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Predicción No-Lineal De Tipos De Cambio: Algoritmos Genéticos, Redes Neuronales Y Fusión De Datos

  • Marcos Álvarez-Díaz
  • Alberto Álvarez
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    It is widely proved the existence of non-linear deterministic structures in the exchange rates dynamic. In this work we intend to exploit these non-linear structures using forecasting methods such as Genetic Algorithm and Neural Networks in the specific case of the Yen/$ and British Pound/$ exchange rates. We also employ a novel perspective, called Data Fusion, based on the combination of the obtained results by the non-linear methods to verify if it exists a synergic effect which permits a predictive improvement. The analysis is performed considering both the point prediction and the devaluation or appreciation anticipation

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    Paper provided by Universidade de Vigo, Departamento de Economía Aplicada in its series Working Papers with number 0205.

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    Length: 35 pages
    Date of creation: May 2002
    Date of revision:
    Handle: RePEc:vig:wpaper:0205
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    Web page: http://webx06.webs.uvigo.es/
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    1. Neely, Christopher & Weller, Paul & Dittmar, Rob, 1997. "Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(04), pages 405-426, December.
    2. Kuan, Chung-Ming & Liu, Tung, 1995. "Forecasting Exchange Rates Using Feedforward and Recurrent Neural Networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(4), pages 347-64, Oct.-Dec..
    3. Pesaran, M Hashem & Timmermann, Allan, 1992. "A Simple Nonparametric Test of Predictive Performance," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 561-65, October.
    4. Fernandez-Rodriguez, Fernando & Sosvilla-Rivero, Simon, 1998. "Testing nonlinear forecastability in time series: Theory and evidence from the EMS," Economics Letters, Elsevier, vol. 59(1), pages 49-63, April.
    5. Zhang, Gioqinang & Hu, Michael Y., 1998. "Neural network forecasting of the British Pound/US Dollar exchange rate," Omega, Elsevier, vol. 26(4), pages 495-506, August.
    6. Soofi, Abdol S. & Cao, Liangyue, 1999. "Nonlinear deterministic forecasting of daily Peseta-Dollar exchange rate," Economics Letters, Elsevier, vol. 62(2), pages 175-180, February.
    7. Colin Fyfe & John Paul Marney & Heather Tarbert, 1999. "Technical analysis versus market efficiency - a genetic programming approach," Applied Financial Economics, Taylor & Francis Journals, vol. 9(2), pages 183-191.
    8. Beenstock, Michael & Szpiro, George, 2002. "Specification search in nonlinear time-series models using the genetic algorithm," Journal of Economic Dynamics and Control, Elsevier, vol. 26(5), pages 811-835, May.
    9. Szpiro, George G, 1997. "A Search for Hidden Relationships: Data Mining with Genetic Algorithms," Computational Economics, Society for Computational Economics, vol. 10(3), pages 267-77, August.
    10. Hsieh, David A, 1989. "Testing for Nonlinear Dependence in Daily Foreign Exchange Rates," The Journal of Business, University of Chicago Press, vol. 62(3), pages 339-68, July.
    11. Francis X. Diebold & James M. Nason, 1989. "Nonparametric exchange rate prediction?," Finance and Economics Discussion Series 81, Board of Governors of the Federal Reserve System (U.S.).
    12. Barnett,William A. & Kirman,Alan P. & Salmon,Mark, 1997. "Nonlinear Dynamics and Economics," Cambridge Books, Cambridge University Press, number 9780521471411, May.
    13. Lubecke, Thomas H. & Nam, Kyung Doo & Markland, Robert E. & Kwok, Chuck C. Y., 1998. "Combining foreign exchange rate forecasts using neural networks," Global Finance Journal, Elsevier, vol. 9(1), pages 5-27.
    14. Qi, Min, 1999. "Nonlinear Predictability of Stock Returns Using Financial and Economic Variables," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(4), pages 419-29, October.
    15. Bajo-Rubio, Oscar & Fernandez-Rodriguez, Fernando & Sosvilla-Rivero, Simon, 1992. "Chaotic behaviour in exchange-rate series : First results for the Peseta--U.S. dollar case," Economics Letters, Elsevier, vol. 39(2), pages 207-211, June.
    16. Racine, Jeffrey, 2001. "On the Nonlinear Predictability of Stock Returns Using Financial and Economic Variables," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(3), pages 380-82, July.
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