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The Factor-Portfolios Approach to Asset Management using Genetic Algorithms

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  • Alejandro Reveiz Herault

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Abstract

We present an investment process that: (i) decomposes securities into risk factors; (ii) allows for the construction of portfolios of assets that would selectively expose the manager to desired risk factors; (iii) perform a risk allocation between these portfolios, allowing for tracking error restrictions in the optimization process and (iv) give the flexibility to manage dinamically the transfer coeffficient (TC). The contribution of this article is to present an investment process that allows the asset manager to limit risk exposure to macro-factors - including expectations on correlation dynamics - whilst allowing for selective exposure to risk factors using mimicking portfolios that emulate the behaviour of given specific. An Artificial Intelligence (AI) optimisation technique is used for risk-budget allocation to factor-portfolios.

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Paper provided by Banco de la Republica de Colombia in its series Borradores de Economia with number 511.

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Handle: RePEc:bdr:borrec:511

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Keywords: Active Management; Portfolio Optimization; Genetic Algorithms; Propensities. Classification JEL: G11; G14; G32.;

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  1. Charles S. Morris & Robert Neal & Douglas Rolph, 1998. "Credit spreads and interest rates : a cointegration approach," Research Working Paper 98-08, Federal Reserve Bank of Kansas City.
  2. Vineer Bhansali & Mark B. Wise, 2001. "Forecasting Portfolio Risk in Normal and Stressed Markets," Papers nlin/0108022, arXiv.org, revised Sep 2001.
  3. Aeljandro Reveiz Herault & Sebastian Rojas, 2008. "The case for active management from the perspective of Complexity Theory," BORRADORES DE ECONOMIA 004566, BANCO DE LA REPÚBLICA.
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