The Bloomberg Corporate Default Risk Model (DRSK) for Public Firms

Bondioli, M.; Goldberg, Martin; Hu, Nan; Li, Chengrui; Maalaoui, Olfa; Stein, Harvey J.

doi:10.2139/ssrn.3911300

Cited by 6 publications

(10 citation statements)

References 8 publications

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“…The DRSK is calibrated to historical financials over a 20 year period containing records for over 65,000 firms. The models achieve high-performance levels in adjusted pseudo-R squared (e.g., between 34% and 47%) [51]. The model DP is predictive of credit events up to a horizon of five years and tracks the realized default rates closely over time.…”

Section: The Bloomberg Corporate Default Risk Model (Drsk) For Public...mentioning

confidence: 89%

“…The DRSK is a hybrid model combining a statistical approach with structural models. Bondolini et al [51] used logistic regression to estimate the probability of default events based on factors that best capture credit risk.…”

Section: The Bloomberg Corporate Default Risk Model (Drsk) For Public...mentioning

confidence: 99%

“…The model is calibrated by logistic regression of the model's factors against the default indicator operation set. Using marginal DPs from the logistic regression, one can obtain cumulative DPs for each tenor {0.25, 0.5, 0.75, 1, 2, 3, 4, 5} in the years as follows in [51]. In the same way, annualized DP can be obtained as follows in Equations ( 27) and ( 28):…”

Section: The Bloomberg Corporate Default Risk Model (Drsk) For Public...mentioning

confidence: 99%

“…The model DP is predictive of credit events up to a horizon of five years and tracks the realized default rates closely over time. According to Bondoli et al [51], the model is responsive to market conditions; default probabilities drop during economic expansions and rise during economic contractions.…”

Section: The Bloomberg Corporate Default Risk Model (Drsk) For Public...mentioning

confidence: 99%

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Default Probabilities and the Credit Spread of Mexican Companies: The Modified Merton Model

Morales-Bañuelos,

Fernández-Anaya

2023

Mathematics

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This study aims to identify the model that best approximates the credit spread that should be fixed on debt instruments issued by both companies listed on the Mexican Stock Market, considering the particularities of the Mexican market. Five models were analyzed: Merton’s model, Brownian Motion Model, Power Law Brownian Motion Model, Bloomberg’s model, and the model presented in this paper, which includes the conformable derivatives, taking as a reference the change in the variable as other authors have done, and the Bloomberg corporate default risk model (DRSK) for publics firms. We concluded that the modified Merton model approximates, to a greater extent, the credit spreads that fix on a prime rate on the loans granted to Mexican non-financial companies.

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Section: The Bloomberg Corporate Default Risk Model (Drsk) For Public...mentioning

confidence: 89%

Section: The Bloomberg Corporate Default Risk Model (Drsk) For Public...mentioning

confidence: 99%

Section: The Bloomberg Corporate Default Risk Model (Drsk) For Public...mentioning

confidence: 99%

Section: The Bloomberg Corporate Default Risk Model (Drsk) For Public...mentioning

confidence: 99%

See 2 more Smart Citations

Default Probabilities and the Credit Spread of Mexican Companies: The Modified Merton Model

Morales-Bañuelos,

Fernández-Anaya

2023

Mathematics

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“…Panel C presents the summary statistics by the firm's credit quality. Bondioli et al (2021) define investment-grade firms as those with a one-year default probability of less than 0.52%. The summary statistics indicate that below-investment-grade firms generally have fewer forecasters, lower mean earnings forecasts, market capitalizations, share prices, higher betas, five-day returns, and 10-day share price volatility than investment-grade firms.…”

Section: Descriptive Statisticsmentioning

confidence: 99%

Herding the crowds: how sentiment affects crowdsourced earnings estimates

Garcia

2024

Financ Mark Portf Manag

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This study investigates the impact of firm-level investor sentiment derived from Twitter and news media on herding behavior among contributors on Estimize, a leading platform for crowdsourced earnings forecasts. The findings show that sentiment gleaned from tweets and news media content positively influences herding among Estimize contributors. Notably, herding intensifies when Twitter and news sentiment polarities align, while divergent sentiment polarities diminish this herding effect. Additionally, the analysis indicates that firms with investment-grade ratings and those characterized by low valuation uncertainty are particularly prone to sentiment-driven herding. Importantly, positive sentiment is identified as having a more potent influence on herding behavior than negative sentiment. By focusing on Estimize contributors, this study offers insights into how firm-level sentiment cues shape the crowd’s herding behavior, offering new perspectives on how different media sources shape the wisdom of the crowd.

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Factors in Swiss franc corporate bond returns

Manser¹

2023

Financ Mark Portf Manag

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The Bloomberg Corporate Default Risk Model (DRSK) for Public Firms

Cited by 6 publications

References 8 publications

Default Probabilities and the Credit Spread of Mexican Companies: The Modified Merton Model

Default Probabilities and the Credit Spread of Mexican Companies: The Modified Merton Model

Herding the crowds: how sentiment affects crowdsourced earnings estimates

Factors in Swiss franc corporate bond returns

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