Credit-Risk Modelling: Theoretical Foundations, Diagnostic Tools, Practical Examples, and Numerical Recipes in Python
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Credit-Risk Modelling: Theoretical Foundations, Diagnostic Tools, Practical Examples, and Numerical Recipes in Python By Bolder, David Jamieson Published by Springer Publication Date: 2018-11-12 Subject: Business & Economics Banks & Banking, Business & Economics Corporate Finance General, Business & Economics Finance Financial Engineering, Business & Economics Insurance Risk Assessment & Management, Business & Economics Statistics, Business & Economics Banks & Banking, Business & Economics Corporate Finance - General, Business & Economics Econometrics, Business & Economics Finance - Financial Engineering, Business & Economics Insurance - Risk Assessment & Management, Business & Economics Statistics, Mathematics Applied, Mathematics Applied, Banking, Corporate Finance, Management & Management Techniques, Probability & Statistics, Management And Management Techniques, Probability And Statistics, Wirtschaft Management, Management & Management Techniques, Corporate Finance, Banking, Probability & Statistics, Business & Economics Insurance Risk Assessment & Management, Business & Economics, Insurance, Risk Assessment & Management, Business & Economics Corporate Finance General, Corporate Finance, General, Mathematics Applied, Mathematics, Applied, Business & Economics Finance Financial Engineering, Finance, Financial Engineering, Business & Economics Banks & Banking, Banks & Banking, Business & Economics Statistics, Statistics, Management And Management Techniques, Probability And Statistics, Anf: Business And Management Subject Keywords: python code; monte carlo; financial engineering; model risk; risk modeling; default risk; binomial models; poisson models; asset correlation; black scholes; markov chains; t distribution; quantitative finance; banking Genre: Management & Management Techniques, Corporate Finance, Banking, Probability & Statistics, Business & Economics, Insurance, Risk Assessment & Management, Business & Economics, Corporate Finance, General, Mathematics, Applied, Business & Economics, Finance, Financial Engineering, Business & Economics, Banks & Banking, Business & Economics, Statistics, Management And Management Techniques, Corporate Finance, Banking, Probability And Statistics Target Audience: Professional and scholarly
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