IDEAS home Printed from https://ideas.repec.org/p/vig/wpaper/0303.html
   My bibliography  Save this paper

Métodos No-Lineales De Predicción En El Mercado De Valores Tecnológicos En España. Una Verificación De La Hipótesis Débil De Eficiencia

Author

Listed:
  • Marcos Álvarez-Díaz
  • Lucy Amigo Dobaño

Abstract

En los últimos años, ante los hallazgos de estructuras deterministas no-lineales en series financieras, la econometría financiera aplicada ha adoptado toda una serie de sofisticadas y potentes técnicas no-lineales de predicción. En este trabajo empleamos el método de ocurrencias análogas, redes neuronales y algoritmos genéticos para predecir la evolución del índice representativo del mercado de valores tecnológicos español, el Ibex Nuevo Mercado. El objetivo perseguido se centra en verificar si existe una cierta capacidad predictiva en su dinámica y, de esta forma, refutar la hipótesis débil de eficiencia en el segmento de cotización caracterizado por su intenso crecimiento y volatilidad como es el tecnológico. Los resultados obtenidos sólo muestran ciertas posibilidades predictivas a 1 periodo empleando la red neuronal, y a 4 y 10 periodos utilizando el algoritmo genético.

Suggested Citation

  • Marcos Álvarez-Díaz & Lucy Amigo Dobaño, 2003. "Métodos No-Lineales De Predicción En El Mercado De Valores Tecnológicos En España. Una Verificación De La Hipótesis Débil De Eficiencia," Working Papers 0303, Universidade de Vigo, Departamento de Economía Aplicada.
    • Handle: RePEc:vig:wpaper:0303
    as

