Journal articles: 'Default (finance)'

1

Phelps, Bruce D. "Defaults and Losses Given Default of Structured Finance Securities." CFA Digest 34, no. 4 (November 2004): 29–31. http://dx.doi.org/10.2469/dig.v34.n4.1561.

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Hu, Jian, and Richard Cantor. "Defaults and Losses Given Default of Structured Finance Securities." Journal of Fixed Income 13, no. 4 (March 31, 2004): 5–24. http://dx.doi.org/10.3905/jfi.2004.391024.

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Lefevre, Alexandra, and Agnes Tourin. "Incorporating Climate Risk into Credit Risk Modeling: An Application in Housing Finance." FinTech 2, no. 3 (September 7, 2023): 614–40. http://dx.doi.org/10.3390/fintech2030034.

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This paper examines the integration of climate risks into structural credit risk models. We focus on applications in housing finance and argue that mortgage defaults due to climate disasters have different statistical features than default due to household-specific reasons. We propose two models incorporating climate risk based on two separate default definitions. The first focuses on default as a response to a decrease in home value, and the second defines default as a consequence of missed mortgage payments. Using mortgage performance data during Hurricane Harvey, we conduct an empirical study whose results suggest that climate events are potentially another source of undiversifiable credit risk affecting homeowners’ ability to make contractual monthly payments. We also show that incorporating this climate-specific default process may capture additional uncertainty in default probability assessments.

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Ahmad, Sanep. "‘Banking Panics’ and Islamic Finance Principles: Lessons from the Current Crisis." ICR Journal 1, no. 2 (December 15, 2009): 358–61. http://dx.doi.org/10.52282/icr.v1i2.753.

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Clearly, the recent ‘bank panics’ and global economic crisis occurred mainly due to the result of debt defaults in subprime mortgages. Firstly, default by home buyers for their loans repayment to the banks and secondly default by banks for their bond repayment in the mortgage bond market. If debt defaults can be avoided in the first place, bank panics and economic crisis will most likely not happen. This means that the origin of the problem is related to bank defaults in the Sub-Prime Model which arises due to poor credit evaluation by banks. Therefore the solution for the current crises should be focused on ways of avoiding debt defaults by borrowers.

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TENG, LONG, MATTHIAS EHRHARDT, and MICHAEL GÜNTHER. "BILATERAL COUNTERPARTY RISK VALUATION OF CDS CONTRACTS WITH SIMULTANEOUS DEFAULTS." International Journal of Theoretical and Applied Finance 16, no. 07 (November 2013): 1350040. http://dx.doi.org/10.1142/s0219024913500404.

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We analyze the general risk-neutral valuation for counterparty risk embedded in a Credit Default Swap (CDS) contract by adapting the recent findings of Brigo and Capponi (2009) to allow for simultaneous defaults among the two parties and the underlying reference credit, while the counterparty risk is considered bilaterally. For the default intensities, we employ a Markov copula model allowing for the possibility of a simultaneous default. The dependence between defaults of three names in a CDS contract and the wrong-way risk will thus be represented by the possibility of simultaneous defaults. We investigate numerically the effect of considering simultaneous defaults on the counterparty risk valuation of a CDS contract. Finally, we study a CDS contract between Royal Dutch Shell and British Airways based on Lehman Brothers applying this methodology, illustrating the bilateral adjustments with the possibility of simultaneous defaults in concrete crisis situations.

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Klompjan, Richard, and Marc J. F. Wouters. "Default Risk in Project Finance." Journal of Structured Finance 8, no. 3 (October 31, 2002): 10–21. http://dx.doi.org/10.3905/jsf.2002.320283.

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Castagnolo, Fernando, and Gustavo Ferro. "Models for predicting default: towards efficient forecasts." Journal of Risk Finance 15, no. 1 (January 28, 2014): 52–70. http://dx.doi.org/10.1108/jrf-08-2013-0057.

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Purpose – The purpose of this paper is to assess and compare the forecast ability of existing credit risk models, answering three questions: Can these methods adequately predict default events? Are there dominant methods? Is it safer to rely on a mix of methodologies? Design/methodology/approach – The authors examine four existing models: O-score, Z-score, Campbell, and Merton distance to default model (MDDM). The authors compare their ability to forecast defaults using three techniques: intra-cohort analysis, power curves and discrete hazard rate models. Findings – The authors conclude that better predictions demand a mix of models containing accounting and market information. The authors found evidence of the O-score's outperformance relative to the other models. The MDDM alone in the sample is not a sufficient default predictor. But discrete hazard rate models suggest that combining both should enhance default prediction models. Research limitations/implications – The analysed methods alone cannot adequately predict defaults. The authors found no dominant methods. Instead, it would be advisable to rely on a mix of methodologies, which use complementary information. Practical implications – Better forecasts demand a mix of models containing both accounting and market information. Originality/value – The findings suggest that more precise default prediction models can be built by combining information from different sources in reduced-form models and combining default prediction models that can analyze said information.

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AMERIO, EMANUELE, PIETRO MULIERE, and PIERCESARE SECCHI. "REINFORCED URN PROCESSES FOR MODELING CREDIT DEFAULT DISTRIBUTIONS." International Journal of Theoretical and Applied Finance 07, no. 04 (June 2004): 407–23. http://dx.doi.org/10.1142/s0219024904002505.

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Based on a Reinforced Urn Process introduced by Muliere et al. [11], we propose a stochastic model for the probability of credit default for debt issuers belonging to the same Moody's rated class. The model predicts how a default probability belonging to a given term structure evolves in time as information about credit defaults of debt issuers with the same Moody's rating becomes available. Connections between implied credit default probabilities and credit spreads will be exploited.

