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 /

Bibliographische Detailangaben
1. Verfasser: Bolder, David Jamieson (VerfasserIn)
Körperschaft: SpringerLink (Online service)
Zusammenfassung:XXXV, 684 p. 130 illus. in color.
text
Sprache:Englisch
Veröffentlicht: Cham : Springer International Publishing : Imprint: Springer, 2018.
Ausgabe:1st ed. 2018.
Schlagworte:
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-Zugang:https://doi.org/10.1007/978-3-319-94688-7
Format: Elektronisch Buch
Inhaltsangabe:
  • 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.

Ähnliche Einträge