Probability Of Default Research Articles

Overview of an alternative trigger for DCL

In this research letter, we suggest a novel trigger for Dynamic Control of Leverage (DCL). These instruments are analogous to conventional Contingent Convertible (CoCo) bonds, employed to constrain a firm’s leverage within specified limits, thus minimizing the likelihood of default. Our proposed trigger enables continuous leverage monitoring, bringing in the desired flexibility allowing the conversion to be triggered ahead of the cash payment. This alternative design, building upon the DCL mechanism, has been shown to further reduce the probability of default while preserving the desirable mean-reverting behaviour of the leverage dynamic. We provide evidence of the model’s effectiveness and discuss the implications of its implementation.

Assessing the influence of ESG score, industry, and stock index on firm default risk: A sustainable bank lending perspective

Using a European sample of 211 listed firms from 2013 to 2022, we analyze the mitigation effect on firms’ probability of default (PD) provided by the influence of ESG performance combined with industry and stock index membership. The results show that improvements in environmental scores reduce PD; while firms’ riskiness increases when we control for industry and stock index. From a banking perspective, we encourage a holistic approach integrating ESG scores into lending practices, adjusted by industry or stock index. Policymakers and regulators should support the widespread adoption of ESG metrics in assessing credit risk.

The role of financial covenants in pricing private investments in public equity

Our study examines the pricing of private placements for issuing firms subject to outstanding loan covenants. Using Private Investments in Public Equity (PIPE) deals from 2001 to 2018, we find that issuing firms restricted by loan covenants offer a discount of 3.9% larger than those without covenants. We corroborate the positive impact of financial covenants on discounts through channel tests that assess covenant violation history, covenant strictness, and the identities of lead PIPE investors. The increased probability of technical default and costly renegotiation in covenants potentially incentivizes borrowing firms to transition from the loan market to the PIPE market. To minimize endogeneity concerns, we use a matched sample, a Heckman selection model, and a two-stage least squares instrumental variable analysis, all of which present consistent results. Based on our findings, we conjecture that PIPE investors are concerned about the transfer of control rights to lenders and, as a result, demand deeper discounts in PIPE offerings.

Default Risk and Option Returns

This paper studies the effects of default risk on expected equity option returns. In the cross-section, expected delta-hedged equity option returns have a negative relation with default risk measured by credit ratings or default probability. In the time series, credit rating downgrades (upgrades) lead to a decrease (increase) in the firm’s delta-hedged option return. Our results are consistent with a stylized capital structure model in which the negative relation between option returns and default risk is driven by firm leverage and asset volatility. This paper was accepted by Lukas Schmid, finance. Funding: A. Vasquez thanks the Asociación Mexicana de Cultura A.C. for financial support. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4796 .

Estimating default probabilities for no- and low-default portfolios: parameter specification via floor constraints

Abstract For low- and no-default portfolios, financial institutions are confronted with the problem to estimate default probabilities for credit ratings for which no default was observed. The Bayesian approach offers a solution but brings the problem of the parameter assignment of the prior distribution. Sequential Bayesian updating allows to settle the question of the location parameter or mean of the prior distribution. This article proposes to use floor constraints to determine the scale or standard deviation parameter of the prior distribution. The floor constraint can also be used to determine the free parameter γ in the Pluto–Tasche approach.

Survival and value: The conglomerate case

AbstractThis paper investigates the relationship between default probability and value when there is a selection bias due to missing controls for firm heterogeneous likelihood to survive in the sample. Our model delivers the following implications for the conglomerate case: (a) the sample conglomerate value increases in their default probability, (b) the sample conglomerate discount falls together with their excess default probability with respect to focused companies, (c) both effects disappear when the analyst controls for survival probability. The data support the presence of a selection bias distorting downwards the relative value of sample firms with higher survival probability.