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Huang, MeiChi. "Markov-switching impacts of housing-market expectations on credit markets." Managerial Finance 46, no. 3 (December 3, 2019): 381–400. http://dx.doi.org/10.1108/mf-08-2019-0391.

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Purpose The purpose of this paper is to investigate linkages between households’ expectations and credit markets in the housing crisis. Design/methodology/approach In the Markov-switching framework, the sample period is classified into high- and low-impact regimes based on impacts of expectations on default rates, and the good-time-to-buy (GTTB) index is chosen to proxy for expectations toward the housing-market dynamics. Findings The results suggest that in high-impact regimes, optimistic expectations are substantially associated with lower defaults for all default rates analyzed, and second mortgage defaults are more sensitive to households’ expectations than first mortgage defaults. In low-impact regimes, the GTTB index significantly influences composite and first-mortgage default rates, but its impact is insignificant for second mortgage and bankcard default rates. Originality/value The results provide compelling evidence that households’ expectations play more important roles in credit markets in turmoil periods.

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Haggag, Kareem, and Giovanni Paci. "Default Tips." American Economic Journal: Applied Economics 6, no. 3 (July 1, 2014): 1–19. http://dx.doi.org/10.1257/app.6.3.1.

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We examine the role of defaults in high-frequency, small-scale choices using unique data on over 13 million New York City taxi rides. Using a regression discontinuity design, we show that default tip suggestions have a large impact on tip amounts. These results are supported by a secondary analysis that uses the quasi-random assignment of customers to different cars to examine default effects on a wider range of fares. Finally, we highlight a potential cost of setting defaults too high, as a higher proportion of customers opt to leave no credit card tip when presented with the higher suggested amounts. (JEL D12, L92)

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Soga, Nomaphelo, Darlington Onojaefe, Lawrence Obokoh, and Wilfred Ukpere. "Consumers’ Perception of The Cost of Credit Default in The Vehicle Finance Industry in South Africa." Journal of Economic Development, Environment and People 10, no. 4 (December 30, 2021): 76–90. http://dx.doi.org/10.26458/jedep.v10i4.721.

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The risk that a borrower may not fulfil his/her borrowing obligation presents credit owner (lender) a default risk management opportunity to maximize the risk-adjusted rate of return and to maintain minimum exposure to default associated cost. This paper investigated respondents’ perception of the cost of credit default and examines requirements for default risk management (DRM) in the vehicle finance industry in South Africa. It is noted that with an increased level of consumer indebtedness, unstable economy, high unemployment, opportunistic risks like health pandemics, vehicle financing faces a higher probability of default from borrowers. This descriptive investigation utilised quantitative approach using a survey method to collect data from 381 purposive randomly selected respondents who are vehicle finance customers in South Africa, Cape Town specifically. Data collection took place in the Western Cape over a nine-month period, utilising personal interview, and emails to administer questionnaires to vehicle finances’ customers as data collection instruments. Responses received were codified and quantitative data were analysed using the Statistical Packages for Social Sciences (SPSS version 25) The paper found mixed and variable respondents’ perception of the cost of credit default. In conclusion, it is perceived that South Africa debt would become more costly with credit default. It can be recommended that a default risk management intervention be applied to manage credit default risk within the context of the unified credit assessment policy in South Africa.

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LI, HUI. "A NOTE ON THE DOUBLE IMPACT ON CVA FOR CDS: WRONG-WAY RISK WITH STOCHASTIC RECOVERY." International Journal of Theoretical and Applied Finance 16, no. 03 (May 2013): 1350013. http://dx.doi.org/10.1142/s0219024913500131.

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Current CVA modeling framework has ignored the impact of stochastic recovery rate. Due to the possible negative correlation between default and recovery rate, stochastic recovery rate could have a doubling effect on wrong-way risk. In the case of a payer CDS, when counterparty defaults, the CDS value could be higher due to default contagion while the recovery rate may also be lower if the economy is in a downturn. Using our recently proposed model of correlated stochastic recovery in the default time Gaussian copula framework, we demonstrate this double impact on wrong-way risk in the CVA calculation for a payer CDS. We also present a new form of Gaussian copula that correlates both default time and recovery rate.

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Lestiani, Karina, Nuzul Rahmayani, and Mahlil Andriaman. "Wanprestasi Dalam Perjanjian Pembiayaan Konsumen (Studi Putusan Nomor 11/Pdt.G/2022/PN Bkt)." Wajah Hukum 7, no. 2 (October 31, 2023): 567. http://dx.doi.org/10.33087/wjh.v7i2.1186.

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Activities between consumers and consumer financing institutions will occur if there is an agreement. In an agreement, an action cannot be separated from a person who cannot fulfill his obligations so that it can be said to have committed a negligence or made a mistake which is called a default. This research discusses Defaults in Consumer Financing Agreements (Decision Study Number 11/Pdt.G/2022/PN BKt). This research raises two problems, namely 1) How is the implementation of the agreement in consumer financing default cases based on the decision of the Bukitinggi District Court Number 11/Pdt.G/2022/PN Bkt? 2) What is the analysis of the judge's considerations in settling default cases in consumer financing agreements based on Bukitinggi District Court decision No. 11/Pdt.G/2022/PN Bkt? This study uses a normative juridical method. The data source used is secondary data, namely data obtained through a literature study with primary legal materials, secondary legal materials and tertiary legal materials. Data collection was carried out by (normative juridical) by using library research (library research) which is a data collection tool that is not directed directly to research subjects. The data analysis used is a qualitative analysis. The results of the study show how the judge considers the settlement of default cases in consumer financing agreements based on the decision of the Bukitinggi District Court Number 11/Pdt.G/2022/PN Bkt and the legal consequences of engagement from a civil aspect in the occurrence of default for both parties in case Number 11/Pdt .G/2022/PN Bkt.. In this decision the judge decided that PT. Mandiri Tunas Finance who defaulted on CV. Roberto First Works. The judge should have decided based on the Civil Code, to determine whether someone has defaulted based on the provisions of Article 1238 of the Civil Code13. In this case the legal consequence of the engagement from a civil aspect in the occurrence of default for both parties is to punish PT. Mandiri Tunas Finance to pay the costs of the case until the trial has been decided in the amount of Rp. 616,000 (six hundred and sixteen thousand rupiah).

