The Factor-Portfolios Approach to Asset Management using Genetic Algorithms
AbstractWe 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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Bibliographic InfoPaper provided by Banco de la Republica de Colombia in its series Borradores de Economia with number 511.
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Active Management; Portfolio Optimization; Genetic Algorithms; Propensities. Classification JEL: G11; G14; G32.;
Other versions of this item:
- Alejandro Reveiz Herault, 2008. "The Factor-Portfolios Approach to Asset Management using Genetic Algorithms," BORRADORES DE ECONOMIA 004626, BANCO DE LA REPÚBLICA.
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- Alejandro Revéiz Herault & Sebastian Rojas, .
"The case for active management from the perspective of Complexity Theory,"
Borradores de Economia
495, Banco de la Republica de Colombia.
- 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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- 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.
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