IDEAS home Printed from https://ideas.repec.org/a/ere/journl/vxxxviy2017i1p1-24.html
   My bibliography  Save this article

¿Existe memoria larga en mercados bursátiles, o depende del modelo, periodo o frecuencia? (Is there Long Memory in Stock Markets, or Does it Depend on the Model, Period or Frequency?)

Author

Listed:
  • Héctor F. Salazar-Núñez

    (Escuela Superior de Economía, Instituto Politécnico Nacional. Ciudad de México, México.)

  • Francisco Venegas-Martínez

    (Escuela Superior de Economía, Instituto Politécnico Nacional. Ciudad de México, México.)

  • Cuauhtémoc Calderón-Villareal

    (Departamento de Estudios Económicos, Colegio de la Frontera Norte, A.C.)

Abstract

El presente trabajo cuestiona si realmente existe memoria larga en los principales mercados accionarios del mundo y, en caso de que esta exista, a qué se debe: ¿al tipo de modelos econométricos empleados, al periodo o la frecuencia de los datos? Para ello, se realiza un análisis comparativo entre modelos ARFIMA y GARCH. Los únicos mercados que mostraron resultados consistentes de memoria larga, independientemente del método, periodo y frecuencia, fueron China y Corea del Sur. El primero tiene memoria larga y el segundo, corta.

Suggested Citation

  • Héctor F. Salazar-Núñez & Francisco Venegas-Martínez & Cuauhtémoc Calderón-Villareal, 2017. "¿Existe memoria larga en mercados bursátiles, o depende del modelo, periodo o frecuencia? (Is there Long Memory in Stock Markets, or Does it Depend on the Model, Period or Frequency?)," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(1), pages 1-24, May.
    • Handle: RePEc:ere:journl:v:xxxvi:y:2017:i:1:p:1-24
    as