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RODRIGUES, MATHEUS PIMENTEL, and ANDRE CURY MAIALY. "MEASURING DEFAULT RISK FOR A PORTFOLIO OF EQUITIES." International Journal of Theoretical and Applied Finance 22, no. 01 (February 2019): 1950012. http://dx.doi.org/10.1142/s0219024919500122.

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This work evaluates some changes proposed by the Basel Committee on Banking Supervision in regulating capital allocation in the trading book for equities following a company default. In the last decade, the committee designed some measures to account for the risk of a company default that the ten-day value-at-risk measure does not capture. The first and more conservative measure designed to capture the effect of defaults was the incremental risk charge. With time, this measure evolved into the default risk charge. We use a Merton model to compute the probability of default and compare this probability to simulated asset returns in order to compute the one-year value-at-risk and capture the risk of a company default. The analysis compares portfolios of Ibovespa companies and S&P 500 companies. Additionally, we propose a method to account for the correlation in the companies and compare the effects of the standard method of capital allocation to those of our models.

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15

ARENTSEN, ERIC, DAVID C. MAUER, BRIAN ROSENLUND, HAROLD H. ZHANG, and FENG ZHAO. "Subprime Mortgage Defaults and Credit Default Swaps." Journal of Finance 70, no. 2 (March 12, 2015): 689–731. http://dx.doi.org/10.1111/jofi.12221.

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16

Vu, Joseph D. V. "Default Rates on Structured Finance Securities." CFA Digest 35, no. 2 (May 2005): 13–15. http://dx.doi.org/10.2469/dig.v35.n2.1656.

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Lucas, Douglas J., Laurie S. Goodman, and Frank J. Fabozzi. "Default Rates on Structured Finance Securities." Journal of Fixed Income 14, no. 2 (September 30, 2004): 44–53. http://dx.doi.org/10.3905/jfi.2004.439836.

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Kohv, Keijo, and Oliver Lukason. "What Best Predicts Corporate Bank Loan Defaults? An Analysis of Three Different Variable Domains." Risks 9, no. 2 (January 25, 2021): 29. http://dx.doi.org/10.3390/risks9020029.

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This paper aims to compare the accuracy of financial ratios, tax arrears and annual report submission delays for the prediction of bank loan defaults. To achieve this, 12 variables from these three domains are used, while the study applies a longitudinal whole-population dataset from an Estonian commercial bank with 12,901 observations of defaulted and non-defaulted firms. The analysis is performed using statistical (logistic regression) and machine learning (neural networks) methods. Out of the three domains used, tax arrears show high prediction capabilities for bank loan defaults, while financial ratios and reporting delays are individually not useful for that purpose. The best default prediction accuracies were 83.5% with tax arrears only and 89.1% with all variables combined. The study contributes to the extant literature by enhancing the bank loan default prediction accuracy with the introduction of novel variables based on tax arrears, and also by indicating the pecking order of satisfying creditors’ claims in the firm failure process.

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FONTANA, CLAUDIO, and WOLFGANG J. RUNGGALDIER. "CREDIT RISK AND INCOMPLETE INFORMATION: FILTERING AND EM PARAMETER ESTIMATION." International Journal of Theoretical and Applied Finance 13, no. 05 (August 2010): 683–715. http://dx.doi.org/10.1142/s0219024910005966.

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We consider a reduced-form credit risk model where default intensities and interest rate are functions of a not fully observable Markovian factor process, thereby introducing an information-driven default contagion effect among defaults of different issuers. We determine arbitrage-free prices of OTC products coherently with information from the financial market, in particular yields and credit spreads and this can be accomplished via a filtering approach coupled with an EM-algorithm for parameter estimation.

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Fons, Jerome S., and Andrew E. Kimball. "Corporate Bond Defaults and Default Rates 1970–1990." Journal of Fixed Income 1, no. 1 (June 30, 1991): 36–47. http://dx.doi.org/10.3905/jfi.1991.692345.

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CRÉPEY, S., M. JEANBLANC, and D. WU. "INFORMATIONALLY DYNAMIZED GAUSSIAN COPULA." International Journal of Theoretical and Applied Finance 16, no. 02 (March 2013): 1350008. http://dx.doi.org/10.1142/s0219024913500088.

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In order to dynamize the static Gaussian copula model of portfolio credit risk, we introduce a model filtration made of a reference Brownian filtration progressively enlarged by the default times. This yields a multidimensional density model of default times, where, as opposed to the classical situation of the Cox model, the reference filtration is not immersed into the enlarged filtration. In mathematical terms this lack of immersion means that martingales in the reference filtration are not martingales in the enlarged filtration. From the point of view of financial interpretation this means default contagion, a good feature in the perspective of modeling counterparty wrong-way risk on credit derivatives. Computational tractability is ensured by invariance of multivariate Gaussian distributions through conditioning by some components, the ones corresponding to past defaults. Moreover the model is Markov in an augmented state-space including past default times. After a discussion of different notions of deltas, the model is applied to the valuation of counterparty risk on credit derivatives.

