Visualizing and Optimizing Portfolio with Nonlinear Transaction Costs and Specific Constraints

Jimbo Henri,Bianca Chenwibianca Chenwi,Ngongo Isidore,Jawad Azimi

doi:10.14738/aivp.81.7530

Abstract

Visualizing and Optimizing Portfolio with Nonlinear Transaction Costs and Specific Constraints

Highlights

Linear and nonlinear transaction costs play a important role in portfolio management and represent source of debate among financial professionals both academic and practitioner
We propose an efficient computational approach called Genetic Algorithm (GA), which is part of evolutionary algorithm representing a powerful tool for obtaining optimal solution for complex optimization problems
To illustrate the features of the GA portfolio approach developed in this paper (GA-optimizer), we consider the historical data of return of eight assets in eight years

Summary

Introduction

Linear and nonlinear transaction costs play a important role in portfolio management and represent source of debate among financial professionals both academic and practitioner. In this paper we shall assume the transaction costs to be non-separable and, we can represent all cost with a unique function C. When the transaction cost of a particular asset is very large, it is not advantageous to change to holding of that asset, which will remain to its initial value, otherwise if the transaction cost is very small, it is worth making the trade and pay such a reasonable cost which could increase exponentially with large number of assets and volume of trade.

Objectives

Results

Discussion

Conclusion