THE CORRELATION IN CORPORATE DEFAULTS: EVIDENCE FROM NON-FINANCIAL LISTED COMPANIES IN SRI LANKA

Default correlation is the extent to which one company's default causes another's default. It measures the relationship between a firm’s individual default probability and the joint default probability among firms. This study makes theoretical contributions by examining the degree of default correlation among non-financial listed firms in terms of credit quality, time horizon, systematic risk, firm size, and liquidity. The researcher selected 550 firm-year observations (240 for default and 310 for non-default) consisting of 55 non-financial listed companies in Sri Lanka from 2012 to 2021. The default firms are selected using the three criteria during the selection period: suffering from losses, having negative net worth, or suffering from negative operating cash flows for more than three consecutive years. The non-default firms are selected by a couple with the default firms based on the same industry and the highest market capitalization. Altman’s (1968) Z-score model is used to determine the credit ratings as high, medium, and low. The study follows Lucas’s (1995) proposed standard binomial approach to measure the default correlation. The study revealed that time horizon, poor credit ratings, high beta, and small size increase the default correlation in the Sri Lankan context; however, liquidity is not a good measurement for default correlation analysis in Sri Lankan context. Credit risk management could underestimate the portfolio credit risk without considering the default correlation. The dynamic nature of default correlation shows that an increment in default risk of individual credit assets engages with a disproportionate increment in portfolio credit assets.

Does Board Gender Diversity Really Improve Financial Performance and Default Risk? Evidence from Romanian Companies Engaged in International Trade

Abstract Currently, in the business world, important attempts are being made to assess the possibility of verifying the creditworthiness of companies by going beyond traditional financial data and incorporating alternative data as well. Does the fact that the board of a company has a certain structure influence the financial health of that company? The paper’s objective is to ascertain if there is a correlation between the board of directors’ gender diversity, financial performance, and the probability of default for that respective company. The empirical study examined a sample of Romanian companies engaged in international trade. Using natural language processing techniques, I predicted the gender of the respective director by his/her first name. The second step of the research was the analysis of the correlation between the percentage of women on the board and traditional financial indicators such as profit or turnover, and the correlation between the percentage of women on the board and that company’s probability of default. The results show that there is generally not a strong correlation between the percentage of women on the board of the company and the other financial and risk indicators at the entire population level, but there is a strong correlation for some specific industries such as education, meaning that there are industries were the presence of women in board really impacts the performance of the business.

Boosting credit risk models

In this article, we give various recommendations to boost the performance of credit risk models. It is based upon more than two decades of research and consulting on the topic. Building credit risk models typically entails four steps: gathering and preprocessing data, modelling of probability of default (PD), Loss Given Default (LGD) and Exposure at Default (EAD), evaluating the credit risk models built and then the deployment step to put them into production. We give recommendations to boost credit risk models during each of these steps. Furthermore, we also define and review model risk as an all-encompassing challenge one needs to be properly aware of during each step of the process. We conclude by presenting a research agenda of topics we believe are in high need for further investigation and study.

Peer-to-peer lending: Legal loan sharking or altruistic investment? Analyzing platform investments from a credit risk perspective

This paper analyzes the performance of peer-to-peer investments, the potential benefits of their information processing and the investor returns, based on the entire portfolio of the Estonian platform Bondora. We found that the platform's scoring model relies on different default probabilities across countries and is weak at predicting default within countries. Alternative information could improve the models, but our analysis could not confirm this benefit of the platform. The average internal rate of return on closed transactions was –4.17%, and 42% of the loans end with a negative IRR. We concluded that P2P borrowers in the European market are mainly high-risk, bank ineligible clients, accepting even loan-sharking level interest rates, which excludes altruistic motives of investors. Even so, investors are not compensated for the credit risk.

Credit risk management analysis: An application of fuzzy theory to forecast the probability of default in a financial institution

Credit risk management analysis: An application of fuzzy theory to forecast the probability of default in a financial institution

Political constraints and sovereign default

We study how political constraints, characterized by the degree of flexibility to choose fiscal policies, affect the probability of sovereign default. To that end, we relax the assumption that policymakers always repay their debt in the dynamic model of fiscal policy developed by Battaglini and Coate (2008). In our setup, legislators bargain over taxes, general spending, debt repayment, and a local public good that can be targeted to the region they represent. Under tighter political constraints, more legislators have veto power, implying that local public goods need to be provided to a larger number of regions. The resources that are freed after a default have to be shared with a higher number of individuals, which reduces the benefits from defaulting in per-capita terms. This lowers the incentive to default compared to the case with lax political constraints. The model is calibrated to Argentina and the results conform to robust empirical evidence. An event study for the 2001/2002 sovereign debt crisis shows that political constraints had an important role in the buildup that led to the crisis.