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Aitken, Rob. "The Sovereignty of Finance? Distress and the Financialization of Sovereign Debt." Perspectives on Global Development and Technology 18, no. 5-6 (December 10, 2019): 493–526. http://dx.doi.org/10.1163/15691497-12341529.

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Abstract This article argues that the relationship between finance and state sovereignty is neither automatic nor understandable in some generalized manner. To develop this argument, I pay particular attention to the financialization of distressed sovereign debt, especially sovereign debt defaults in the Global South with particular reference to Argentina’s default in 2001 and the string of legal cases it triggered. These legal processes breathed a strange after-life into Argentina’s defaulted debt by converting that debt into fully commodified financial contracts. I argue that the financialization of sovereign debt is enabled by a long and complex evolution in the application of the doctrine of restrictive sovereign immunity. This financialization, moreover, is indicative of ways in which forms of financial distress are reworked as renewed sources of financial value. This provokes questions about the very relationship between waste and value in our global political economy.

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DI GRAZIANO, GIUSEPPE, and L. C. G. ROGERS. "A DYNAMIC APPROACH TO THE MODELING OF CORRELATION CREDIT DERIVATIVES USING MARKOV CHAINS." International Journal of Theoretical and Applied Finance 12, no. 01 (February 2009): 45–62. http://dx.doi.org/10.1142/s0219024909005142.

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The modeling of credit events is in effect the modeling of the times to default of various names. The distribution of individual times to default can be calibrated from CDS quotes, but for more complicated instruments, such as CDOs, the joint law is needed. Industry practice is to model this correlation using a copula/base correlation approach, which suffers significant deficiencies. We present a new approach to default correlation modeling, where defaults of different names are driven by a common continuous-time Markov process. Individual default probabilities and default correlations can be calculated in closed form. We provide semi-analytic formulas for the pricing of CDO tranches via Laplace-transform techniques which are both fast and easy to implement. The model calibrates to quoted tranche prices with a high degree of precision and allows one to price non-standard tranches in a consistent and arbitrage-free manner. The number of parameters of the model is flexible and can be adjusted to adapt to the set of market data one is calibrating to. More importantly, the model is dynamically consistent and can be used to price options on tranches and other exotic path-dependent products.

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Wang, Yuhao, Jiaxian Shen, Jinnan Pan, and Tingqiang Chen. "A Credit Risk Contagion Intensity Model of Supply Chain Enterprises under Different Credit Modes." Sustainability 14, no. 20 (October 19, 2022): 13518. http://dx.doi.org/10.3390/su142013518.

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The rapid development of theoretical and practical innovations in corporate finance driven by supply chain finance has exacerbated the complexity of credit default risk contagion among supply chain enterprises. Financial risks in the supply chain greatly hinder its sustainable development; thus, strengthening financial risk management is necessary to ensure the sustainability of the supply chain. Based on the single-channel and dual-channel credit financing models of retailers in the supply chain, the purpose of this paper was to construct a model of the intensity of credit default risk contagion among supply chain enterprises under different credit financing models, and investigate the influencing factors of credit risk contagion among supply chain enterprises and its mechanism of action through a computational simulation system. The results were as follows: (1) there was a positive relationship between the production cost of suppliers and the contagion intensity of the supply chain credit default risk, and the contagion effect of the supply chain credit default risk increased significantly when both retailers defaulted on trade credit to suppliers; (2) the market retail price of the product was negatively related to the contagion intensity of the supply chain credit default risk, and the contagion intensity of the supply chain credit default risk increased significantly when both retailers defaulted on trade credit to the supplier; (3) the intensity of credit default risk contagion in the supply chain was positively correlated with both the commercial bank risk-free rate and the trade credit rate, and retailers’ repayment priority on trade credit debt was negatively correlated with suppliers’ wholesale prices and positively correlated with retailers’ order volumes, with retailers’ repayment priority positively affecting retailers’ bank credit rates and negatively affecting suppliers’ bank credit rates; and (4) retailers’ repayment priority on trade credit debt was negatively correlated with the intensity of supply chain credit default risk contagion, and the lower the retailer’s bank credit limit, the higher the trade credit limit, and the stronger the credit default contagion effect in the supply chain.

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Zhou, Chunsheng. "An Analysis of Default Correlations and Multiple Defaults." Review of Financial Studies 14, no. 2 (April 2001): 555–76. http://dx.doi.org/10.1093/rfs/14.2.555.

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Foster, Benjamin P., Terry J. Ward, and Jon Woodroof. "An Analysis of the Usefulness of Debt Defaults and Going Concern Opinions in Bankruptcy Risk Assessment." Journal of Accounting, Auditing & Finance 13, no. 3 (July 1998): 351–71. http://dx.doi.org/10.1177/0148558x9801300311.

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This study extends the research of Hopwood et al. (1994) and Mutchler et al. (1997) by empirically investigating the relationships between loan defaults, violation of loan covenants, going-concern opinions, and bankruptcy in bankruptcy prediction models. One objective of this study is to empirically test the ability of loan defaults/accommodations and loan covenant violations to assess the risk of bankruptcy. Another objective of this study is to investigate the impact of failing to control for these two distress events on results from tests of the usefulness of going-concern opinions in assessing bankruptcy risk. Results suggest that loan default/accommodation and loan covenant violation are both significant explanatory variables of bankruptcy at the time of the last annual report before the event. While a going-concern opinion variable appears to significantly explain bankruptcy, it is not significant when included in a model with loan default/accommodation and covenant violation variables. Consequently, our results suggest that researchers should include both loan default/accommodation and covenant violation as control variables when using bankruptcy to test the usefulness of going-concern opinions.

