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Large Scale Portfolio Optimization with Piecewise Linear Transaction Costs

Potaptchik Marina (mpotaptc***at***math.uwaterloo.ca)
Levent Tuncel (ltuncel***at***math.uwaterloo.ca)
Henry Wolkowicz (hwolkowicz***at***uwaterloo.ca)

Abstract: We consider the fundamental problem of computing an optimal portfolio based on a quadratic mean-variance model of the objective function and a given polyhedral representation of the constraints. The main departure from the classical quadratic programming formulation is the inclusion in the objective function of piecewise linear, separable functions representing the transaction costs. We handle the nonsmoothness in the objective function by using spline approximations. The problem is then solved using a primal-dual interior-point method with a crossover to an active set method. Our numerical tests show that we can solve large scale problems efficiently and accurately.

Keywords: Portfolio Optimization, Quadratic Programming, Piecewise Differentiable Functions, Separable Problems

Category 1: Applications -- OR and Management Sciences (Finance and Economics )

Category 2: Convex and Nonsmooth Optimization (Nonsmooth Optimization )

Category 3: Nonlinear Optimization (Quadratic Programming )

Citation: CORR 2006-19, Dept. Combinatorics and Optimization, University of Waterloo, Sept, 2006

Download: [PDF]

Entry Submitted: 09/26/2006
Entry Accepted: 09/27/2006
Entry Last Modified: 09/26/2006

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