Peer-to-Peer (P2P) Lending Risk Management: Assessing Credit Risk on Social Lending Platforms Using Textual Factors

Peer-to-peer (P2P) lending platforms offer Internet users the possibility to borrow money from peers without the intervention of traditional financial institutions. Due to the anonymity on such social lending platforms, determining the creditworthiness of borrowers is of high importance. Beyond the disclosure of traditional financial variables that enable risk assessment, peer-to-peer lending platforms offer the opportunity to reveal additional information on the loan purpose. We investigate whether this self-disclosed information is used to show reliability and to outline creditworthiness of platform participants. We analyze more than 70,000 loans funded at a leading social lending platform. We show that linguistic and content-based factors help to explain a loan's probability of default and that content-based factors are more important than linguistic variables. Surprisingly, not every information provided by borrowers underlines creditworthiness. Instead, certain aspects rather indicate a higher probability of default. Our study provides important insights on information disclosure in the context of peer-to-peer lending, shows how to increase performance in credit scoring and is highly relevant for the stakeholders on social lending platforms.

Default prediction of small and medium enterprises: Portuguese construction sector

PurposeThis paper aims to study the default risk of small and medium-sized enterprises in the construction sector.Design/methodology/approachAn unbalanced sample of 2,754 Portuguese companies from the construction sector, from 2008 to 2020, is analysed. Companies are classified in default or compliant following an ex-ante criterion. Then, using the stepwise analysis, the most relevant variables are selected, which are later used in the logit model. To verify the robustness of the results, a sample of legally insolvent companies is added (mixed criterion) and the initial sample is split into two subperiods.FindingsFinancial variables are the most relevant to predict the pattern for this sample. The main conclusions show that smaller and older companies, more indebted, with more liquidity and with higher EBIT have a higher probability of default. These conclusions are confirmed using a mixed criterion to classify companies as default or compliant and including a macroeconomic dummy.Practical implicationsThis work not only contributes to enlarging the literature review but also makes relevant contributions to practice. Companies from the construction sector can understand which indicators must control to avoid financial problems. The government also has relevant information that can help in adapting or creating regulations for recovering or revitalizing companies.Originality/valueThis study proposed an ex-ante criterion that can be used for all types of companies. Most works use a legal or a mixed criterion that does not allow for detecting signs of financial problems in advance. Moreover, the sample used is almost unexplored – SMEs from a sector with great mortality rate.

Does prospectus readability matter for bond issuance pricing? Evidence from China

We investigate the informational role of prospectus readability in determining the pricing of newly issued bonds in China. We construct a text-based measure of prospectus readability and find that less readable prospectus is associated with higher credit spread of newly issued bond. Furthermore, we then find that less readability of prospectus is associated with higher default probability of issuers, which lends support to the information manipulation view of readability. Moreover, we observe that the relationship between readability and spread is more pronounced for issuers with lower ratings and private ownership, as well as for bonds lacking external guarantees and associated with less reputable underwriters. These findings collectively highlight the importance of prospectus readability as a determinant of bond pricing in China, indicating that investors require a risk premium for bonds with inferior readability in their prospectuses.

TLAC bonds and bank risk-taking

This study explores the relation between total loss-absorbing capacity (TLAC) bonds and bank risk-taking. TLAC bonds contain a unique instrument in that they entail “structural subordination,” which enables them to be converted into equity to resolve a failure of subsidiaries of global systemically important banks (G-SIBs). Given the debate in the literature over the impact of subordinated bonds on issuers’ risk-taking, we find that a larger amount of TLAC bond issuance is associated with higher risk. Although TLAC regulation is designed to mitigate systemic risk, we unveil the opposite result, which may increase the probability of G-SIB default.

The fall of DHFL: hidden issues that everyone ignored

Learning outcomes The learning outcomes are as follows: to be able to evaluate early warning signs/red flags through financial statement analysis; to be able to analyse company’s credit or debt servicing using a thorough process of fundamental analysis; to be able to analyse and decode the financial health of an organization through different financial tools applicable according to the industry such as default probability and financial ratios; and to be able to synthesize credit rating framework and role of credit rating agencies in the bond market. Case overview/synopsis In late January 2019, the allegation by an online investigative portal about the misuse of the Dewan Housing Finance Corporation Ltd. (DHFL) money by its promoter for buying asset abroad was the start of the fall of the non-banking finance company giant. This was followed by a series of downgrade by credit rating agencies on its debt and eventual default on its interest payment on 4 June 2019 which upset multiple portfolio investors and the regulators. Investors became sceptical about the regulator’s policy and inefficiencies of credit rating agencies in predicting the default along with asset management houses which were expected to guard investors’ interest. One investor, Shikhar Pachori, decided to scrutinize all hidden information on DHFL to investigate if DHFL crisis arises because of unknown factors which was not in control of management or if it a clear negligence on the part of all involved parties. The case tries to emphasize the aspect of Asset-Liability Management and process of credit analysis while looking for red flags which aids in identifying any stress in company’s financial or any potential default by company. Complexity academic level This case can be used in the advance level of post-graduate finance course or MBA program for elective/specialization courses such as Financial Statement Analysis, Financial Institutions and Market and Fixed Income. Supplementary materials Teaching notes are available for educators only. Subject code CSS 1: Accounting and Finance