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Gale, Douglas, and Piero Gottardi. "Bankruptcy, Finance Constraints, and the Value of the Firm." American Economic Journal: Microeconomics 3, no. 2 (May 1, 2011): 1–37. http://dx.doi.org/10.1257/mic.3.2.1.

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We study a competitive model in which market incompleteness implies that debt-financed firms may default in some states of nature, and default may lead to the sale of the firms' assets at fire sale prices when a finance constraint is binding. The anticipation of such “losses” alone may distort firms' investment decisions. We characterize the conditions under which fire sales occur in equilibrium, and their consequences on firms' investment decisions. We also show that endogenous financial crises may arise in this environment, with asset prices collapsing as a result of pure self-fulfilling beliefs. Finally, we examine alternative interventions to restore the efficiency of equilibria. (JEL D83, G31, G32, G33)

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Maloney, David, Sung-Chul Hong, and Barin Nag. "Economic Disruptions in Repayment of Peer Loans." International Journal of Financial Studies 11, no. 4 (September 30, 2023): 116. http://dx.doi.org/10.3390/ijfs11040116.

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Economic disruptions can alter the likelihood of defaults on peer-to-peer loans, causing those impacted to adjust. The option to declare economic hardship and temporarily reduce the payment burden can provide some relief. When this occurs, the borrower’s financial qualifications have changed. The qualities instrumental in successfully securing the original loan terms must be reanalyzed to manage risk. This is a critical point in the life of the loan because the declaration of financial hardship can signal that the borrower’s ability to repay has diminished. We present a novel default detection scheme for borrowers experiencing an economic disruption based on the Two-Class Support Vector Machine, a data classification algorithm for supervised learning problems. The method utilizes data from actual loan records (15,355 loans from 2016 through 2020), specifically from borrowers who declared economic hardship. We provide a detailed description of the default detection process and present results that show defaults among borrowers experiencing financial hardship can be predicted accurately.

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Foote, Christopher L., and Paul S. Willen. "Mortgage-Default Research and the Recent Foreclosure Crisis." Annual Review of Financial Economics 10, no. 1 (November 2018): 59–100. http://dx.doi.org/10.1146/annurev-financial-110217-022541.

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This article reviews the surge in research on mortgage default inspired by the recent foreclosure crisis. Economists already understood a great deal about default, both theoretically and empirically, when the crisis began, but new research has moved the frontier further by improving data sources, building dynamic optimizing models of default, and explicitly addressing reverse causality between rising foreclosures and falling house prices. Mortgage defaults also featured prominently in early papers that pointed to subprime and other privately securitized mortgages as fundamental drivers of the housing boom, although this research has been criticized recently. Going forward, improvements to data and models will allow researchers to make progress on the two central questions in this literature. First, what are the relative contributions of adverse life events and negative equity to mortgage default? Second, why is default so rare, even among people with deep negative equity or acute financial distress?

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White, Benjamin X., Duo Jiang, and Dolores Albarracín. "The Limits of Defaults: The Influence of Decision Time on Default Effects." Social Cognition 39, no. 5 (October 2021): 543–69. http://dx.doi.org/10.1521/soco.2021.39.5.543.

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The stability of default effects to contextual features is critical to their use in policy. In this paper, decision time was investigated as a contextual factor that may pose limits on the efficacy of defaults. Consistent with the hypothesis that time constraints may increase reliance on contextual cues, four experiments, including a preregistered one of a nationally representative sample, and a meta-analysis that included four additional pilot experiments, indicated that short decision times increased the advantage of action defaults (i.e., the default option automatically endorsed the desired behavior) and that the default advantage was trivial or nonexistent when decision times were longer. These effects replicated for naturalistic as well as externally induced decision times and were present even when participants were unaware that time was limited. This research has critical implications for psychological science and allied disciplines concerned with policy in the domains of public health, finance and economics, marketing, and environmental sciences.

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Erturk, Erkan, and Thomas G. Gillis. "Default Behavior of Global Structured Finance Securities." Journal of Structured Finance 10, no. 3 (October 31, 2004): 48–55. http://dx.doi.org/10.3905/jsf.2004.443360.

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BRIGO, DAMIANO, ANDREA PALLAVICINI, and ROBERTO TORRESETTI. "CLUSTER-BASED EXTENSION OF THE GENERALIZED POISSON LOSS DYNAMICS AND CONSISTENCY WITH SINGLE NAMES." International Journal of Theoretical and Applied Finance 10, no. 04 (June 2007): 607–31. http://dx.doi.org/10.1142/s0219024907004342.

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We extend the common Poisson shock framework reviewed for example in Lindskog and McNeil [15] to a formulation avoiding repeated defaults, thus obtaining a model that can account consistently for single name default dynamics, cluster default dynamics and default counting process. This approach allows one to introduce significant dynamics, improving on the standard "bottom-up" approaches, and to achieve true consistency with single names, improving on most "top-down" loss models. Furthermore, the resulting GPCL model has important links with the previous GPL dynamical loss model in Brigo et al. [6], which we point out. Model extensions allowing for more articulated spread and recovery dynamics are hinted at. Calibration to both DJi-TRAXX and CDX index and tranche data across attachments and maturities shows that the GPCL model has the same calibration power as the GPL model while allowing for consistency with single names.

