In this paper, a structural model for credit rating migration is developed and validated, by which the migration boundary is recovered for the first time.
Research on listed companies’ credit ratings, considering classification performance and interpretability
This study uses the correlation coefficient and F-test to select the initial features of a credit evaluation system, and then a validity index for a second selection to ensure that the feature system has the optimum ability to discriminate in determining…
Beyond the contract: client behavior from origination to default as the new set of the loss given default risk drivers
In this paper, we expand the modeling process by constructing a set of client-behavior-based predictors that can be used to construct more precise models, and we investigate the economic justifications empirically to examine their potential usage.
Bifractal receiver operating characteristic curves: a formula for generating receiver operating characteristic curves in credit-scoring contexts
This paper formulates a mathematical model for generating receiver operating characteristic (ROC) curves without underlying data.
This paper analyzes the relationship between option risk and expected return from the perspective of the underlying beta, and estimates the degree of correlation.
This paper examines which hybridization strategy is more suitable for credit risk assessment in the dynamic financial world.
Determination of weights for an optimal credit rating model based on default and nondefault distance maximization
This study proposes a credit rating model that accurately identifies default and nondefault companies by maximizing intergroup credit score deviations and minimizing intragroup deviations.
The author presents four methods to estimate the sample variance of the accuracy ratio and the area under the curve.
This paper aims to fill a gap in the literature by providing statistical properties of the population stability index (PSI) and some recommendations on its use.
A FAVAR modeling approach to credit risk stress testing and its application to the Hong Kong banking industry
In this paper, a credit risk stress testing model based on the factor-augmented vector autoregressive (FAVAR) approach is proposed to project credit risk loss under stressed scenarios.
This paper provides a theoretical and empirical analysis of alternative discount rate concepts for computing loss given default rates using historical bank workout data.
A k-means++-improved radial basis function neural network model for corporate financial crisis early warning: an empirical model validation for Chinese listed companies
This paper aims to simplify the early warning model for financial crises by collecting and analyzing the financial data of Chinese special treatment (ST) companies, normally listed companies and cancel special treatment (CST) companies.
The use of range-based volatility estimators in testing for Granger causality in risk on international capital markets
This study utilizes the extreme value theory (EVT) approach to compare the performance of a wide variety of range-based volatility estimators in the analysis of causality in risk between emerging and developed markets.
Old-fashioned parametric models are still the best: a comparison of value-at-risk approaches in several volatility states
The authors present backtesting results for 1% and 2.5% VaR of six indexes from emerging and developed countries using several of the best-known VaR models, including generalized autoregressive conditional heteroscedasticity (GARCH), extreme value theory…
This study compares the gradient-boosting model with four other well-known classifiers, namely, a classification and regression tree (CART), logistic regression (LR), multivariate adaptive regression splines (MARS) and a random forest (RF).
Risk-neutral densities: advanced methods of estimating nonnormal options underlying asset prices and returns
This work expands the analysis in Cooper (1999) and Santos and Guerra (2014), and the performance of the nonstructural models in estimating the "true" RNDs was measured through a process that generates "true" RNDs that are closer to reality, due to the…
This research develops a framework adopting conditional covariance modeling combined with various de-noising methods to estimate the portfolio VaR and proves the importance of DCC over the sample rolling method widely used in the industry.
International Financial Reporting Standard 9 expected credit loss estimation: advanced models for estimating portfolio loss and weighting scenario losses
In this paper, the authors propose a model to estimate the expected portfolio losses brought about by recession risk and a quantitative approach to determine the scenario weights. The model and approach are validated by an empirical example, where they…
This paper determines if enough data is available for forecasting or stress testing, a better measure of data length is required.
New approach delivers stable measure of conduct risk VAR, says senior op risk quant
In this study, the authors search for a benchmark model with available market-based predictors to evaluate the net contribution of internet search activity data in forecasting volatility. The paper conducts in-sample analysis and out-of-sample…
Consortium promises cost savings in outsourcing model validation, but some say pooling doesn’t float
Based on a survey of twenty-nine major financial institutions, this paper aims to advise banks and other financial services firms on what is needed to get ready for and become compliant with BCBS 239, especially in the area of risk data validation.
So-called ‘incremental value-at-risk’ offers future snapshot of op risk exposure, authors say