IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-07c50001.html
   My bibliography  Save this article

Scale invariance in financial time series

Author

Listed:
  • Ranasinghe Malmini

    (University of Sri Jayewardenepura)

Abstract

We focus on new insights of scale invariance and scaling properties usefully applied in the framework of a statistical approach to study the empirical finance. Two stock returns of Sri Lankan stock market indices All Share Price Index and Milanka Price Index index were considered. Central parts of the probability distribution function of returns are well fitted by the Lorentzian distribution function. However, tail parts of the probability distribution function follow a power law asymptotic behavior. We found that the probability distribution function of returns for both All Share Price Index and Milanka Price Index , is outside the L´evy stable distribution. Sri Lankan stock market is not described by the random Gaussian stochastic processes.

Suggested Citation

  • Ranasinghe Malmini, 2007. "Scale invariance in financial time series," Economics Bulletin, AccessEcon, vol. 3(24), pages 1-7.
    • Handle: RePEc:ebl:ecbull:eb-07c50001
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/pubs/EB/2007/Volume3/EB-07C50001A.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    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. Lallouache, Mehdi & Abergel, Frédéric, 2014. "Tick size reduction and price clustering in a FX order book," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 488-498.
    2. 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.
    3. Hua, Jia-Chen & Chen, Lijian & Falcon, Liberty & McCauley, Joseph L. & Gunaratne, Gemunu H., 2015. "Variable diffusion in stock market fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 221-233.
    4. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    5. 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.
    6. Kang, Sang Hoon & Yoon, Seong-Min, 2008. "Long memory features in the high frequency data of the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5189-5196.
    7. Denzler, Stefan M. & Dacorogna, Michel M. & Muller, Ulrich A. & McNeil, Alexander J., 2006. "From default probabilities to credit spreads: Credit risk models do explain market prices," Finance Research Letters, Elsevier, vol. 3(2), pages 79-95, June.
    8. J. B. Glattfelder & A. Dupuis & R. B. Olsen, 2010. "Patterns in high-frequency FX data: discovery of 12 empirical scaling laws," Quantitative Finance, Taylor & Francis Journals, vol. 11(4), pages 599-614.
    9. 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.
    10. Moonis Shakeel & Bhavana Srivastava, 2021. "Stylized Facts of High-frequency Financial Time Series Data," Global Business Review, International Management Institute, vol. 22(2), pages 550-564, April.
    11. Nava, Noemi & Di Matteo, T. & Aste, Tomaso, 2016. "Anomalous volatility scaling in high frequency financial data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 434-445.
    12. Bekiros, Stelios D., 2015. "Heuristic learning in intraday trading under uncertainty," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 34-49.
    13. 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.
    14. Leah Kelly, 2004. "Inference and Intraday Analysis of Diversified World Stock Indices," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 24, July-Dece.
    15. F. Baldovin & F. Camana & M. Caporin & M. Caraglio & A.L. Stella, 2015. "Ensemble properties of high-frequency data and intraday trading rules," Quantitative Finance, Taylor & Francis Journals, vol. 15(2), pages 231-245, February.
    16. Seemann, Lars & McCauley, Joseph L. & Gunaratne, Gemunu H., 2011. "Intraday volatility and scaling in high frequency foreign exchange markets," International Review of Financial Analysis, Elsevier, vol. 20(3), pages 121-126, June.
    17. Vladimir Petrov & Anton Golub & Richard Olsen, 2019. "Instantaneous Volatility Seasonality of High-Frequency Markets in Directional-Change Intrinsic Time," JRFM, MDPI, vol. 12(2), pages 1-31, April.
    18. Leah Kelly, 2004. "Inference and Intraday Analysis of Diversified World Stock Indices," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2004, January-A.
    19. Karuppiah, Jeyanthi & Los, Cornelis A., 2005. "Wavelet multiresolution analysis of high-frequency Asian FX rates, Summer 1997," International Review of Financial Analysis, Elsevier, vol. 14(2), pages 211-246.
    20. Wei Sun & Svetlozar Rachev & Frank Fabozzi & Petko Kalev, 2009. "A new approach to modeling co-movement of international equity markets: evidence of unconditional copula-based simulation of tail dependence," Empirical Economics, Springer, vol. 36(1), pages 201-229, February.

    More about this item

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • P0 - Political Economy and Comparative Economic Systems - - General

    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:ebl:ecbull:eb-07c50001. 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: John P. Conley (email available below). General contact details of provider: .

    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.