Case Study: Omega Portfolio Rebalancing

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Case study background and problem formulations

Instructions for optimization with PSG Run-File, PSG MATLAB Toolbox, PSG MATLAB Subroutines and PSG R.

PROBLEM 1: problem_omega
Maximize Avg_g
subject to
Pm_pen ≤ Const1 (downside loss constraint)
Linear = Const2 (budget constraint)
Const3 ≥ Linear ≤ Const4 (constraints on allocations to strategies)
Const5 ≥ X ≤ Const6 (constraints on allocations to individual managers)
Box constraints (box constraints for individual positions)
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Avg_g = Average Gain
Pm_pen = Partial Moment Penalty for Loss
Box constraints = constraints on individual decision variables
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# of Variables # of Scenarios Objective Value Solving Time, PC 3.14GHz (sec)
Dataset 10 641 0.12142 <0.01
Environments
Run-File Problem Statement Data Solution
Matlab Toolbox Data
Matlab Subroutines Matlab Code Data
R R Code Data

 

CASE STUDY SUMMARY
This case study demonstrates an Omega optimization setup for a portfolio optimization problem. A fund of funds blends the risk-return profiles of various hedge fund managers/strategies to meet investor requirements. The data for this case study are prepared with the Converter_Omega_Portfolio. To install this converter you should download installation file Converter_Omega_Portfolio_setup.zip in the Client Area () from the Download page by selecting the “Case Studies” downloading option.