IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2309.12034.html
   My bibliography  Save this paper

A detection analysis for temporal memory patterns at different time-scales

Author

Listed:
  • Fabio Vanni
  • David Lambert

Abstract

This paper introduces a novel methodology that utilizes latency to unveil time-series dependence patterns. A customized statistical test detects memory dependence in event sequences by analyzing their inter-event time distributions. Synthetic experiments based on the renewal-aging property assess the impact of observer latency on the renewal property. Our test uncovers memory patterns across diverse time scales, emphasizing the event sequence's probability structure beyond correlations. The time series analysis produces a statistical test and graphical plots which helps to detect dependence patterns among events at different time-scales if any. Furthermore, the test evaluates the renewal assumption through aging experiments, offering valuable applications in time-series analysis within economics.

Suggested Citation

  • Fabio Vanni & David Lambert, 2023. "A detection analysis for temporal memory patterns at different time-scales," Papers 2309.12034, arXiv.org.
    • Handle: RePEc:arx:papers:2309.12034
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2309.12034
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alan Washburn, 1992. "Present Values with Renewals," Management Science, INFORMS, vol. 38(6), pages 846-850, June.
    2. Stindl, Tom & Chen, Feng, 2018. "Likelihood based inference for the multivariate renewal Hawkes process," Computational Statistics & Data Analysis, Elsevier, vol. 123(C), pages 131-145.
    3. Amitrajeet A. Batabyal, 2008. "Introduction To Dynamic And Stochastic Approaches To The Environment And Economic Development," World Scientific Book Chapters, in: Dynamic And Stochastic Approaches To The Environment And Economic Development, chapter 1, pages 1-38, World Scientific Publishing Co. Pte. Ltd..
    4. Mantegna,Rosario N. & Stanley,H. Eugene, 2007. "Introduction to Econophysics," Cambridge Books, Cambridge University Press, number 9780521039871.
    5. Jensen, Mark J. & Liu, Ming, 2006. "Do long swings in the business cycle lead to strong persistence in output?," Journal of Monetary Economics, Elsevier, vol. 53(3), pages 597-611, April.
    6. Giacomo Bormetti & Lucio Maria Calcagnile & Michele Treccani & Fulvio Corsi & Stefano Marmi & Fabrizio Lillo, 2015. "Modelling systemic price cojumps with Hawkes factor models," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1137-1156, July.
    7. Liu, Ming, 2000. "Modeling long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 99(1), pages 139-171, November.
    8. Leipus, Remigijus & Paulauskas, Vygantas & Surgailis, Donatas, 2005. "Renewal regime switching and stable limit laws," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 299-327.
    9. Ohanissian, Arek & Russell, Jeffrey R. & Tsay, Ruey S., 2008. "True or Spurious Long Memory? A New Test," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 161-175, April.
    10. Batabyal, Amitrajeet A. & Yoo, Seung Jick, 1994. "Renewal theory and natural resource regulatory policy under uncertainty," Economics Letters, Elsevier, vol. 46(3), pages 237-241, November.
    11. Khaldoun Khashanah & Jing Chen & Alan Hawkes, 2018. "A slightly depressing jump model: intraday volatility pattern simulation," Quantitative Finance, Taylor & Francis Journals, vol. 18(2), pages 213-224, February.
    12. Chipman, John S, 1977. "A Renewal Model of Economic Growth: The Continuous Case," Econometrica, Econometric Society, vol. 45(2), pages 295-316, March.
    13. Emmanuel Bacry & Iacopo Mastromatteo & Jean-Franc{c}ois Muzy, 2015. "Hawkes processes in finance," Papers 1502.04592, arXiv.org, revised May 2015.
    14. Amitrajeet A Batabyal, 2008. "Dynamic and Stochastic Approaches to the Environment and Economic Development," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6617, August.
    15. Alan G. Hawkes, 2018. "Hawkes processes and their applications to finance: a review," Quantitative Finance, Taylor & Francis Journals, vol. 18(2), pages 193-198, February.
