10. Robust Portfolio Optimization

  1. Bernhard Pfaff

Published Online: 30 OCT 2012

DOI: 10.1002/9781118477144.ch10

Financial Risk Modelling and Portfolio Optimization with R

Financial Risk Modelling and Portfolio Optimization with R

How to Cite

Pfaff, B. (2012) Robust Portfolio Optimization, in Financial Risk Modelling and Portfolio Optimization with R, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9781118477144.ch10

Author Information

  1. Invesco Global Strategies, Germany

Publication History

  1. Published Online: 30 OCT 2012
  2. Published Print: 28 DEC 2012

ISBN Information

Print ISBN: 9780470978702

Online ISBN: 9781118477144

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Keywords:

  • Monte Carlo simulation;
  • robust optimization techniques;
  • robust portfolio optimization;
  • robust statistics

Summary

It would be desirable to have estimators available which lessen the impact of outliers and thus produce estimates that are representative of the bulk of sample data, and/or optimization techniques that incorporate estimations errors directly. The former can be achieved by utilizing robust statistics and the latter by employing robust optimization techniques. This chapter presents these two means from a theoretical point of view. It deals with the utilization of robust rather than classical estimators. The chapter briefly describes the robust approaches and techniques for optimizing portfolios. The packages that are partly or wholly dedicated to robust estimation methods in the context of multivariate data analysis are also presented. The chapter concludes with empirical applications in the form of a Monte Carlo simulation and back-test comparisons, where these robust portfolio optimizations are compared to portfolio solutions based on ordinary sample estimators.

Controlled Vocabulary Terms

Monte Carlo simulation