Credit-Risk Modelling Theoretical Foundations, Diagnostic Tools, Practical Examples, and Numerical Recipes in Python /

Credit-Risk Modelling Theoretical Foundations, Diagnostic Tools, Practical Examples, and Numerical Recipes in Python /

Bibliographic Details
Main Author: Bolder, David Jamieson (Author)
Corporate Author: SpringerLink (Online service)
Summary:XXXV, 684 p. 130 illus. in color.
text
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
Edition:1st ed. 2018.
Subjects:
Financial risk management.
Business enterprises > Finance.
Social sciences > Mathematics.
Financial engineering.
Financial services industry.
Statistics .
Risk Management.
Corporate Finance.
Mathematics in Business, Economics and Finance.
Financial Engineering.
Financial Services.
Statistics in Business, Management, Economics, Finance, Insurance.
Online Access:https://doi.org/10.1007/978-3-319-94688-7
Format: Electronic eBook
Table of Contents:
  • Getting Started
  • Part I Modelling Frameworks
  • A Natural First Step.-Mixture or Actuarial Models
  • Threshold Models.-The Genesis of Credit-Risk Modelling
  • Part II Diagnostic Tools
  • A Regulatory Perspective
  • Risk Attribution
  • Monte Carlo Methods
  • Part III Parameter Estimation
  • Default Probabilities
  • Default and Asset Correlation.

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