IDEAS home Printed from https://ideas.repec.org/p/arx/papers/cond-mat-0302434.html
   My bibliography  Save this paper

Using the Scaling Analysis to Characterize Financial Markets

Author

Listed:
  • T. Di Matteo
  • T. Aste
  • M. M. Dacorogna

Abstract

We empirically analyze the scaling properties of daily Foreign Exchange rates, Stock Market indices and Bond futures across different financial markets. We study the scaling behaviour of the time series by using a generalized Hurst exponent approach. We verify the robustness of this approach and we compare the results with the scaling properties in the frequency-domain. We find evidence of deviations from the pure Brownian motion behavior. We show that these deviations are associated with characteristics of the specific markets and they can be, therefore, used to distinguish the different degrees of development of the markets.

Suggested Citation

  • T. Di Matteo & T. Aste & M. M. Dacorogna, 2003. "Using the Scaling Analysis to Characterize Financial Markets," Papers cond-mat/0302434, arXiv.org.
    • Handle: RePEc:arx:papers:cond-mat/0302434
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/cond-mat/0302434
    File Function: Latest version
    Download Restriction: no
    ---><---

    Other versions of this item:

    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. Fulvio Corsi & Gilles Zumbach & Ulrich A. Muller & Michel M. Dacorogna, 2001. "Consistent High-precision Volatility from High-frequency Data," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 30(2), pages 183-204, July.
    3. Grau-Carles, Pilar, 2000. "Empirical evidence of long-range correlations in stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 396-404.
    4. H. E. Stanley & V. Plerou, 2001. "Scaling and universality in economics: empirical results and theoretical interpretation," Quantitative Finance, Taylor & Francis Journals, vol. 1(6), pages 563-567.
    5. B. B. Mandelbrot, 2001. "Stochastic volatility, power laws and long memory," Quantitative Finance, Taylor & Francis Journals, vol. 1(6), pages 558-559.
    6. Blake LeBaron, 2001. "Volatility," Computing in Economics and Finance 2001 108, Society for Computational Economics.
    7. Benoit Mandelbrot, 1967. "The Variation of Some Other Speculative Prices," The Journal of Business, University of Chicago Press, vol. 40, pages 393-393.
    8. M. F. M. Osborne, 1959. "Brownian Motion in the Stock Market," Operations Research, INFORMS, vol. 7(2), pages 145-173, April.
    9. J.-P. Bouchaud & M. Potters & M. Meyer, 2000. "Apparent multifractality in financial time series," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 13(3), pages 595-599, February.
    10. M. Ausloos & K. Ivanova, 2001. "Correlations Between Reconstructed EUR Exchange Rates vs. CHF, DKK, GBP, JPY and USD," Papers cond-mat/0104260, arXiv.org.
    11. Weron, Rafal & Przybyłowicz, Beata, 2000. "Hurst analysis of electricity price dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 283(3), pages 462-468.
    12. Brock, W A, 1999. "Scaling in Economics: A Reader's Guide," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 8(3), pages 409-446, September.
    13. Patrick A. Groenendijk & André Lucas & Casper G. de Vries, 1998. "A Hybrid Joint Moment Ratio Test for Financial Time Series," Tinbergen Institute Discussion Papers 98-104/2, Tinbergen Institute.
    14. Vandewalle, N. & Ausloos, M., 1997. "Coherent and random sequences in financial fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 246(3), pages 454-459.
    15. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    16. Muller, Ulrich A. & Dacorogna, Michel M. & Olsen, Richard B. & Pictet, Olivier V. & Schwarz, Matthias & Morgenegg, Claude, 1990. "Statistical study of foreign exchange rates, empirical evidence of a price change scaling law, and intraday analysis," Journal of Banking & Finance, Elsevier, vol. 14(6), pages 1189-1208, December.
    17. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    18. Eugene F. Fama, 1963. "Mandelbrot and the Stable Paretian Hypothesis," The Journal of Business, University of Chicago Press, vol. 36, pages 420-420.
    19. Gençay, Ramazan & Dacorogna, Michel & Muller, Ulrich A. & Pictet, Olivier & Olsen, Richard, 2001. "An Introduction to High-Frequency Finance," Elsevier Monographs, Elsevier, edition 1, number 9780122796715.
    20. Stanley, H.E & Buldyrev, S.V & Goldberger, A.L & Havlin, S & Peng, C.-K & Simons, M, 1999. "Scaling features of noncoding DNA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 273(1), pages 1-18.
    21. Jean-Philippe Bouchaud & Marc Potters & Martin Meyer, 1999. "Apparent multifractality in financial time series," Science & Finance (CFM) working paper archive 9906347, Science & Finance, Capital Fund Management.
    22. M. Ausloos & K. Ivanova, 2001. "False Euro (FEUR) exchange rate correlated behaviors and investment strategy," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 20(4), pages 537-541, April.
    23. Gençay, Ramazan & Selçuk, Faruk & Whitcher, Brandon, 2001. "Scaling properties of foreign exchange volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 289(1), pages 249-266.
    24. T. Lux, 2001. "Turbulence in financial markets: the surprising explanatory power of simple cascade models," Quantitative Finance, Taylor & Francis Journals, vol. 1(6), pages 632-640.
    25. N. Vandewalle & M. Ausloos, 1998. "Sparseness and Roughness of Foreign Exchange Rates," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 9(05), pages 711-719.
    26. B. LeBaron, 2001. "Stochastic volatility as a simple generator of apparent financial power laws and long memory," Quantitative Finance, Taylor & Francis Journals, vol. 1(6), pages 621-631.
    27. K. Ivanova & M. Ausloos, 2001. "False EUR exchange rates vs. DKK, CHF, JPY and USD. What is a strong currency?," Papers cond-mat/0103033, arXiv.org.
    28. M. Dacorogna & U. Mller & R. Olsen & O. Pictet, 2001. "Defining efficiency in heterogeneous markets," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 198-201.
    29. Ausloos, M., 2000. "Statistical physics in foreign exchange currency and stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 285(1), pages 48-65.
    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. Ioan Roxana, 2020. "Capital Market Correlations Structure During The Covid-19 Crisis," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 6, pages 67-79, December.
    2. Selçuk, Faruk & Gençay, Ramazan, 2006. "Intraday dynamics of stock market returns and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 375-387.
    3. Selçuk, Faruk, 2004. "Financial earthquakes, aftershocks and scaling in emerging stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 306-316.

