Dr. Andrew Lim: Robust Portfolio Selection with Benchmarked Objectives

Event Details
  • Date/Time:
    • Thursday April 24, 2008
      11:00 am - 12:00 pm
  • Location: Executive Classroom
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    $0.00
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Contact
Jennifer Harris
H. Milton Stewart School of Industrial and Systems Engineering
Contact Jennifer Harris
Summaries

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.

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H. Milton Stewart School of Industrial and Systems Engineering (ISYE)

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Seminar/Lecture/Colloquium
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Dr. Andrew Lim
Status
  • Created By: Jennifer Harris
  • Workflow Status: Published
  • Created On: Oct 12, 2009 - 4:39pm
  • Last Updated: Oct 7, 2016 - 9:47pm