IDEAS home Printed from https://ideas.repec.org/a/taf/quantf/v15y2015i8p1365-1374.html
   My bibliography  Save this article

Long correlations and fractional difference analysis applied to the study of memory effects in high-frequency (tick) data

Author

Listed:
  • Maria Pia Beccar Varela
  • Francis Biney
  • Ionut Florescu

Abstract

This work is devoted to the study of long correlations, memory effects and other statistical properties of a sample of high-frequency (tick) data. The high-frequency data sample consists of high-frequency (minute) data for several stocks over a seven-day period which we know is relevant for market crush behaviour in the US market; 10-18 March 2008. The Hurst exponent estimation, the detrended fluctuation analysis and the fractional difference parameter are the tools used for this analysis. It also investigates the underlying volatility processes in high-frequency (tick) data using range of GARCH specifications. The GARCH variants considered include the basic GARCH, IGARCH, ARFIMA (0, ,0)-GARCH and FIGARCH models. In all the applications, the methodology provides insight into features of these series volatility.

Suggested Citation

  • Maria Pia Beccar Varela & Francis Biney & Ionut Florescu, 2015. "Long correlations and fractional difference analysis applied to the study of memory effects in high-frequency (tick) data," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1365-1374, August.
    • Handle: RePEc:taf:quantf:v:15:y:2015:i:8:p:1365-1374
    DOI: 10.1080/14697688.2015.1032547
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/14697688.2015.1032547
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/14697688.2015.1032547?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mantegna,Rosario N. & Stanley,H. Eugene, 2007. "Introduction to Econophysics," Cambridge Books, Cambridge University Press, number 9780521039871, October.
    2. Stanley, H.Eugene, 2003. "Statistical physics and economic fluctuations: do outliers exist?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 318(1), pages 279-292.
    3. Yanhui Liu & Pierre Cizeau & Martin Meyer & Chung-Kang Peng & H. Eugene Stanley, 1997. "Correlations in Economic Time Series," Papers cond-mat/9706021, arXiv.org.
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. 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.
    6. Mariani, Maria Cristina & Liu, Yang, 2006. "A new analysis of intermittence, scale invariance and characteristic scales applied to the behavior of financial indices near a crash," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 345-352.
    7. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    8. Kantelhardt, Jan W. & Berkovits, Richard & Havlin, Shlomo & Bunde, Armin, 1999. "Are the phases in the Anderson model long-range correlated?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 266(1), pages 461-464.
    9. Ivanova, K & Ausloos, M, 1999. "Application of the detrended fluctuation analysis (DFA) method for describing cloud breaking," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 274(1), pages 349-354.
    10. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    11. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    12. Robinson, P. M., 1991. "Testing for strong serial correlation and dynamic conditional heteroskedasticity in multiple regression," Journal of Econometrics, Elsevier, vol. 47(1), pages 67-84, January.
    13. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    14. Mariani, M.C. & Liu, Y., 2007. "A new analysis of the effects of the Asian crisis of 1997 on emergent markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 307-316.
    15. Ferraro, Marta & Furman, Nicolas & Liu, Yang & Mariani, Cristina & Rial, Diego, 2006. "Analysis of intermittence, scale invariance and characteristic scales in the behavior of major indices near a crash," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 359(C), pages 576-588.
    16. Liu, Yanhui & Cizeau, Pierre & Meyer, Martin & Peng, C.-K. & Eugene Stanley, H., 1997. "Correlations in economic time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 245(3), pages 437-440.
    17. Stanley, H.E & Amaral, L.A.N & Canning, D & Gopikrishnan, P & Lee, Y & Liu, Y, 1999. "Econophysics: Can physicists contribute to the science of economics?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 269(1), pages 156-169.
    18. Peng, C.-K. & Buldyrev, S.V. & Goldberger, A.L. & Havlin, S. & Mantegna, R.N. & Simons, M. & Stanley, H.E., 1995. "Statistical properties of DNA sequences," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 221(1), pages 180-192.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Un, Kuok Sin & Ausloos, Marcel, 2022. "Equity premium prediction: Taking into account the role of long, even asymmetric, swings in stock market behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).