    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. Matteo, T. Di & Aste, T. & Dacorogna, Michel M., 2005. "Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 827-851, April.
    2. Segnon, Mawuli & Lux, Thomas, 2013. "Multifractal models in finance: Their origin, properties, and applications," Kiel Working Papers 1860, Kiel Institute for the World Economy (IfW Kiel).
    3. Selçuk, Faruk & Gençay, Ramazan, 2006. "Intraday dynamics of stock market returns and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 375-387.
    4. Goddard, John & Onali, Enrico, 2012. "Self-affinity in financial asset returns," International Review of Financial Analysis, Elsevier, vol. 24(C), pages 1-11.
    5. Selçuk, Faruk, 2004. "Financial earthquakes, aftershocks and scaling in emerging stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 306-316.
    6. Baldovin, Fulvio & Caporin, Massimiliano & Caraglio, Michele & Stella, Attilio L. & Zamparo, Marco, 2015. "Option pricing with non-Gaussian scaling and infinite-state switching volatility," Journal of Econometrics, Elsevier, vol. 187(2), pages 486-497.
    7. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Kiel Working Papers 1426, Kiel Institute for the World Economy (IfW Kiel).
    8. Xu, Zhaoxia & Gençay, Ramazan, 2003. "Scaling, self-similarity and multifractality in FX markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 323(C), pages 578-590.
    9. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
    10. Barunik, Jozef & Aste, Tomaso & Di Matteo, T. & Liu, Ruipeng, 2012. "Understanding the source of multifractality in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4234-4251.
    11. Raffaello Morales & T. Di Matteo & Ruggero Gramatica & Tomaso Aste, 2011. "Dynamical Hurst exponent as a tool to monitor unstable periods in financial time series," Papers 1109.0465, arXiv.org.
    12. Boilard, J.-F. & Kanazawa, K. & Takayasu, H. & Takayasu, M., 2018. "Empirical scaling relations of market event rates in foreign currency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1152-1161.
    13. Dubovikov, M.M & Starchenko, N.V & Dubovikov, M.S, 2004. "Dimension of the minimal cover and fractal analysis of time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(3), pages 591-608.
    14. Paulo Ferreira & Luís Carlos Loures, 2020. "An Econophysics Study of the S&P Global Clean Energy Index," Sustainability, MDPI, vol. 12(2), pages 1-9, January.
    15. Marcel Ausloos, 2013. "Econophysics: Comments on a Few Applications, Successes, Methods and Models," IIM Kozhikode Society & Management Review, , vol. 2(2), pages 101-115, July.
    16. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    17. Wang, Dong-Hua & Yu, Xiao-Wen & Suo, Yuan-Yuan, 2012. "Statistical properties of the yuan exchange rate index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(12), pages 3503-3512.
    18. Seemann, Lars & Hua, Jia-Chen & McCauley, Joseph L. & Gunaratne, Gemunu H., 2012. "Ensemble vs. time averages in financial time series analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(23), pages 6024-6032.
    19. Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.
    20. Antoniades, I.P. & Brandi, Giuseppe & Magafas, L. & Di Matteo, T., 2021. "The use of scaling properties to detect relevant changes in financial time series: A new visual warning tool," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).

    More about this item

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets

    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:cond-mat/0302434. 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.