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RUTKOWSKI, MAREK, and ANTHONY ARMSTRONG. "VALUATION OF CREDIT DEFAULT SWAPTIONS AND CREDIT DEFAULT INDEX SWAPTIONS." International Journal of Theoretical and Applied Finance 12, no. 07 (November 2009): 1027–53. http://dx.doi.org/10.1142/s0219024909005579.

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The paper provides simple and rigorous, albeit fairly general, derivations of valuation formulae for credit default swaptions and credit default index swaptions. Results of this work cover as special cases the pricing formulae derived previously by Jamshidian [Finance and Stochastics8 (2004) 343–371], Pedersen [Quantitative Credit Research (2003)], Brigo and Morini (2005), and Morini and Brigo (2007). Most results presented in this work are completely independent of a particular convention regarding the specification of the fee and protection legs and thus they can also be used for valuation of other credit derivatives that exhibit similar features (for instance, options on CDO tranches). The main tools are a judicious choice of the reference filtration and a suitable specification of the risk-neutral dynamics for the pre-default (loss-adjusted) fair market spread.

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Yu, Tingting, and Yunxiang Huo. "Complexity Analysis of Consumer Finance following Computer LightGBM Algorithm under Industrial Economy." Mobile Information Systems 2022 (July 30, 2022): 1–9. http://dx.doi.org/10.1155/2022/2865959.

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In the advancement of communication technologies and electronic commerce, the industrial economy consumer finance serves as the source of financial stability and improves the economic and social status of the household; thus, there is a need to significantly prevent default in consumer finance. The prediction of individual default and prevent default in consumer finance has become a significant factor promoting the growth of the industrial economy in the financial sector. Thus, there is a need for an effective and efficient approach for promoting the industrial economy. This study aims to improve the prediction accuracy of individual default and prevent default in consumer finance using an optimized light gradient boosting machine (LightGBM) algorithm. The principles of LightGBM are explored, and the key factors affecting the performance of LightGBM are analyzed. The prediction performance of LightGBM is improved by balancing the training dataset. The performance of LightGBM is compared with several machine learning algorithms using Alibaba Cloud Tianchi big datasets. The experimental results show that the LightGBM prediction model achieved the highest performance with an accuracy of 81%, precision 88%, recall 72%, the area under the curve (AUC) with 0.76, and the F1 score (F1) with 0.79. The optimization of LightGBM can greatly enhance the prediction of personal default, which is helpful to the effective analysis of consumer finance complexity, reducing the investment risk of the financial industry and promoting the development of the industrial economy in the financial sector.

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Choe, Geon Ho, and Hyun Jin Jang. "Thekth default time distribution and basket default swap pricing." Quantitative Finance 11, no. 12 (October 21, 2010): 1793–801. http://dx.doi.org/10.1080/14697688.2010.494611.

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Kavishe, Wilfred Felix, Wilfred Felix Kavishe, NsubiliIsaga Pascal Ndaki, and Daudi Pascal Ndaki. "Interaction Effect Between Loan Officers’ Characteristics and Loan Default Rate on Crowdfunding Approval." PAN-AFRICAN JOURNAL OF BUSINESS MANAGEMENT 8, no. 1 (June 5, 2024): 125–42. http://dx.doi.org/10.61538/pajbm.v8i1.1528.

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MicroFinance Institution (MFI) officers screen loans for a prosocial crowdfunding campaign in developing economies. However, loan officers’ screening decision is influenced by loan officers’ default rate, hence the loan officers are likely to focus on the better borrowers. However, crowdfunding emerged to provide finance to entrepreneurs who are less likely to meet the loan screening requirements. Thus, this study examined the interaction effect between loan officers’ characteristics and loan defaults on crowdfunding approval. We usedordered logistic regression to primary data collected from loan officers in microfinance institutions that are registered by the largest prosocial crowdfunding platform Kiva asfield partners. The study found a significant interaction effect of loan officers’ default rate and gender, experience and crowdfunding awareness. Thus, the results implied that, the demographic characteristics of the loan officers are interacted by the loan officers’ default rate when deciding to approve a loan for a crowdfunding campaign. Therefore, the findings recommended imparting loan officers with techniques that will help them keep a low default rate and those loan officers with a low default rate should work on crowdfunding approval

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Li, Xiaoli, and Yanming Sun. "Network Evolutionary Game-Based Diffusion Mechanism regarding the Nonperformance of Farmers in Agricultural Supply Chain Finance." Discrete Dynamics in Nature and Society 2022 (February 28, 2022): 1–11. http://dx.doi.org/10.1155/2022/8550974.

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Agricultural supply chain finance effectively alleviates the problem of farmers’ credit constraints and realizes the commercialization and sustainability of agriculture. However, the rapid spread of farmers’ credit default behavior will seriously affect the stability of the agricultural supply chain and the wide application of agricultural supply chain finance. To prevent the rapid spread of farmers’ credit default behavior, the diffusion mechanism of farmers’ default behavior is studied with network evolutionary game. The results indicate the following: (a) When some farmers choose the default strategy because their default income is greater than their performance income, the default behavior in the small-world network will not spread to the whole network. However, in the scale-free network, when the default rate of return exceeds a certain threshold, it will lead to the spread of default behavior throughout the network. (b) In the small-world network, the spread of default will be inhibited to some extent with the increase of extra returns. However, the effect of raising extra returns on the spread of default behavior is not obvious in the scale-free network.

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Li, Wenli, Michelle J. White, and Ning Zhu. "Did Bankruptcy Reform Cause Mortgage Defaults to Rise?" American Economic Journal: Economic Policy 3, no. 4 (November 1, 2011): 123–47. http://dx.doi.org/10.1257/pol.3.4.123.

