Quantitative Operational Risk Models

Quantitative Operational Risk Models

by Catalina Bolancé, Montserrat Guillén, Jim Gustafsson, Jens Perch Nielsen
Released February 2012
Publisher(s): CRC Press
ISBN: 9781439895931

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Book description

Presenting a nonparametric approach to modeling operational risk data, this book offers a practical perspective that combines statistical analysis and management orientations. It covers the statistical theory prerequisites and summarizes important contributions made in the past decade. The authors explain how to implement the new density estimation methods for analyzing the loss distribution in operational risk for banks and insurance companies. They also include SAS and R routines to implement all of the procedures discussed in the text.

Table of contents

  1. Front Cover
  2. Dedication
  3. About the authors
  4. Preface
  5. Contents (1/3)
  6. Contents (2/3)
  7. Contents (3/3)
  8. 1. Understanding Operational Risk (1/3)
  9. 1. Understanding Operational Risk (2/3)
  10. 1. Understanding Operational Risk (3/3)
  11. 2. Operational Risk Data and Parametric Models (1/4)
  12. 2. Operational Risk Data and Parametric Models (2/4)
  13. 2. Operational Risk Data and Parametric Models (3/4)
  14. 2. Operational Risk Data and Parametric Models (4/4)
  15. 3. Semiparametric Models for Operational Risk Severities (1/4)
  16. 3. Semiparametric Models for Operational Risk Severities (2/4)
  17. 3. Semiparametric Models for Operational Risk Severities (3/4)
  18. 3. Semiparametric Models for Operational Risk Severities (4/4)
  19. 4. Combining Operational Risk Data Sources (1/2)
  20. 4. Combining Operational Risk Data Sources (2/2)
  21. 5. Underreporting (1/4)
  22. 5. Underreporting (2/4)
  23. 5. Underreporting (3/4)
  24. 5. Underreporting (4/4)
  25. 6. Combining Underreported Internal and External Data for Operational Risk Measurement (1/5)
  26. 6. Combining Underreported Internal and External Data for Operational Risk Measurement (2/5)
  27. 6. Combining Underreported Internal and External Data for Operational Risk Measurement (3/5)
  28. 6. Combining Underreported Internal and External Data for Operational Risk Measurement (4/5)
  29. 6. Combining Underreported Internal and External Data for Operational Risk Measurement (5/5)
  30. 7. A Guided Practical Example (1/22)
  31. 7. A Guided Practical Example (2/22)
  32. 7. A Guided Practical Example (3/22)
  33. 7. A Guided Practical Example (4/22)
  34. 7. A Guided Practical Example (5/22)
  35. 7. A Guided Practical Example (6/22)
  36. 7. A Guided Practical Example (7/22)
  37. 7. A Guided Practical Example (8/22)
  38. 7. A Guided Practical Example (9/22)
  39. 7. A Guided Practical Example (10/22)
  40. 7. A Guided Practical Example (11/22)
  41. 7. A Guided Practical Example (12/22)
  42. 7. A Guided Practical Example (13/22)
  43. 7. A Guided Practical Example (14/22)
  44. 7. A Guided Practical Example (15/22)
  45. 7. A Guided Practical Example (16/22)
  46. 7. A Guided Practical Example (17/22)
  47. 7. A Guided Practical Example (18/22)
  48. 7. A Guided Practical Example (19/22)
  49. 7. A Guided Practical Example (20/22)
  50. 7. A Guided Practical Example (21/22)
  51. 7. A Guided Practical Example (22/22)
  52. Bibliography (1/2)
  53. Bibliography (2/2)

Product information

  • Title: Quantitative Operational Risk Models
  • Author(s): Catalina Bolancé, Montserrat Guillén, Jim Gustafsson, Jens Perch Nielsen
  • Release date: February 2012
  • Publisher(s): CRC Press
  • ISBN: 9781439895931