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Opening the black box – Quantile neural networks for loss given default prediction
16 references·3 citing·50 second hop
Opening the black box – Quantile neural networks for loss given default prediction (2021)Opening the black box – Quantile neural n…Machine learning for credit scoring: Improving logistic regression with non-linear decision-tree effects (2021)Machine learning for credit s…Predicting bank insolvencies using machine learning techniques (2020)Predicting bank insolvencies …Empirical Asset Pricing via Machine Learning (2020)Empirical Asset Pricing via M…Grabit: Gradient tree-boosted Tobit models for default prediction (2019)Grabit: Gradient tree-boosted…Ensemble learning with label proportions for bankruptcy prediction (2019)Ensemble learning with label …DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)DeepAR: Probabilistic forecas…Bayesian regularized artificial neural networks for the estimation of the probability of default (2019)Bayesian regularized artifici…Predicting mortgage default using convolutional neural networks (2018)Predicting mortgage default u…Empirical Asset Pricing via Machine Learning (2018)Empirical Asset Pricing via M…Deep learning models for bankruptcy prediction using textual disclosures (2018)Deep learning models for bank…The determinants of bank loan recovery rates (2011)The determinants of bank loan…Loss given default models incorporating macroeconomic variables for credit cards (2011)Loss given default models inc…Comparison of modeling methods for Loss Given Default (2011)Comparison of modeling method…Benchmarking regression algorithms for loss given default modeling (2011)Benchmarking regression algor…Forecasting bank loans loss-given-default (2010)Forecasting bank loans loss-g…Loss given default of high loan-to-value residential mortgages (2008)Loss given default of high lo…Emerging technologies in finance: challenges for a sustainable finance (2025)Emerging technologies in fina…PREDICTING STOCK MARKET MOVEMENTS USING NEURAL NETWORKS: A REVIEW AND APPLICATION STUDY (2024)PREDICTING STOCK MARKET MOVEM…Interpretable machine learning for creditor recovery rates (2024)Interpretable machine learnin…Benchmarking state-of-the-art classification algorithms for credit scoring (2003)Development and application of consumer credit scoring models using profit-based classification measures (2014)Deep learning for limit order books (2018)Two-stage consumer credit risk modelling using heterogeneous ensemble learning (2019)Measuring Corporate Bond Mortality and Performance (1989)Does industry-wide distress affect defaulted firms? 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(2022)Comparing Predictive Accuracy (1995)Credit default prediction from user-generated text in peer-to-peer lending using deep learning (2021)A two-stage hybrid credit risk prediction model based on XGBoost and graph-based deep neural network (2022)Big data, artificial intelligence and machine learning: A transformative symbiosis in favour of financial technology (2022)Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis (2021)Machine learning advances for time series forecasting (2021)Machine learning in the Chinese stock market (2021)
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References

  • 2019DeepAR: Probabilistic forecasting with autoregressive recurrent networks2,726 cited
  • 2020Empirical Asset Pricing via Machine Learning2,528 cited
  • 2018Deep learning models for bankruptcy prediction using textual disclosures480 cited
  • 2021Machine learning for credit scoring: Improving logistic regression with non-linear decision-tree effects438 cited
  • 2018Empirical Asset Pricing via Machine Learning384 cited
  • 2008Loss given default of high loan-to-value residential mortgages193 cited
  • 2011Benchmarking regression algorithms for loss given default modeling186 cited
  • 2018Predicting mortgage default using convolutional neural networks181 cited
  • 2010Forecasting bank loans loss-given-default171 cited
  • 2020Predicting bank insolvencies using machine learning techniques164 cited
  • 2011Loss given default models incorporating macroeconomic variables for credit cards161 cited
  • 2011Comparison of modeling methods for Loss Given Default151 cited
  • 2019Bayesian regularized artificial neural networks for the estimation of the probability of default130 cited
  • 2011The determinants of bank loan recovery rates109 cited
  • 2019Grabit: Gradient tree-boosted Tobit models for default prediction

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98 cited
  • 2019Ensemble learning with label proportions for bankruptcy prediction81 cited
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    • 2024Interpretable machine learning for creditor recovery rates23 cited