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An empirical investigation of Australian Stock Exchange data

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  • Bertram, William K
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    Abstract

    We present an empirical study of high frequency Australian equity data examining the behaviour of distribution tails and the existence of long memory. A method is presented allowing us to deal with Australian Stock Exchange data by splitting it into two separate data series representing an intraday and overnight component. Power-law exponents for the empirical density functions are estimated and compared with results from other studies. Using the autocorrelation and variance plots we find there to be a strong indication of long-memory type behaviour in the absolute return, volume and transaction frequency.

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    Bibliographic Info

    Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

    Volume (Year): 341 (2004)
    Issue (Month): C ()
    Pages: 533-546

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    Handle: RePEc:eee:phsmap:v:341:y:2004:i:c:p:533-546

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    Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

    Related research

    Keywords: Econophysics; Power law tails; Long memory process;

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    Cited by:
    1. Bertram, William K. & Peiris, M. Shelton, 2007. "An example of a misclassification problem applied to Australian equity data," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 3627-3630, May.
    2. Tabak, B.M. & Takami, M.Y. & Cajueiro, D.O. & Petitinga, A., 2009. "Quantifying price fluctuations in the Brazilian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(1), pages 59-62.
    3. Gao-Feng Gu & Xiong Xiong & Yong-Jie Zhang & Wei Chen & Wei Zhang & Wei-Xing Zhou, 2014. "Stylized facts of price gaps in limit order books: Evidence from Chinese stocks," Papers 1405.1247, arXiv.org.
    4. Gu, Gao-Feng & Chen, Wei & Zhou, Wei-Xing, 2008. "Empirical distributions of Chinese stock returns at different microscopic timescales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 495-502.
    5. Bertram, William K., 2009. "Optimal trading strategies for Itô diffusion processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2865-2873.
    6. Mark M. Meerschaert & Enrico Scalas, 2006. "Coupled continuous time random walks in finance," Papers physics/0608281, arXiv.org.
    7. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2013. "Intraday volatility spillovers between spot and futures indices: Evidence from the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1795-1802.
    8. Politi, Mauro & Scalas, Enrico, 2008. "Fitting the empirical distribution of intertrade durations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(8), pages 2025-2034.
    9. Bertram, William K., 2008. "Measuring time dependent volatility and cross-sectional correlation in Australian equity returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(13), pages 3183-3191.
    10. Raynaud, Franck & Lautier, Delphine, 2011. "Statistical properties of derivatives: a journey in term structures," Economics Papers from University Paris Dauphine 123456789/5528, Paris Dauphine University.
    11. Long, Yu, 2013. "Visibility graph network analysis of gold price time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(16), pages 3374-3384.

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