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Genetic Algorithm Optimisation for Finance and Investment

  • Robert Pereira

    ()

    (School of Economics, La Trobe University)

This paper provides an introduction to the use of genetic algo- rithms for financial optimisation. The aim is to give the reader a basic understanding of the computational aspects of these algorithms and how they can be applied to decision making in finance and investment. Genetic algorithms are especially suitable for complex problems char- actised by large solution spaces, multiple optima, non differentiability of the objective function, and other irregular features. The mechanics of constructing and using a genetic algorithm for optimisation are illustrated through a simple example.

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File URL: http://www.latrobe.edu.au/__data/assets/pdf_file/0006/130857/2000.02.pdf
File Function: First version, 2000.02.pdf
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Paper provided by School of Economics, La Trobe University in its series Working Papers with number 2000.02.

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Length: 29 pages
Date of creation: Feb 2000
Date of revision:
Handle: RePEc:trb:wpaper:2000.02
Contact details of provider: Web page: http://www.latrobe.edu.au/economics

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  1. Dorsey, Robert E & Mayer, Walter J, 1995. "Genetic Algorithms for Estimation Problems with Multiple Optima, Nondifferentiability, and Other Irregular Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 53-66, January.
  2. L. Ingber, 1989. "Very fast simulated re-annealing," Lester Ingber Papers 89vf, Lester Ingber.
  3. L. Ingber, 1996. "Statistical mechanics of nonlinear nonequilibrium financial markets: Applications to optimized trading," Lester Ingber Papers 96nf, Lester Ingber.
  4. Hinich, Melvin J & Patterson, Douglas M, 1985. "Evidence of Nonlinearity in Daily Stock Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(1), pages 69-77, January.
  5. Christopher J. Neely & Paul A. Weller, 2011. "Technical analysis in the foreign exchange market," Working Papers 2011-001, Federal Reserve Bank of St. Louis.
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