    Download full text from publisher

    File URL: https://webx06.webs8.uvigo.es/wp-content/uploads/2023/11/wp0303.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Tauchen, George & Zhang, Harold & Liu, Ming, 1996. "Volume, volatility, and leverage: A dynamic analysis," Journal of Econometrics, Elsevier, vol. 74(1), pages 177-208, September.
    3. 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 339-368, July.
    4. 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 380-382, July.
    5. Fernandez-Rodriguez, Fernando & Gonzalez-Martel, Christian & Sosvilla-Rivero, Simon, 2000. "On the profitability of technical trading rules based on artificial neural networks:: Evidence from the Madrid stock market," Economics Letters, Elsevier, vol. 69(1), pages 89-94, October.
    6. Diebold, Francis X. & Nason, James A., 1990. "Nonparametric exchange rate prediction?," Journal of International Economics, Elsevier, vol. 28(3-4), pages 315-332, May.
    7. 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.
    8. Allen, Franklin & Karjalainen, Risto, 1999. "Using genetic algorithms to find technical trading rules," Journal of Financial Economics, Elsevier, vol. 51(2), pages 245-271, February.
    9. Gencay, Ramazan, 1998. "Optimization of technical trading strategies and the profitability in security markets," Economics Letters, Elsevier, vol. 59(2), pages 249-254, May.
    10. 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 419-429, October.
    11. M. A. Kaboudan, 2000. "Genetic Programming Prediction of Stock Prices," Computational Economics, Springer;Society for Computational Economics, vol. 16(3), pages 207-236, December.
    12. John Barkoulas & Nickolaos Travlos, 1998. "Chaos in an emerging capital market? The case of the Athens Stock Exchange," Applied Financial Economics, Taylor & Francis Journals, vol. 8(3), pages 231-243.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marcos Álvarez-Díaz & Alberto Álvarez, 2002. "Predicción No-Lineal De Tipos De Cambio: Algoritmos Genéticos, Redes Neuronales Y Fusión De Datos," Working Papers 0205, Universidade de Vigo, Departamento de Economía Aplicada.
    2. Marcos Álvarez-Díaz & Alberto Álvarez, 2003. "Predicción No-Lineal De Tipos De Cambio: Algoritmos Genéticos, Redes Neuronales Y Fusión De Datos," Working Papers 0301, Universidade de Vigo, Departamento de Economía Aplicada.
    3. Marcos Alvarez Díaz & Lucy Amigo Dobano & Francisco Rodríguez de Prado, "undated". "Taxing on Housing: A Welfare Evaluation of the Spanish Personal Income Tax," Studies on the Spanish Economy 142, FEDEA.
    4. Maasoumi, Esfandiar & Racine, Jeff, 2002. "Entropy and predictability of stock market returns," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 291-312, March.
    5. Mougoué, Mbodja & Aggarwal, Raj, 2011. "Trading volume and exchange rate volatility: Evidence for the sequential arrival of information hypothesis," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2690-2703, October.
    6. Julián Andrada Félix & Fernando Fernández Rodríguez & María Dolores García Artiles, 2004. "Non-linear trading rules in the New York Stock Exchange," Documentos de trabajo conjunto ULL-ULPGC 2004-05, Facultad de Ciencias Económicas de la ULPGC.
    7. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    8. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, September.
    9. Olmedo,E. & Velasco, F. & Valderas, J.M., 2007. "Caracterización no lineal y predicción no paramétrica en el IBEX35/Nonlinear Characterization and Predictions of IBEX 35," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 25, pages 815-842, Diciembre.
    10. Fernandez-Rodriguez, Fernando & Sosvilla-Rivero, Simon & Andrada-Felix, Julian, 1999. "Exchange-rate forecasts with simultaneous nearest-neighbour methods: evidence from the EMS," International Journal of Forecasting, Elsevier, vol. 15(4), pages 383-392, October.
    11. Cheol‐Ho Park & Scott H. Irwin, 2007. "What Do We Know About The Profitability Of Technical Analysis?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 786-826, September.
    12. Kian-Ping Lim & Venus Khim-Sen Liew & Hock-Tsen Wong, 2003. "Weak-form Efficient Market Hypothesis, Behavioural Finance and Episodic Transient Dependencies: The Case of the Kuala Lumpur Stock Exchange," Finance 0312012, University Library of Munich, Germany.
    13. Rodríguez-Vargas, Adolfo, 2020. "Forecasting Costa Rican inflation with machine learning methods," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
    14. F. FernAndez-RodrIguez & S. Sosvilla-Rivero & J. Andrada-FElix, 2003. "Technical analysis in foreign exchange markets: evidence from the EMS," Applied Financial Economics, Taylor & Francis Journals, vol. 13(2), pages 113-122.
    15. Yang, Jian & Su, Xiaojing & Kolari, James W., 2008. "Do Euro exchange rates follow a martingale? Some out-of-sample evidence," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 729-740, May.
    16. Blake LeBaron, "undated". "Technical Trading Rules and Regime Shifts in Foreign Exchange," Working papers _007, University of Wisconsin - Madison.
    17. Ayan Bhattacharya & Rudra Sensarma, 2013. "Non-linearities in Emerging Financial Markets: Evidence from India," IIM Kozhikode Society & Management Review, , vol. 2(2), pages 165-175, July.
    18. Preminger, Arie & Franck, Raphael, 2007. "Forecasting exchange rates: A robust regression approach," International Journal of Forecasting, Elsevier, vol. 23(1), pages 71-84.
    19. Andreas Krause, 2009. "Evaluating the performance of adapting trading strategies with different memory lengths," Papers 0901.0447, arXiv.org.
    20. Bekiros, Stelios D., 2010. "Heterogeneous trading strategies with adaptive fuzzy Actor-Critic reinforcement learning: A behavioral approach," Journal of Economic Dynamics and Control, Elsevier, vol. 34(6), pages 1153-1170, June.

    More about this item

    Keywords

    Stock Market efficiency; time series non linear forecasting;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vig:wpaper:0303. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Departamento de Economía Aplicada (email available below). General contact details of provider: https://edirc.repec.org/data/deviges.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.