Case Study: Omega Portfolio Rebalancing
Back to main pageCase 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_gnsubject 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) ——————————————————————– Avg_g = Average Gai
Pm_pen = Partial Moment Penalty for Loss
Box constraints = constraints on individual decision variables ——————————————————————–
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) ——————————————————————– Avg_g = Average Gai
Pm_pen = Partial Moment Penalty for Loss
Box constraints = constraints on individual decision variables ——————————————————————–
| # 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 SUMMARYThis 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.