IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v298y2001i3p521-529.html
   My bibliography  Save this article

Heterogeneous volatility cascade in financial markets

Author

Listed:
  • Zumbach, Gilles
  • Lynch, Paul

Abstract

Using high frequency data, we have studied empirically the change of volatility, also called volatility derivative, for various time horizons. In particular, the correlation between the volatility derivative and the volatility realized in the next time period is a measure of the response function of the market participants. This correlation shows explicitly the heterogeneous structure of the market according to the characteristic time horizons of the different agents. It reveals a volatility cascade from long to short time horizons, with a structure different from the one observed in turbulence. Moreover, we have developed a new ARCH-type model which incorporates the different groups of agents, with their characteristic memory. This model reproduces well the empirical response function, and allows us to quantify the importance of each group.

Suggested Citation

  • Zumbach, Gilles & Lynch, Paul, 2001. "Heterogeneous volatility cascade in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 298(3), pages 521-529.
  • Handle: RePEc:eee:phsmap:v:298:y:2001:i:3:p:521-529
    DOI: 10.1016/S0378-4371(01)00249-7
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437101002497
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/S0378-4371(01)00249-7?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. Lui, Yu-Hon & Mole, David, 1998. "The use of fundamental and technical analyses by foreign exchange dealers: Hong Kong evidence," Journal of International Money and Finance, Elsevier, vol. 17(3), pages 535-545, June.
    2. Muller, Ulrich A. & Dacorogna, Michel M. & Dave, Rakhal D. & Olsen, Richard B. & Pictet, Olivier V. & von Weizsacker, Jacob E., 1997. "Volatilities of different time resolutions -- Analyzing the dynamics of market components," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 213-239, June.
    3. Dacorogna, Michael M. & Muller, Ulrich A. & Nagler, Robert J. & Olsen, Richard B. & Pictet, Olivier V., 1993. "A geographical model for the daily and weekly seasonal volatility in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 12(4), pages 413-438, August.
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. 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.
    6. Jensen, Michael C., 1978. "Some anomalous evidence regarding market efficiency," Journal of Financial Economics, Elsevier, vol. 6(2-3), pages 95-101.
    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. Damien Challet & Vincent Ragel, 2023. "Recurrent Neural Networks with more flexible memory: better predictions than rough volatility," Working Papers hal-04165354, HAL.
    2. Léo Parent, 2022. "The EWMA Heston model," Post-Print hal-04431111, HAL.
    3. David Mcmillan & Alan Speight, 2008. "Long-memory in high-frequency exchange rate volatility under temporal aggregation," Quantitative Finance, Taylor & Francis Journals, vol. 8(3), pages 251-261.
    4. Daniel Fricke & Thomas Lux, 2015. "The effects of a financial transaction tax in an artificial financial market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(1), pages 119-150, April.
    5. Gilles Zumbach, 2010. "Volatility conditional on price trends," Quantitative Finance, Taylor & Francis Journals, vol. 10(4), pages 431-442.
    6. Gilles Zumbach, 2009. "Volatility forecasts and the at-the-money implied volatility: a multi-components ARCH approach and its relation with market models," Papers 0901.2275, arXiv.org.
    7. Ramazan Gencay & Nikola Gradojevic & Faruk Selcuk & Brandon Whitcher, 2010. "Asymmetry of information flow between volatilities across time scales," Quantitative Finance, Taylor & Francis Journals, vol. 10(8), pages 895-915.
    8. Leunga Njike, Charles Guy & Hainaut, Donatien, 2024. "Affine Heston model style with self-exciting jumps and long memory," LIDAM Discussion Papers ISBA 2024001, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    9. Julien Idier, 2011. "Long-term vs. short-term comovements in stock markets: the use of Markov-switching multifractal models," The European Journal of Finance, Taylor & Francis Journals, vol. 17(1), pages 27-48.
    10. Gilles Zumbach, 2011. "Characterizing heteroskedasticity," Quantitative Finance, Taylor & Francis Journals, vol. 11(9), pages 1357-1369, October.
    11. Omar El Euch & Jim Gatheral & Radov{s} Radoiv{c}i'c & Mathieu Rosenbaum, 2018. "The Zumbach effect under rough Heston," Papers 1809.02098, arXiv.org.
    12. Blanc, Pierre & Chicheportiche, Rémy & Bouchaud, Jean-Philippe, 2014. "The fine structure of volatility feedback II: Overnight and intra-day effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 58-75.
    13. Marcus Cordi & Serge Kassibrakis & Damien Challet, 2018. "The market nanostructure origin of asset price time reversal asymmetry," Working Papers hal-01966419, HAL.
    14. Milan Bašta, 2014. "Simulating Bivariate Stationary Processes with Scale-Specific Characteristics," Acta Oeconomica Pragensia, Prague University of Economics and Business, vol. 2014(1), pages 3-26.
    15. Clark, Andrew, 2004. "Evidence of log-periodicity in corporate bond spreads," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(3), pages 585-595.
    16. Nicolas Boitout & Loredana Ureche-Rangau, 2004. "Towards A Multifractal Paradigm Of Stochastic Volatility?," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 7(07), pages 823-851.
    17. Marcus Cordi & Damien Challet & Serge Kassibrakis, 2021. "The market nanostructure origin of asset price time reversal asymmetry," Quantitative Finance, Taylor & Francis Journals, vol. 21(2), pages 295-304, February.
    18. Jean-Philippe Bouchaud, 2024. "The Self-Organized Criticality Paradigm in Economics & Finance," Papers 2407.10284, arXiv.org, revised Sep 2024.
    19. Charles Guy Njike Leunga & Donatien Hainaut, 2024. "Affine Heston model style with self-exciting jumps and long memory," Annals of Finance, Springer, vol. 20(1), pages 1-43, March.
    20. Gilles Zumbach, 2007. "Time reversal invariance in finance," Papers 0708.4022, arXiv.org.
    21. Wang, Xunxiao & Wu, Chongfeng & Xu, Weidong, 2015. "Volatility forecasting: The role of lunch-break returns, overnight returns, trading volume and leverage effects," International Journal of Forecasting, Elsevier, vol. 31(3), pages 609-619.