    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. Mariani, M.C. & Florescu, I. & Beccar Varela, M.P. & Ncheuguim, E., 2010. "Study of memory effects in international market indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(8), pages 1653-1664.
    2. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2010. "Long memory volatility in Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(7), pages 1425-1433.
    3. Mariani, M.C. & Libbin, J.D. & Kumar Mani, V. & Beccar Varela, M.P. & Erickson, C.A. & Valles-Rosales, D.J., 2008. "Long correlations and Normalized Truncated Levy Models applied to the study of Indian Market Indices in comparison with other emerging markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(5), pages 1273-1282.
    4. Li, Gang & Li, Yong, 2015. "Forecasting copper futures volatility under model uncertainty," Resources Policy, Elsevier, vol. 46(P2), pages 167-176.
    5. Giraitis, Liudas & Leipus, Remigijus & Robinson, Peter M. & Surgailis, Donatas, 2004. "LARCH, leverage, and long memory," LSE Research Online Documents on Economics 294, London School of Economics and Political Science, LSE Library.
    6. Liudas Giraitis, 2004. "LARCH, Leverage, and Long Memory," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 177-210.
    7. Breidt, F. Jay & Crato, Nuno & de Lima, Pedro, 1998. "The detection and estimation of long memory in stochastic volatility," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 325-348.
    8. Wilfredo Palma & Mauricio Zevallos, 2004. "Analysis of the correlation structure of square time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(4), pages 529-550, July.
    9. Nick James & Max Menzies, 2023. "Collective dynamics, diversification and optimal portfolio construction for cryptocurrencies," Papers 2304.08902, arXiv.org, revised Jun 2023.
    10. Grajales Correa, Carlos Alexander & Pérez Ramírez, Fredy Ocaris & Venegas-Martínez, Francisco, 2014. "Análisis comparativo de modelos para estimar la distribución de la volatilidad de series financieras de rendimientos [A Comparative Analysis of Models for Estimating the Volatility Distribution of ," MPRA Paper 54845, University Library of Munich, Germany.
    11. Liudas Giraitis & Remigijus Leipus & Peter M Robinson & Donatas Surgailis, 2003. "LARCH, Leverage and Long Memory," STICERD - Econometrics Paper Series 460, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    12. Tomasz Wójtowicz & Henryk Gurgul, 2009. "Long memory of volatility measures in time series," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 19(1), pages 37-54.
    13. Christensen, Bent Jesper & Nielsen, Morten Ørregaard & Zhu, Jie, 2010. "Long memory in stock market volatility and the volatility-in-mean effect: The FIEGARCH-M Model," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 460-470, June.
    14. CHIA-LIN CHANG & MICHAEL McALEER & ROENGCHAI TANSUCHAT, 2012. "Modelling Long Memory Volatility In Agricultural Commodity Futures Returns," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 7(02), pages 1-27.
    15. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    16. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2013. "Econometric modeling of exchange rate volatility and jumps," Chapters, in: Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), Handbook of Research Methods and Applications in Empirical Finance, chapter 16, pages 373-427, Edward Elgar Publishing.
    17. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    18. Khim-Sen Liew & Kian-Ping Lim & Chee-Keong Choong, 2003. "On The Forecastability Of Asean-5 Stock Markets Returns Using Time Series Models," Finance 0307012, University Library of Munich, Germany.
    19. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    20. Francesco Audrino & Fabio Trojani, 2006. "Estimating and predicting multivariate volatility thresholds in global stock markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 345-369, April.

    More about this item

    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:taf:quantf:v:15:y:2015:i:8:p:1365-1374. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RQUF20 .

    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.