    Download full text from publisher

    File URL: http://www.economia.uanl.mx/revistaensayos/xxxvi/1/1_Francisco_Venegas.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sowell, Fallaw, 1992. "Maximum likelihood estimation of stationary univariate fractionally integrated time series models," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 165-188.
    2. GabJin Oh & Cheol-Jun Um & Seunghwan Kim, 2006. "Statistical Properties of the Returns of Stock Prices of International Markets," Papers physics/0601126, arXiv.org.
    3. Jussi Tolvi, 2003. "Long memory in a small stock market," Economics Bulletin, AccessEcon, vol. 7(3), pages 1-13.
    4. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    5. Granger, Clive W. J. & Hyung, Namwon, 2004. "Occasional structural breaks and long memory with an application to the S&P 500 absolute stock returns," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 399-421, June.
    6. Emmanuel Anoruo & Luis Gil-Alana, 2011. "Mean reversion and long memory in African stock market prices," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 35(3), pages 296-308, July.
    7. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    8. Sadique, Shibley & Silvapulle, Param, 2001. "Long-Term Memory in Stock Market Returns: International Evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 6(1), pages 59-67, January.
    9. Machinea, José Luis, 2009. "La crisis financiera internacional: su naturaleza y los desafíos de política económica," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), April.
    10. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    11. Lee, Dongin & Schmidt, Peter, 1996. "On the power of the KPSS test of stationarity against fractionally-integrated alternatives," Journal of Econometrics, Elsevier, vol. 73(1), pages 285-302, July.
    12. Katsumi Shimotsu & Peter C. B. Phillips, 2002. "Pooled Log Periodogram Regression," Journal of Time Series Analysis, Wiley Blackwell, vol. 23(1), pages 57-93, January.
    13. Hiremath, Gourishankar S & Bandi, Kamaiah, 2011. "Testing Long Memory in Stock Returns of Emerging Markets: Some Further Evidence," MPRA Paper 48517, University Library of Munich, Germany.
    14. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    15. John T. Barkoulas & Christopher F. Baum & Nickolaos Travlos, 1996. "Long Memory in the Greek Stock Market," Boston College Working Papers in Economics 356., Boston College Department of Economics.
    16. Cheung, Yin-Wong & Lai, Kon S., 1995. "A search for long memory in international stock market returns," Journal of International Money and Finance, Elsevier, vol. 14(4), pages 597-615, August.
    17. repec:ebl:ecbull:v:7:y:2003:i:3:p:1-13 is not listed on IDEAS
    18. Olan Henry, 2002. "Long memory in stock returns: some international evidence," Applied Financial Economics, Taylor & Francis Journals, vol. 12(10), pages 725-729.
    19. C. W. J. Granger & Roselyne Joyeux, 1980. "An Introduction To Long‐Memory Time Series Models And Fractional Differencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 15-29, January.
    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. Luis A. Gil-Alana & Trilochan Tripathy, 2016. "Long Range Dependence in the Indian Stock Market: Evidence of Fractional Integration, Non-Linearities and Breaks," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(2), pages 199-215, December.
    2. Tripathy, Naliniprava, 2022. "Long memory and volatility persistence across BRICS stock markets," Research in International Business and Finance, Elsevier, vol. 63(C).
    3. Ngene, Geoffrey & Tah, Kenneth A. & Darrat, Ali F., 2017. "Long memory or structural breaks: Some evidence for African stock markets," Review of Financial Economics, Elsevier, vol. 34(C), pages 61-73.
    4. Caporale, Guglielmo Maria & Gil-Alana, Luis & Plastun, Alex, 2018. "Is market fear persistent? A long-memory analysis," Finance Research Letters, Elsevier, vol. 27(C), pages 140-147.
    5. Emmanuel Anoruo & Luis Gil-Alana, 2011. "Mean reversion and long memory in African stock market prices," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 35(3), pages 296-308, July.
    6. Luis A. Gil-Alana & Yun Cao, 2011. "Stock market prices in China. Efficiency, mean reversion, long memory volatility and other implicit dynamics," Faculty Working Papers 12/11, School of Economics and Business Administration, University of Navarra.
    7. Luis Gil-Alana, 2010. "Testing persistence in the context of conditional heteroscedasticity errors," Applied Financial Economics, Taylor & Francis Journals, vol. 20(22), pages 1709-1723.
    8. Ezzat, Hassan, 2013. "Long Memory Processes and Structural Breaks in Stock Returns and Volatility: Evidence from the Egyptian Exchange," MPRA Paper 51465, University Library of Munich, Germany.
    9. Geoffrey Ngene & Kenneth A. Tah & Ali F. Darrat, 2017. "Long memory or structural breaks: Some evidence for African stock markets," Review of Financial Economics, John Wiley & Sons, vol. 34(1), pages 61-73, September.
    10. Al-Shboul, Mohammad & Anwar, Sajid, 2016. "Fractional integration in daily stock market indices at Jordan's Amman stock exchange," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 16-37.
    11. Kasman, Adnan & Kasman, Saadet & Torun, Erdost, 2009. "Dual long memory property in returns and volatility: Evidence from the CEE countries' stock markets," Emerging Markets Review, Elsevier, vol. 10(2), pages 122-139, June.
    12. Kyaw, NyoNyo A. & Los, Cornelis A. & Zong, Sijing, 2006. "Persistence characteristics of Latin American financial markets," Journal of Multinational Financial Management, Elsevier, vol. 16(3), pages 269-290, July.
    13. Guglielmo Maria Caporale & Juncal Cuñado & Luis A. Gil-Alana, 2013. "Modelling long-run trends and cycles in financial time series data," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(3), pages 405-421, May.
    14. Rim Ammar Lamouchi, 2020. "Long Memory and Stock Market Efficiency: Case of Saudi Arabia," International Journal of Economics and Financial Issues, Econjournals, vol. 10(3), pages 29-34.
    15. Heni Boubaker & Giorgio Canarella & Rangan Gupta & Stephen M. Miller, 2023. "A Hybrid ARFIMA Wavelet Artificial Neural Network Model for DJIA Index Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1801-1843, December.
    16. Henryk Gurgul & Tomasz Wójtowicz, 2006. "Long-run properties of trading volume and volatility of equities listed in DJIA index," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 16(3-4), pages 29-56.
    17. Anju Bala & Kapil Gupta, 2020. "Examining The Long Memory In Stock Returns And Liquidity In India," Copernican Journal of Finance & Accounting, Uniwersytet Mikolaja Kopernika, vol. 9(3), pages 25-43.
    18. Guglielmo Maria Caporale & Luis A. Gil‐Alana & James C. Orlando, 2016. "Linkages Between the US and European Stock Markets: A Fractional Cointegration Approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 21(2), pages 143-153, April.
    19. Kuttu, Saint, 2018. "Modelling long memory in volatility in sub-Saharan African equity markets," Research in International Business and Finance, Elsevier, vol. 44(C), pages 176-185.
    20. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.

    More about this item

    Keywords

    Mercados bursátiles; Memoria larga; Métodos econométricos de series de tiempo;
    All these keywords.

    JEL classification:

    • N2 - Economic History - - Financial Markets and Institutions
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

    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:ere:journl:v:xxxvi:y:2017:i:1:p:1-24. 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: Dora María Vega Facio (email available below). General contact details of provider: https://edirc.repec.org/data/feualmx.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.