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. John Wiley & Sons.
Credit Risk Analytics: The R Companion
$70.31
This book teaches advanced data analytics and credit risk modeling suitable for postsecondary studies in economics and finance.
Additional information
Weight | 0.458 lbs |
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Dimensions | 19.1 × 1.5 × 23.5 in |
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