Chapter

Managing the Model Risk with the Methods of the Probabilistic Decision Theory

Model Risk and Selection

  1. Vacslav S. Glukhov PhD

Published Online: 15 DEC 2012

DOI: 10.1002/9781118182635.efm0084

Encyclopedia of Financial Models

Encyclopedia of Financial Models

How to Cite

Glukhov, V. S. 2012. Managing the Model Risk with the Methods of the Probabilistic Decision Theory. Encyclopedia of Financial Models. .

Author Information

  1. Head of Quantitative Strategies and Data Analytics, Liquidnet Europe Ltd, London, United Kingdom

Publication History

  1. Published Online: 15 DEC 2012

Abstract

Practical applications of financial models require a proper assessment of the model risk due to uncertainty of the model parameters. Methods of the probabilistic decision theory achieve this objective. Probabilistic decision making starts from the Bayesian inference process, which supplies the posterior distribution of parameters. Bayesian incorporation of priors, or opinions, which influence posterior confidence intervals for the model parameters, is indispensable in real-world financial applications. Then, the utility function is used to evaluate practical implications of uncertainty of parameters by comparing the relative expected values of differing decisions. Probabilistic decision making involves computer simulations in all realistic situations. Still, a complete analytical treatment is possible in simple cases.

Keywords:

  • model risks;
  • Bayesian inference;
  • Probabilistic decision theory;
  • utility function;
  • ceteris paribus;
  • risk tolerance;
  • risk model;
  • hedging ratio;
  • probability of default