ANALISIS PENGARUH USIA, JUMLAH PINJAMAN, PENGALAMAN USAHA DAN OMZET USAHA TERHADAP KELANCARAN ANGSURAN PEMBIAYAAN ULTRA MIKRO (UMi)

The purpose of this research is to develop a predictive model for the probability of default from Ultra Micro financing customers (UMi) which was initiated by the Government Investment Agency of the Ministry of Finance of the Republic of Indonesia in 2017. The analytical method uses Logistics Regression (Logit) as binary logit by sampling observational data. in 2021 by purposive sampling as many as 398 debtors consisting of 46 defaulted debtors and 352 current debtors. The dependent variable uses binary data with dummy "0" for defaulted debtors, while the dummy data "1" for current debtors and the Independent variable uses a gross revenue, education level, financing plafond provided, business experience and age of the debtor. This study reveals that only the education level and age of the debtor have a significant effect on the probability of non-performing loans to ultra micro customers.

Probability of default and political instability in the MENA region

PurposeThis study aims to empirically investigate the impact of political instability on the banking stability of the dual banking system in the Middle East and North African (MENA) countries.Design/methodology/approachThe study measures banking stability with probability of default (PD) and Zscore by employing the generalised method of moment (GMM) between 2007 and 2021 on the dual banking system in the region. The authors further estimate short-long-run situations coupled with a robustness test using a generalised least square (GLS) model.FindingsThe authors' findings indicate that institutional factors of political stability, crisis period, high-crisis countries, law and order and macroeconomic indicators influence the two types of banking stability in the region. The authors found the consistency of the factors explaining stability in the region in both short-and long-run situations. Consequently, the study also reveals the adverse effects of crisis periods and high-crisis countries on banking stability.Practical implicationsThe results of this study explicitly identify the critical need for sustaining political stability and abiding by laws and order to achieve dual banking stability in the region. Therefore, policymakers may consider allowing the region's banks to operate beyond retail banking since diversification enhances banking stability.Originality/valueThe authors' study balances by employing dual stability measurement in predicting the impact of political instability, law and order and other indicators on the MENA region's two banking models. This study uncovers the effect of the global crisis period on banking stability and high-crisis countries in the region and verifies the models' robustness.

Pricing of Credit Default Swaps from the Perspective of Credit Enhancement in PPP Projects

The difficulty in financing has become the primary obstacle in the process of promoting a public–private partnership (PPP). Asset securitization is a financial model that can exchange the predictable cash flow of illiquid PPP project assets with the current cash flow, and credit enhancement is crucial in this process. Different from the traditional external credit enhancement of PPP projects based on government guarantees, this paper introduces an innovative credit risk management tool, i.e., credit default swaps (CDS), into the process of asset securitization in the PPP model. In order to avoid opportunistic behavior caused by information asymmetry in the process of financial product transaction, a CDS trading contract between PPP project investors and risk management institutions based on the principal–agent theory and a flexible CDS pricing model is proposed. Through a demonstration case of the Leshan to Rongjiang Expressway in China, the volatility correlation among CDS contract default probability, pricing, and related factors, such as default limits, operation period, compensation amount, project investment return, investment return volatility, and PPP project investors’ expected inputs, is obtained. The study shows that (1) appropriate CDS pricing helps to generate investors’ high expected inputs and diligence with controls; (2) there is a positive correlation between the change of default limit and compensation amount, and the set value of default limit should not be too high, otherwise it may induce the increase of default probability; and (3) based on the high return on assets and moderate asset volatility of PPP projects, the probability of default of CDS contracts is low. The innovative financial mechanism developed by the principal–agent theory could enrich the credit enhancement methods in asset securities of PPP projects.