Quantitative finance collector
C++ Matlab VBA/Excel Java Mathematica R/Splus Net Code Site Other
May 28

Heuristic Optimization for Downside Risk Minimization

Posted by abiao at 16:24 | Code » Matlab | Comments(0) | Reads(7174)
Modern portfolio optimization started with Markowitz Efficient Frontier, Heuristic search and optimization is a new approach for solving complex problems that overcomes many shortcomings of traditional optimization techniques. Heuristic optimization techniques are general purpose methods that are very flexible and can be applied to many types of objective functions and constraints, especially where the objective function is non-convex and has many local minima. This is in particular the case when the risk is expressed as VaR, expected shortfall, Omega, maximum loss etc., and when the future returns of the individual assets are modelled as scenarios.

An interesting paper "A Data-Driven Optimization Heuristic for Downside Risk Minimization" demonstrates how to apply Heuristic optimization method under constraint of downside risk, code can be downloaded at http://comisef.eu/?q=resources_data_driven_opt, take a look if interested.


Add a comment
Emots
Enable HTML
Enable UBB
Enable Emots
Hidden
Remember
Nickname   Password   Optional
Site URI   Email   [Register]