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Machine learning loss given default for corporate debt · Study

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ArticleMachine learning loss given default for corporate debt

Luke M. Olson2021

Article2021

Machine learning loss given default for corporate debt

Luke M. Olson · Min Qi · Xinlei Shelly Zhao

18 citations·0/0 files stored·Journal of Empirical Finance

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Financial Distress and Bankruptcy Prediction Credit Risk and Financial Regulations Machine Learning and Data Classification

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References

2012On the use of cross-validation for time series predictor evaluation 2017A note on the validity of cross-validation for evaluating autoregressive time series prediction 2011Benchmarking regression algorithms for loss given default modeling 2010Forecasting bank loans loss-given-default 2011Comparison of modeling methods for Loss Given Default 2014Support vector regression for loss given default modelling 2013Loss given default for leasing: Parametric and nonparametric estimations 2017Fuzzy decision fusion approach for loss-given-default modeling

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2018Loss functions for Loss Given Default model comparisonarticle · 8 shared references 2019Predicting loss given default in leasing: A closer look at models and variable selectionarticle · 7 shared references 2021Predicting loss given default using post-default informationarticle · 7 shared references 2021Forecasting loss given default for peer-to-peer loans via heterogeneous stacking ensemble approacharticle · 6 shared references 2021Intertemporal defaulted bond recoveries prediction via machine learningarticle · 6 shared references 2017Loss given default adjusted workout processes for leasesarticle · 6 shared references

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Year2021

Typearticle

Published2021-09-06

VenueJournal of Empirical Finance

ISSN-L0927-5398

Languageen

Citations18

Files0 public / 0

ShelfFinancial Distress and Bankruptcy Prediction

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doi10.1016/j.jempfin.2021.08.009

openalex_workW3198477196

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