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Credit Risk Analytics: The R Companion

Credit Risk Analytics: The R Companion
Credit Risk Analytics: The R Companion
Credit risk analytics in R will enable you to build credit risk models from start to finish. Accessing real credit data via the accompanying website www.creditriskanalytics.net, you will master a wide range of applications, including building your own PD, LGD and EAD models as well as mastering industry challenges such as reject inference, low default portfolio risk modeling, model validation and stress testing. This book has been written as a companion to Baesens, B., Roesch, D. and Scheule, H., 2016. Credit Risk Analytics: Measurement Techniques, Applications, and Examples in SAS
CreateSpace
Scheule, Harald
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Roesch, Daniel
89de5a2d-596e-45e4-a0b6-3b15943dc5b0
Baesens, Bart
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Scheule, Harald
db0d8b64-621e-4161-b198-e8681ddee63e
Roesch, Daniel
89de5a2d-596e-45e4-a0b6-3b15943dc5b0
Baesens, Bart
f7c6496b-aa7f-4026-8616-ca61d9e216f0

Scheule, Harald, Roesch, Daniel and Baesens, Bart (2017) Credit Risk Analytics: The R Companion , CreateSpace, 264pp.

Record type: Book

Abstract

Credit risk analytics in R will enable you to build credit risk models from start to finish. Accessing real credit data via the accompanying website www.creditriskanalytics.net, you will master a wide range of applications, including building your own PD, LGD and EAD models as well as mastering industry challenges such as reject inference, low default portfolio risk modeling, model validation and stress testing. This book has been written as a companion to Baesens, B., Roesch, D. and Scheule, H., 2016. Credit Risk Analytics: Measurement Techniques, Applications, and Examples in SAS

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Published date: 2017

Identifiers

Local EPrints ID: 425854
URI: http://eprints.soton.ac.uk/id/eprint/425854
PURE UUID: 7b0a6cab-c0e4-46c9-a8af-1a28bbe334dc
ORCID for Bart Baesens: ORCID iD orcid.org/0000-0002-5831-5668

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Date deposited: 05 Nov 2018 17:30
Last modified: 12 Dec 2021 03:27

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Contributors

Author: Harald Scheule
Author: Daniel Roesch
Author: Bart Baesens ORCID iD

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