IDEAS home Printed from https://ideas.repec.org/a/bla/jtsera/v42y2021i2p161-185.html
   My bibliography  Save this article

Long range dependence for stable random processes

Author

Listed:
  • Vitalii Makogin
  • Marco Oesting
  • Albert Rapp
  • Evgeny Spodarev

Abstract

We investigate long and short memory in α‐stable moving averages and max‐stable processes with α‐Fréchet marginal distributions. As these processes are heavy‐tailed, we rely on the notion of long range dependence based on the covariance of indicators of excursion sets. Sufficient conditions for the long and short range dependence of α‐stable moving averages are proven in terms of integrability of the corresponding kernel functions. For max‐stable processes, the extremal coefficient function is used to state a necessary and sufficient condition for long range dependence.

Suggested Citation

  • Vitalii Makogin & Marco Oesting & Albert Rapp & Evgeny Spodarev, 2021. "Long range dependence for stable random processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(2), pages 161-185, March.
  • Handle: RePEc:bla:jtsera:v:42:y:2021:i:2:p:161-185
    DOI: 10.1111/jtsa.12560
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/jtsa.12560
    Download Restriction: no

    File URL: https://libkey.io/10.1111/jtsa.12560?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
    ---><---

    References listed on IDEAS

    as
    1. Damarackas, Julius & Paulauskas, Vygantas, 2017. "Spectral covariance and limit theorems for random fields with infinite variance," Journal of Multivariate Analysis, Elsevier, vol. 153(C), pages 156-175.
    2. Jan Beran & Bikramjit Das & Dieter Schell, 2012. "On robust tail index estimation for linear long‐memory processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(3), pages 406-423, May.
    3. Epaminondas Panas, 2001. "Estimating fractal dimension using stable distributions and exploring long memory through ARFIMA models in Athens Stock Exchange," Applied Financial Economics, Taylor & Francis Journals, vol. 11(4), pages 395-402.
    4. Beran, Jan & Schell, Dieter, 2012. "On robust tail index estimation," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3430-3443.
    5. Paulauskas, V. J., 1976. "Some remarks on multivariate stable distributions," Journal of Multivariate Analysis, Elsevier, vol. 6(3), pages 356-368, September.
    6. Hira L. Koul & Donatas Surgailis, 2018. "Asymptotic Distributions of Some Scale Estimators in Nonlinear Models With Long Memory Errors Having Infinite Variance," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(3), pages 273-298, May.
    7. Martin Schlather, 2003. "A dependence measure for multivariate and spatial extreme values: Properties and inference," Biometrika, Biometrika Trust, vol. 90(1), pages 139-156, March.
    8. Kokoszka, P. & Mikosch, T., 1997. "The integrated periodogram for long-memory processes with finite or infinite variance," Stochastic Processes and their Applications, Elsevier, vol. 66(1), pages 55-78, February.
    9. 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.
    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. Igor Fedotenkov, 2020. "A Review of More than One Hundred Pareto-Tail Index Estimators," Statistica, Department of Statistics, University of Bologna, vol. 80(3), pages 245-299.
    2. Chengping Gong & Chengxiu Ling, 2018. "Robust Estimations for the Tail Index of Weibull-Type Distribution," Risks, MDPI, vol. 6(4), pages 1-15, October.
    3. Yuan, Ying & Zhuang, Xin-tian & Jin, Xiu & Huang, Wei-qiang, 2014. "Stable distribution and long-range correlation of Brent crude oil market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 173-179.
    4. Bariviera, Aurelio F. & Basgall, María José & Hasperué, Waldo & Naiouf, Marcelo, 2017. "Some stylized facts of the Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 82-90.
    5. Jussi Tolvi, 2003. "Long memory in a small stock market," Economics Bulletin, AccessEcon, vol. 7(3), pages 1-13.
    6. Karling, Maicon J. & Lopes, Sílvia R.C. & de Souza, Roberto M., 2023. "Multivariate α-stable distributions: VAR(1) processes, measures of dependence and their estimations," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
    7. Fung, Tsz Chai, 2022. "Maximum weighted likelihood estimator for robust heavy-tail modelling of finite mixture models," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 180-198.
    8. Cristofaro, Lorenzo & Gil-Alana, Luis A. & Chen, Zhongfei & Wanke, Peter, 2021. "Modelling stock market data in China: Crisis and Coronavirus," Finance Research Letters, Elsevier, vol. 41(C).
    9. Yalama, Abdullah & Celik, Sibel, 2013. "Real or spurious long memory characteristics of volatility: Empirical evidence from an emerging market," Economic Modelling, Elsevier, vol. 30(C), pages 67-72.
    10. repec:ebl:ecbull:v:7:y:2003:i:3:p:1-13 is not listed on IDEAS
    11. Lisana B. Martinez & M. Belén Guercio & Aurelio Fernandez Bariviera & Antonio Terceño, 2018. "The impact of the financial crisis on the long-range memory of European corporate bond and stock markets," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 45(1), pages 1-15, February.
    12. 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.
    13. Fátima Brilhante, M. & Ivette Gomes, M. & Pestana, Dinis, 2013. "A simple generalisation of the Hill estimator," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 518-535.
    14. Can, S.U. & Mikosch, T. & Samorodnitsky, G., 2010. "Weak Convergence of the function-indexed integrated periodogram for infinite variance processes," Other publications TiSEM 3be90f1b-2f53-4987-b46e-c, Tilburg University, School of Economics and Management.
    15. Erhard Reschenhofer & Manveer K. Mangat, 2021. "Fast computation and practical use of amplitudes at non-Fourier frequencies," Computational Statistics, Springer, vol. 36(3), pages 1755-1773, September.
    16. Barkoulas, John T. & Baum, Christopher F., 1996. "Long-term dependence in stock returns," Economics Letters, Elsevier, vol. 53(3), pages 253-259, December.
    17. Geoffrey Ngene & Ann Nduati Mungai & Allen K. Lynch, 2018. "Long-Term Dependency Structure and Structural Breaks: Evidence from the U.S. Sector Returns and Volatility," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 21(02), pages 1-38, June.
    18. Gil-Alana, L.A., 2006. "Fractional integration in daily stock market indexes," Review of Financial Economics, Elsevier, vol. 15(1), pages 28-48.
    19. Christos Christodoulou-Volos & Fotios Siokis, 2006. "Long range dependence in stock market returns," Applied Financial Economics, Taylor & Francis Journals, vol. 16(18), pages 1331-1338.
    20. Ørregaard Nielsen, Morten, 2004. "Local empirical spectral measure of multivariate processes with long range dependence," Stochastic Processes and their Applications, Elsevier, vol. 109(1), pages 145-166, January.
    21. Kausik Chaudhuri, 1997. "Stock returns in emerging markets: a common trend analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 4(2), pages 105-108.

    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:bla:jtsera:v:42:y:2021:i:2:p:161-185. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782 .

    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.