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Homeowners in financial distress can use bankruptcy to avoid defaulting on their mortgages, since filing loosens their budget constraints. But the 2005 bankruptcy reform made bankruptcy less favorable to homeowners and therefore caused mortgage defaults to rise. We test this relationship and find that the reform caused prime and subprime mortgage default rates to rise by 23% and 14%, respectively. Default rates rose even more for homeowners who were particularly negatively affected by the reform. We calculate that bankruptcy reform caused mortgage default rates to rise by one percentage point even before the start of the financial crisis. (JEL D14, G01, G21, K35)

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Schweikert, Jochen, and Markus Höchstötter. "Epidemiological spreading of mortgage default." International Journal of Housing Markets and Analysis 12, no. 1 (February 4, 2019): 74–93. http://dx.doi.org/10.1108/ijhma-05-2017-0047.

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Purpose This paper aims to introduce mathematical models to capture the spreading of epidemics to explain the expansion of mortgage default events in the USA. Design/methodology/approach The authors use the state of infectiousness and death to represent the subsequent steps of payment elinquency and default, respectively. As the local economic structure influences regional unemployment, which is a strong driver of mortgage default, the authors model interdependencies of regional mortgage default rates through employment conditions and vicinity. Findings Based on a large sample between 2000 and 2014 of loan-level data, the estimation of key parameters of the model is proposed. The model’s forecast accuracy shows an above-average performance compared to well-known approaches such as linear regression or logit models. Originality/value The key findings may be useful in understanding the dynamics of mortgage defaults and its spatial spreading.

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Gai, Lorenzo, and Federica Ielasi. "Operational drivers affecting credit risk of mutual guarantee institutions." Journal of Risk Finance 15, no. 3 (May 19, 2014): 275–93. http://dx.doi.org/10.1108/jrf-12-2013-0087.

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Purpose – The purpose of this paper is to investigate the drivers influencing the risk of default on mutual guaranteed loans. The authors aim to verify whether default is influenced by the specific business policies of mutual guarantee institutions (MGIs) and to recommend guidelines for directing their operating management. Design/methodology/approach – The authors analyse the guaranteed portfolios of 19 Italian MGIs and investigate the determinants of the defaulted positions at the end of June 2011. The sample consists of 167,777 guaranteed loans, of which 11,349 are in default. Using regression models, we identify the variables related to the business model of MGIs that are significantly associated with default on their positions. Findings – The defaulted positions of MGIs are significantly correlated with the type of issued guarantees. This condition should be considered in defining product and price policies. Practical implications – The authors identify some critical issues in the risk-taking processes of MGIs. The tested hypothesis highlights the opportunities for the optimisation of guaranteed loan portfolios, which is necessary for reducing the profitability/liquidity pressures of these financial institutions and enhancing their efficiency as instruments for mitigating the effects of credit rationing and promoting the revitalisation of small-and medium-sized enterprises. Originality/value – The results are based on an original and reserved dataset, which is not available in public financial statements or public statistics, but is collected directly from the MGIs that are part of the study.

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Fan, Jiaqi. "Predicting of Credit Default by SVM and Decision Tree Model Based on Credit Card Data." BCP Business & Management 38 (March 2, 2023): 28–33. http://dx.doi.org/10.54691/bcpbm.v38i.3666.

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With the global financial crisis and increased credit risk, default forecasting is playing an increasingly important role in every sector of the economy. Currently, there are linear models and machine learning models for predicting credit defaults. In recent years, big data risk control models are superior to traditional bank models in predicting default rates, and can also conduct business quickly and on a large scale. This paper compares the SVM and the decision tree model in the machine learning model based on the credit card loan data set, and finally evaluates the prediction effect between the two models. According to the study, the decision tree model outperforms the SVM in terms of prediction accuracy. The use of big data to conduct machine learning to predict credit conditions enables financial institutions to serve small, medium and micro enterprises that were difficult to cover by traditional finance on a large scale in the past. It is a world-class innovation in finance.

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Agarwal, Sumit, Yongheng Deng, and Jia He. "International Real Estate Review." International Real Estate Review 23, no. 2 (June 30, 2020): 151–87. http://dx.doi.org/10.53383/100298.

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The global economy is in the midst of a recession triggered by the ongoing pandemic of a novel coronavirus disease (COVID-19). The shutdown of the economy and a surge in the unemployment rate also cause stress to the US housing and mortgage system and create significant impacts on the default behaviour of mortgage borrowers. The potential rise in mortgage defaults may renew the long-standing debate over the empirical observation of why some mortgage borrowers do not default as "ruthlessly¨ as the finance theory predicts. In this paper, we propose an alternative theory to explain for the different default behaviours among mortgage borrowers. We hypothesize that the difference among time preferences across mortgage choices is one of the underlying factors that causes the heterogeneity in default patterns. Borrowers can either have a present-biased preference (overvaluing immediate outcomes), or a time-consistent preference (with standard exponential discounting). Borrowers with a present-biased preference are more likely to accept back-loaded mortgages that minimize up-front costs, even though this increases their risk of going ¡§underwater¡¨ and entering default when an adverse shock, such as the one from the ongoing pandemic, occurs.

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Murthy, Uma, and Paul Anthony Mariadas. "An Exploratory Study on the Factors Contributing Loan Repayment Default among the Loan Borrowers in Micro Finance Institutions in Shah Alam, Selangor." International Journal of Business and Management 12, no. 12 (November 20, 2017): 242. http://dx.doi.org/10.5539/ijbm.v12n12p242.

