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Machine learning loss given default for corporate debt
11 references·0 citing·39 second hop
Machine learning loss given default for corporate debt (2021)Machine learning loss given default for c…Loss functions for Loss Given Default model comparison (2018)Loss functions for Loss Given…Fuzzy decision fusion approach for loss-given-default modeling (2017)Fuzzy decision fusion approac…A note on the validity of cross-validation for evaluating autoregressive time series prediction (2017)A note on the validity of cro…Support vector regression for loss given default modelling (2014)Support vector regression for…Forecasting Loss Given Default models: impact of account characteristics and the macroeconomic state (2014)Forecasting Loss Given Defaul…Loss given default for leasing: Parametric and nonparametric estimations (2013)Loss given default for leasin…Ensemble Predictions of Recovery Rates (2013)Ensemble Predictions of Recov…On the use of cross-validation for time series predictor evaluation (2012)On the use of cross-validatio…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…Unit Roots, Cointegration, and Structural Change (1999)To Explain or to Predict? (2010)Default probability estimation via pair copula constructions (2015)Current Issues in Economics and Finance (2017)Predicting loss given default in leasing: A closer look at models and variable selection (2019)Time Series Analysis, Forecasting and Control. (1971)Time Series Analysis: Forecasting and Control (1977)Another look at measures of forecast accuracy (2006)Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure (2016)Forecasting: theory and practice (2022)Bank loan losses-given-default: A case study (2005)Does industry-wide distress affect defaulted firms? Evidence from creditor recoveries (2007)Intertemporal defaulted bond recoveries prediction via machine learning (2021)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)On the Pricing of Corporate Debt: The Risk Structure of Interest Rates (1974)ON THE PRICING OF CORPORATE DEBT: THE RISK STRUCTURE OF INTEREST RATES* (1974)Merton, Robert C. (2010)A zero-adjusted gamma model for mortgage loan loss given default (2013)Enhancing two-stage modelling methodology for loss given default with support vector machines (2017)Measuring Corporate Bond Mortality and Performance (1989)Credit risk drivers: Evaluating the contribution of firm level information and of macroeconomic dynamics (2008)Applied Economic Forecasting (1967)Applied Economic Forecasting (1967)Macroeconomic variable selection for creditor recovery rates (2018)Opening the black box – Quantile neural networks for loss given default prediction (2021)The Link between Default and Recovery Rates: Theory, Empirical Evidence, and Implications* (2005)Macroeconomic Conditions and the Puzzles of Credit Spreads and Capital Structure (2010)Fuzzy Logic and Its Uses in Finance: A Systematic Review Exploring Its Potential to Deal with Banking Crises (2019)Forecasting loss given default for peer-to-peer loans via heterogeneous stacking ensemble approach (2021)Forecasting with Exponential Smoothing : The State Space Approach (2008)Ensemble approach based on bagging, boosting and stacking for short-term prediction in agribusiness time series (2019)Evaluating time series forecasting models: an empirical study on performance estimation methods (2020)M5 accuracy competition: Results, findings, and conclusions (2022)Modeling, forecasting and trading the EUR exchange rates with hybrid rolling genetic algorithms—Support vector regression forecast combinations (2015)An artificial intelligence system for predicting customer default in e-commerce (2018)Multi-view ensemble learning based on distance-to-model and adaptive clustering for imbalanced credit risk assessment in P2P lending (2020)
this work references cited by second hop

References

  • 2012On the use of cross-validation for time series predictor evaluation1,324 cited
  • 2017A note on the validity of cross-validation for evaluating autoregressive time series prediction770 cited
  • 2011Benchmarking regression algorithms for loss given default modeling186 cited
  • 2010Forecasting bank loans loss-given-default171 cited
  • 2011Comparison of modeling methods for Loss Given Default151 cited
  • 2014Support vector regression for loss given default modelling105 cited
  • 2013Loss given default for leasing: Parametric and nonparametric estimations55 cited
  • 2017Fuzzy decision fusion approach for loss-given-default modeling49 cited
  • 2014Forecasting Loss Given Default models: impact of account characteristics and the macroeconomic state47 cited
  • 2013Ensemble Predictions of Recovery Rates47 cited
  • 2018Loss functions for Loss Given Default model comparison37 cited

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