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Predicting EU Energy Industry Excess Returns on EU Market Index via a Constrained Genetic Algorithm

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  • Massimiliano Kaucic

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    File URL: http://hdl.handle.net/10.1007/s10614-009-9176-4
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    Bibliographic Info

    Article provided by Society for Computational Economics in its journal Computational Economics.

    Volume (Year): 34 (2009)
    Issue (Month): 2 (September)
    Pages: 173-193

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    Handle: RePEc:kap:compec:v:34:y:2009:i:2:p:173-193

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    Web page: http://www.springerlink.com/link.asp?id=100248
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    Related research

    Keywords: Genetic algorithm; Penalty function method; Model selection; Excess return; Information criteria; C32; C52; C53; C61; C63;

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    1. Pesaran, M Hashem & Timmermann, Allan, 1995. " Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-28, September.
    2. Allan Timmermann & M. Hashem Pesaran, 1999. "A Recursive Modelling Approach to Predicting UK Stock Returns," FMG Discussion Papers dp322, Financial Markets Group.
    3. M. A. Kaboudan, 2000. "Genetic Programming Prediction of Stock Prices," Computational Economics, Society for Computational Economics, vol. 16(3), pages 207-236, December.
    4. Daniel Grenouilleau, 2006. "The Stacked Leading Indicators Dynamic Factor Model: A Sensitivity Analysis of Forecast Accuracy using Bootstrapping," European Economy - Economic Papers 249, Directorate General Economic and Monetary Affairs (DG ECFIN), European Commission.
    5. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-59, April.
    6. Kelvin Balcombe, 2005. "Model Selection Using Information Criteria and Genetic Algorithms," Computational Economics, Society for Computational Economics, vol. 25(3), pages 207-228, June.
    7. Ahumada, Hildegart A, 1985. "An Encompassing Test of Two Models of the Balance of Trade for Argentina," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 47(1), pages 51-70, February.
    8. K. J. Martijn Cremers, 2002. "Stock Return Predictability: A Bayesian Model Selection Perspective," Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1223-1249.
    9. David E. Rapach & Jack K. Strauss, 2008. "Forecasting US employment growth using forecast combining methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 75-93.
    10. Julia Campos & Neil R. Ericsson & David F. Hendry, 2005. "General-to-specific modeling: an overview and selected bibliography," International Finance Discussion Papers 838, Board of Governors of the Federal Reserve System (U.S.).
    11. Hoeting, Jennifer & Raftery, Adrian E. & Madigan, David, 1996. "A method for simultaneous variable selection and outlier identification in linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 22(3), pages 251-270, July.
    12. Bossaerts, Peter & Hillion, Pierre, 1999. "Implementing Statistical Criteria to Select Return Forecasting Models: What Do We Learn?," Review of Financial Studies, Society for Financial Studies, vol. 12(2), pages 405-28.
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    Cited by:
    1. Ivan Savin & Peter Winker, 2010. "Heuristic Optimization Methods for Dynamic Panel Data Model Selection. Application on the Russian Innovative Performance," Working Papers 027, COMISEF.

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