in tranquil regime. We therefore apply Markov switching model to investigate the possibility that the influence of theoretical determinants of CDS spread has a regime dependent behavior. In all regimes Korean sovereign CDS spreads are highly sensitive to stock market returns, whereas in tranquil regime interest rates also have influence on CDS spreads. We conclude that for the efficient hedging of CDS exposure trader should adjust equity hedge ratio to the relevant regime.

The purpose of this paper is to assess the significance of the Merton distance-to-default (DD) in predicting defaults for a sample of listed Indian firms.

The study uses a matched pair sample of defaulting and non-defaulting listed Indian firms. It employs two alternative statistical techniques, namely, logistic regression and multiple discriminant analysis.

The option-based DD is found to be statistically significant in predicting defaults and has a significantly negative relationship with the probability of default. The DD retains its significance even after the addition of Altman’s Z-score. This further establishes its robustness as a significant predictor of default.

The study re-establishes the utility of the Merton model in India using a simplified version of the Merton model that can be easily operationalized by practitioners, reasonably larger sample size and is done in a more recent period covering the post global financial crisis period. The findings could be valuable to banks, financial institutions, investors and managers.

This paper aims to investigate informational efficiency of stock, options and credit default swap (CDS) markets. Previous research suggests that informed traders prefer equity option and CDS markets over stock markets to exploit their informational advantage. As a result, equity and credit derivative markets contribute more to price discovery compared to stock markets.

In this study, the authors investigate the dynamics behind informed investors’ trading decisions in European stock, options and CDS markets. This allows to identify the predictive explanatory power of the unique information contained in each market with respect to future stock, CDS and option market movements.

A lead-lag relation is found between the CDS market and the other markets, in which changes in CDS spreads are able to consistently forecast changes in stock prices and equity options’ implied volatilities, indicating how the fast-growing CDS market seems to play a special role in the price discovery process. Moreover, in contrast to results of US studies, the stock market is found to forecast changes in the other two markets, suggesting that investors also prefer stock market involvement to exploit their information advantages before moving to CDS and option markets. Interestingly, these patterns have only emerged during the recent financial crisis, while before the crisis, the option market was found to be of major importance in the price discovery process.

The authors are the first to study the lead-lag relationship among European stock, option and CDS markets for a large sample period covering the financial crisis.

The purpose of this paper is to demonstrate the applicability of the Credit Default Swaps (CDS), as a financial instrument, for transferring of risk in project finance loans. Also, an equation has been derived for pricing of CDS spreads.

The debt service cover ratio (DSCR) is modeled as a Brownian Motion (BM) with a power-law model fitted to the mean and half-variance of the existing data set of DSCRs. The survival probability of DSCR is calculated during the operational phase of the project finance deal, using a closed-form analytical method, and the results are verified by Monte Carlo simulation (MCS).

It is found that using the power-law model yields higher CDS premiums. This in turn confirms the necessity of conducting rigorous statistical analysis in fitting the best performing model as uninformed reliance on constant time-invariant drift and diffusion model can erroneously result in smaller CDS spreads. A sensitivity analysis also shows that the results are very sensitive to the recovery rate and cost of debt values.

Insufficiency of free cash flow is a major risk in the toll road project finance and hence there is a need to develop innovative financial instruments for risk management. In this paper, a novel valuation method of CDS is proposed assuming that DSCR follows the BM stochastic process.

The new capital accord, otherwise known as Basel II, from the Basel Committee on Banking Supervision, addresses the issue of financial risk. Within the latest version of the new accord and numerous consultation papers, the committee has reinforced its emphasis on risk management, encouraging banks to improve their risk assessment capabilities. Basel II attempts to accomplish this by closely aligning capital with modern risk management best practices, and by ensuring that the emphasis on risk makes its way onto supervisory practices and market discipline. Thus, regulatory pressure is, and will remain over the near future, a key driver of risk management systems development across market, credit and operational risk.

As the end of the 2006 deadline to implement regulatory changes being proposed by the Basel Committee on Banking Supervision looms closer, banks are battling to make their credit risk management systems compliant. But the majority are looking beyond the demands of the regulator. Some are realizing that Basel II provides them with an opportunity to improve their overall risk management strategy, improve business decision‐making, and increase shareholder value.