Fast gradient descent method for Mean‐CVaR optimization

Fast gradient descent method for Mean‐CVaR optimization

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Article ID: iaor20132690
Volume: 205
Issue: 1
Start Page Number: 203
End Page Number: 212
Publication Date: May 2013
Journal: Annals of Operations Research
Authors: ,
Keywords: portfolio selection
Abstract:

We propose an iterative gradient descent algorithm for solving scenario‐based Mean‐CVaR portfolio selection problem. The algorithm is fast and does not require any LP solver. It also has efficiency advantage over the LP approach for large scenario size.

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