Risk Quantification and Allocation Methods for Practitioners.

Risk Quantification and Allocation Methods for Practitioners.

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Bibliographic Details
Superior document:Atlantis Studies in Computational Finance and Financial Engineering Series
:
Belles-Sampera, Jaume.
TeilnehmendeR:
Guillén, Montserrat.
Santolino, Miguel.
Place / Publishing House:Amsterdam : : Amsterdam University Press,, 2017.
©2017.
Year of Publication:2017
Edition:1st ed.
Language:English
Series:Atlantis Studies in Computational Finance and Financial Engineering Series
Online Access:
Physical Description:1 online resource (169 pages)
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Table of Contents:
  • Intro
  • Preface
  • Contents
  • List of Figures
  • List of Tables
  • Part I Risk Assessment
  • Preliminary concepts on quantitative risk measurement
  • Risk measurement - Theory
  • First definitions
  • Properties for risk measures
  • Risk measurement - Practice
  • `Liability side' versus `asset side' perspectives
  • Some misunderstandings to be avoided in practice
  • Exercises
  • Data on losses for risk evaluation
  • An example on three dimensional data
  • Basic graphical analysis of the loss severity distributions
  • Quantile estimation
  • Examples
  • A family of distortion risk measures
  • Overview on risk measures
  • Distortion risk measures
  • A new family of risk measures: GlueVaR
  • Linear combination of risk measures
  • Subadditivity
  • Concavity of the distortion function
  • Example of risk measurement with GlueVaR
  • Exercises
  • GlueVaR and other new risk measures
  • Analytical closed-form expressions of GlueVaR
  • Illustration: GlueVaR expression for Student t distribution
  • Analytical expressions for other frequently used distributions
  • The Cornish-Fisher approximation of GlueVaR
  • On the relationship between GlueVaR and Tail Distortion risk measures
  • On the relationship between GlueVaR and RVaR risk measures
  • Example
  • Exercises
  • Risk measure choice
  • Aggregate attitude towards risk
  • Local risk attitude
  • Application of risk assessment in a scenario involving catastrophic losses
  • Calibration of GlueVaR parameters
  • Data and Results
  • GlueVaR to reflect risk attitudes
  • Exercises
  • Part II Capital Allocation Problems
  • An overview on capital allocation problems
  • Main concepts and notation
  • Properties of capital allocation principles
  • Review of some principles
  • The gradient allocation principle
  • Other capital allocation principles based on partial contributions
  • The excess based allocation principle.
  • Further reading
  • Exercices
  • Capital allocation based on GlueVaR
  • A capital allocation framework
  • The Haircut capital allocation principle
  • Proportional risk capital allocation principles using GlueVaR
  • Stand-alone proportional allocation principles using GlueVaR
  • Proportional allocation principles based on partial contributions using GlueVaR
  • An example of risk capital allocation on claim costs
  • Exercices
  • Capital allocation principles as compositional data
  • The simplex and its vectorial and metric structure
  • From capital allocation principles to compositional data
  • Simplicial concepts applied to capital allocation
  • The inverse of a capital allocation
  • Ranking capital allocation principles
  • Averaging capital allocation principles
  • An illustration
  • Exercises
  • Appendix
  • Equivalent expression for the GlueVaR distortion function
  • Bijective relationship between heights and weights as parameters for GlueVaR risk measures
  • Relationship between GlueVaR and Tail Distortion risk measures
  • Bibliography
  • Biographies of the authors
  • Index.

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