    16. M. Schneider & F. Lillo & L. Pelizzon, 2018. "Modelling illiquidity spillovers with Hawkes processes: an application to the sovereign bond market," Quantitative Finance, Taylor & Francis Journals, vol. 18(2), pages 283-293, February.
    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. Chatzikonstanti, Vasiliki & Venetis, Ioannis A., 2015. "Long memory in log-range series: Do structural breaks matter?," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 104-113.
    2. Hui Qu & Tianyang Wang & Peng Shangguan & Mengying He, 2024. "Revisiting the puzzle of jumps in volatility forecasting: The new insights of high‐frequency jump intensity," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 218-251, February.
    3. Hai-Chuan Xu & Wei-Xing Zhou, 2020. "Modeling aggressive market order placements with Hawkes factor models," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-12, January.
    4. Kyungsub Lee, 2022. "Application of Hawkes volatility in the observation of filtered high-frequency price process in tick structures," Papers 2207.05939, arXiv.org, revised Sep 2024.
    5. Mercuri, Lorenzo & Perchiazzo, Andrea & Rroji, Edit, 2024. "A Hawkes model with CARMA(p,q) intensity," Insurance: Mathematics and Economics, Elsevier, vol. 116(C), pages 1-26.
    6. Kyungsub Lee, 2024. "Discrete Hawkes process with flexible residual distribution and filtered historical simulation," Papers 2401.13890, arXiv.org.
    7. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    8. Leipus, Remigijus & Paulauskas, Vygantas & Surgailis, Donatas, 2005. "Renewal regime switching and stable limit laws," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 299-327.
    9. Nikolaus Graf von Luckner & Rüdiger Kiesel, 2021. "Modeling Market Order Arrivals on the German Intraday Electricity Market with the Hawkes Process," JRFM, MDPI, vol. 14(4), pages 1-31, April.
    10. Abderrazak Ben Maatoug & Rim Lamouchi & Russell Davidson & Ibrahim Fatnassi, 2018. "Modelling Foreign Exchange Realized Volatility Using High Frequency Data: Long Memory versus Structural Breaks," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 10(1), pages 1-25, March.
    11. Antoine Fosset & Jean-Philippe Bouchaud & Michael Benzaquen, 2020. "Endogenous Liquidity Crises," Post-Print hal-02567495, HAL.
    12. Leschinski, Christian & Sibbertsen, Philipp, 2018. "The Periodogram of Spurious Long-Memory Processes," Hannover Economic Papers (HEP) dp-632, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    13. Antoine Fosset & Jean-Philippe Bouchaud & Michael Benzaquen, 2020. "Non-parametric Estimation of Quadratic Hawkes Processes for Order Book Events," Papers 2005.05730, arXiv.org.
    14. Bufalo, Michele & Ceci, Claudia & Orlando, Giuseppe, 2024. "Addressing the financial impact of natural disasters in the era of climate change," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).
    15. Simon Clinet & William T. M. Dunsmuir & Gareth W. Peters & Kylie-Anne Richards, 2021. "Asymptotic distribution of the score test for detecting marks in hawkes processes," Statistical Inference for Stochastic Processes, Springer, vol. 24(3), pages 635-668, October.
    16. Hainaut, Donatien & Goutte, Stephane, 2018. "A switching microstructure model for stock prices," LIDAM Discussion Papers ISBA 2018014, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    17. Hainaut, Donatien, 2016. "A bivariate Hawkes process for interest rate modeling," Economic Modelling, Elsevier, vol. 57(C), pages 180-196.
    18. Kramer, Anke & Kiesel, Rüdiger, 2021. "Exogenous factors for order arrivals on the intraday electricity market," Energy Economics, Elsevier, vol. 97(C).
    19. Cao, Jingyi & Landriault, David & Li, Bin, 2020. "Optimal reinsurance-investment strategy for a dynamic contagion claim model," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 206-215.
    20. Kyungsub Lee, 2023. "Multi-kernel property in high-frequency price dynamics under Hawkes model," Papers 2302.11822, arXiv.org.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:2309.12034. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.