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Patterns in high-frequency FX data: discovery of 12 empirical scaling laws

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  • J. B. Glattfelder
  • A. Dupuis
  • R. B. Olsen

Abstract

We have discovered 12 independent new empirical scaling laws in foreign exchange data series that hold for close to three orders of magnitude and across 13 currency exchange rates. Our statistical analysis crucially depends on an event-based approach that measures the relationship between different types of events. The scaling laws give an accurate estimation of the length of the price-curve coastline, which turns out to be surprisingly long. The new laws substantially extend the catalogue of stylized facts and sharply constrain the space of possible theoretical explanations of the market mechanisms.

Suggested Citation

  • 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.
  • Handle: RePEc:taf:quantf:v:11:y:2010:i:4:p:599-614
    DOI: 10.1080/14697688.2010.481632
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    Cited by:

    1. T. Bisig & A. Dupuis & V. Impagliazzo & R. B. Olsen, 2012. "The scale of market quakes," Quantitative Finance, Taylor & Francis Journals, vol. 12(4), pages 501-508, July.
    2. 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.
    3. Aloud, Monira & Tsang, Edward & Olsen, Richard & Dupuis, Alexandre, 2012. "A directional-change event approach for studying financial time series," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 6, pages 1-17.
    4. Edward P. K. Tsang & Ran Tao & Antoaneta Serguieva & Shuai Ma, 2017. "Profiling high-frequency equity price movements in directional changes," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 217-225, February.
    5. Monira Essa Aloud, 2016. "Time Series Analysis Indicators under Directional Changes: The Case of Saudi Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 6(1), pages 55-64.
    6. Monira Essa Aloud, 2016. "Profitability of Directional Change Based Trading Strategies: The Case of Saudi Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 6(1), pages 87-95.
    7. Gapeev, Pavel V. & Rodosthenous, Neofytos & Chinthalapati, V.L Raju, 2019. "On the Laplace transforms of the first hitting times for drawdowns and drawups of diffusion-type processes," LSE Research Online Documents on Economics 101272, London School of Economics and Political Science, LSE Library.
    8. Noemi Nava & T. Di Matteo & Tomaso Aste, 2015. "Anomalous volatility scaling in high frequency financial data," Papers 1503.08465, arXiv.org, revised Dec 2015.
    9. Thomas Chopping, 2014. "Scaling laws: a viable alternative to value at risk?," Quantitative Finance, Taylor & Francis Journals, vol. 14(5), pages 889-911, May.
    10. James B. Glattfelder & Thomas Bisig & Richard B. Olsen, 2014. "R&D Strategy Document," Papers 1405.6027, arXiv.org.
    11. Denis M. Filatov & Maksim A. Vanyarkho, 2014. "An Unconventional Attempt to Tame Mandelbrot's Grey Swans," Papers 1406.5718, arXiv.org.
    12. Aloud, Monira & Tsang, Edward & Olsen, Richard & Dupuis, Alexandre, 2011. "A directional-change events approach for studying financial time series," Economics Discussion Papers 2011-28, Kiel Institute for the World Economy (IfW).
    13. Vladimir Petrov & Anton Golub & Richard Olsen, 2019. "Instantaneous Volatility Seasonality of High-Frequency Markets in Directional-Change Intrinsic Time," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 12(2), pages 1-31, April.
    14. Anton Golub & Gregor Chliamovitch & Alexandre Dupuis & Bastien Chopard, 2014. "Multi-scale Representation of High Frequency Market Liquidity," Papers 1402.2198, arXiv.org.

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