Dr. Andrew Lim: Robust Portfolio Selection with Benchmarked Objectives

Event Details
  • Date/Time:
    • Thursday April 24, 2008 - Friday April 25, 2008
      11:00 am - 11:59 am
  • Location: Executive Classroom
  • Phone:
  • URL:
  • Email:
  • Fee(s):
  • Extras:
Jennifer Harris
H. Milton Stewart School of Industrial and Systems Engineering
Contact Jennifer Harris

Summary Sentence: Dr. Andrew Lim: Robust Portfolio Selection with Benchmarked Objectives

Full Summary: Andrew Lim is a faculty candidate in ISyE in the area of QCF.

Title: Robust portfolio selection with benchmarked objectives

In this paper, we propose and analyze a new approach to finding robust portfolios for asset allocation problems. It differs from the usual worst case approach in that a (dynamic) portfolio is evaluated not only by its performance when there is an adversarial opponent (``nature"), but also by its performance relative to a fully informed benchmark investor who behaves optimally given complete knowledge of the model (i.e. nature's decision). This relative performance approach has several important properties: (i) optimal decisions are less pessimistic than portfolios obtained from the usual worst case approach, (ii) the dynamic problem reduces to a convex static optimization problem under reasonable choices of the benchmark portfolio for important classes of models including ambiguous jump-diffusions, and (iii) this static problem is dual to a Bayesian version of a single period asset allocation problem where the prior on the unknown parameters (for the dual problem) correspond to the Lagrange multipliers in this duality relationship.

Additional Information

In Campus Calendar

School of Industrial and Systems Engineering (ISYE)

Invited Audience
No audiences were selected.
Dr. Andrew Lim
  • Created By: Jennifer Harris
  • Workflow Status: Published
  • Created On: Oct 12, 2009 - 4:39pm
  • Last Updated: Oct 7, 2016 - 9:47pm