    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. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    2. Park, Cheol-Ho & Irwin, Scott H., 2004. "The Profitability Of Technical Trading Rules In Us Futures Markets: A Data Snooping Free Test," 2004 Conference, April 19-20, 2004, St. Louis, Missouri 19011, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    3. Mohamed Chikhi & Anne Péguin-Feissolle & Michel Terraza, 2013. "SEMIFARMA-HYGARCH Modeling of Dow Jones Return Persistence," Computational Economics, Springer;Society for Computational Economics, vol. 41(2), pages 249-265, February.
    4. Amilon, Henrik, 2008. "Estimation of an adaptive stock market model with heterogeneous agents," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 342-362, March.
    5. Amin Aminimehr & Ali Raoofi & Akbar Aminimehr & Amirhossein Aminimehr, 2022. "A Comprehensive Study of Market Prediction from Efficient Market Hypothesis up to Late Intelligent Market Prediction Approaches," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 781-815, August.
    6. Remes, Piia, 2013. "Putting a Price on Carbon – Econometric Essays on the European Union Emissions Trading Scheme and its Impacts," Research Reports 62, VATT Institute for Economic Research.
    7. Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
    8. F. DePenya & L. Gil-Alana, 2006. "Testing of nonstationary cycles in financial time series data," Review of Quantitative Finance and Accounting, Springer, vol. 27(1), pages 47-65, August.
    9. repec:uts:finphd:39 is not listed on IDEAS
    10. Degenhardt, Thomas & Auer, Benjamin R., 2018. "The “Sell in May” effect: A review and new empirical evidence," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 169-205.
    11. Kamal, Mona, 2014. "Studying the Validity of the Efficient Market Hypothesis (EMH) in the Egyptian Exchange (EGX) after the 25th of January Revolution," MPRA Paper 54708, University Library of Munich, Germany.
    12. Xiufeng Yan, 2021. "Multiplicative Component GARCH Model of Intraday Volatility," Papers 2111.02376, arXiv.org.
    13. Matheus José Silva de Souza & Danilo Guimarães Franco Ramos & Marina Garcia Pena & Vinicius Amorim Sobreiro & Herbert Kimura, 2018. "Examination of the profitability of technical analysis based on moving average strategies in BRICS," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 4(1), pages 1-18, December.
    14. Yaya, OlaOluwa S. & Vo, Xuan Vinh & Adekoya, Oluwasegun B., 2021. "Market Efficiency of Asian Stocks: Evidence based on Narayan-Liu-Westerlund GARCH-based Unit root test," MPRA Paper 109828, University Library of Munich, Germany.
    15. Aatola, Piia, 2013. "Putting a Price on Carbon – Econometric Essays on the European Union Emissions Trading Scheme and its Impacts," Research Reports P62, VATT Institute for Economic Research.
    16. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
    17. OlaOluwa S. Yaya & Oluwasegun B. Adekoya & Xuan Vinh Vo & Mamdouh Abdulaziz Saleh Al‐Faryan, 2024. "Stock Market Efficiency in Asia: Evidence from the Narayan–Liu–Westerlund's GARCH‐based unit root test," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 91-101, January.
    18. Ausloos, Marcel & Jovanovic, Franck & Schinckus, Christophe, 2016. "On the “usual” misunderstandings between econophysics and finance: Some clarifications on modelling approaches and efficient market hypothesis," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 7-14.
    19. Roberto Ortiz & Mauricio Contreras & Marcelo Villena, 2015. "On the Efficient Market Hypothesis of Stock Market Indexes: The Role of Non-synchronous Trading and Portfolio Effects," Papers 1510.03926, arXiv.org.
    20. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    21. repec:uts:finphd:38 is not listed on IDEAS
    22. Emmanuel O. Nwosu & Anthony Orji & Ogomegbunam Anagwu, 2013. "African Emerging Equity Markets Re-examined: Testing the Weak Form Efficiency Theory," African Development Review, African Development Bank, vol. 25(4), pages 485-498.

    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:eee:phsmap:v:298:y:2001:i:3:p:521-529. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.