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This research is carried out to discover the factors contributing to loan repayment default in micro finance institutions based in Shah Alam, Selangor, Malaysia. The findings will be useful for the micro finance institutions in Malaysia in selecting and implementing suitable policies to reduce defaults. In this research, data is collected through questionnaires. These questionnaires are distributed to 120 loan borrowers of micro finance institution in Shah Alam, Selangor. Furthermore, the data was analyzed with the software known as Statistical package for Social Science, for short SPSS. This study established that nature of business operated by loan borrowers is one of the factors that will influence loan repayment. Finding of this study are established that there is a positive relationship between nature of business operation and negative relationship between age of borrowers, diversion of funds by borrowers as well as repayment schedule to loan defaults.

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Catão, Luis A. V., and Rui C. Mano. "Default premium." Journal of International Economics 107 (July 2017): 91–110. http://dx.doi.org/10.1016/j.jinteco.2017.03.005.

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Harju, Antti J. "A Rank Estimator Approach to Modeling Default Frequencies." Journal of Risk and Financial Management 16, no. 10 (October 15, 2023): 444. http://dx.doi.org/10.3390/jrfm16100444.

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This study introduces a non-parametric methodology for estimating expected frequencies of defaults and other credit events. The methodology allows for an independent estimation of a credit-quality variable, referred to as a default rank variable. In a subsequent step, the relationship between the rank variable and the expected default frequency is established. This analysis can be achieved by initially determining the functional dependence between the rank variable and the expected tail default frequencies representing the average default frequencies of entities ranked lower than a given rank value. The expected default frequency can then be derived from a simple linear integral equation. We propose a prototype model for public corporations which establishes generalized logistic function dependencies between the distance-to-default rank variable and the expected default frequencies in the log–log space. This relationship applies to public corporations across different credit rating categories.

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Taslim, M. A. "Entrepreneurship, Default, and the Problem of Development Finance." Canadian Journal of Economics 28, no. 4a (November 1995): 961. http://dx.doi.org/10.2307/135942.

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Hendriani, Mutia Marta. "LOANS SETTLEMENT AT FEDERAL INTERNATIONAL FINANCE Ltd. (FIF) BANDAR LAMPUNG CITY." Cepalo 5, no. 2 (December 31, 2021): 121–30. http://dx.doi.org/10.25041/cepalo.v5no2.2363.

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There are many ways to purchase a vehicle, including a credit system. However, various problems arise in its application regarding the settlement of bad loans caused by default debtors. This study aims to analyse the efforts made by Federal International Finance Ltd. (FIF) Bandar Lampung City in resolving motor vehicle bad loans due to default debtors. This study uses empirical normative legal research methods and qualitative descriptive methods. The data is obtained from direct observations and interviews, then linked to legal regulations concerning the default problem. The results indicate that Federal International Finance Ltd. has an ideal solution to resolve bad Loans through litigation and non-litigation. Efforts to settle bad loans through non-litigation could be made by giving a subpoena to the debtor. Furthermore, the creditor could take litigation by filing a civil lawsuit against the debtor for default according to Article 1243 of the Civil Code.

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Muhammad Kusnady Tabsir, Arfin Hamid, and Irwan Misbach. "Handling of Consumer Defaults at PT Adira Finance from the Perspective of Islamic Economics Ethics." Formosa Journal of Sustainable Research 2, no. 2 (February 27, 2023): 299–310. http://dx.doi.org/10.55927/fjsr.v2i2.3108.

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Defaults in motor vehicle loan agreements by consumers occur because of the consumptive nature of customer is not directly proportional to their income. In addition there is a bad faith from some consumer not to carry out their obligation as they should. The purpose of this study was to analyze the handling of defaults on motor vehicle agreements at PT Adira finance. This study used qualitative research method with field research. The result show that PT Adira Finance in dealing with the consumers default in motor vehicle loan agreements from the perspective of the Islamic business ethics has implemented several basic principles of business ethics in Islamic economics especially monotheism, free will, responsibility and truth. While the principle of balance and justice. PT. Adira Finance has not fully applied Islamic economic ethics, especially in term of writing of consumer debt that are eligible for assistance because they meet certain conditions such as going bankrupt

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Shea, Patrick E., and Paul Poast. "War and Default." Journal of Conflict Resolution 62, no. 9 (June 1, 2017): 1876–904. http://dx.doi.org/10.1177/0022002717707239.

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Sovereign borrowing is often used to cover the costs of war. This borrowing, coupled with war’s economic disruptions, strains states’ ability to honor debt promises. Contrary to conventional expectations, however, we find that default is not common after wars. To explain the relationship between war and sovereign default, this article lays out a selection effect argument: war participants are unlikely to default in the first place, while states likely to default are unable to acquire the financing necessary to fight a war. In sum, states that lack the financial means to adequately borrow avoid paths to war. After offering some examples of the selection mechanism at work, we present evidence that states unlikely to default will avoid entering the war sample. Our findings have implications for the inferences researchers make about war finance and war onset.

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Bi, Huixin, and Nora Traum. "Estimating Sovereign Default Risk." American Economic Review 102, no. 3 (May 1, 2012): 161–66. http://dx.doi.org/10.1257/aer.102.3.161.

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This paper uses Bayesian methods to estimate the sovereign default probability for Greece and Italy in the post-EMU period. We build a real business cycle model that allows for interactions among fiscal policy instruments, sovereign default risk, and a “fiscal limit,” which measures the maximum level of debt the government is willing to finance. We estimate the full nonlinear model using likelihood inference methods. Although we find that Greece historically had a lower default probability than Italy for a given debt level, our estimates suggest that the Italian government is more willing to service debt than the Greek government.

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Journal articles on the topic 'Default (finance)'

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