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Multi-scale Representation of High Frequency Market Liquidity

  • Anton Golub
  • Gregor Chliamovitch
  • Alexandre Dupuis
  • Bastien Chopard
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    We introduce an event based framework of directional changes and overshoots to map continuous financial data into the so-called Intrinsic Network - a state based discretisation of intrinsically dissected time series. Defining a method for state contraction of Intrinsic Network, we show that it has a consistent hierarchical structure that allows for multi-scale analysis of financial data. We define an information theoretic measurement termed Liquidity that characterises the unlikeliness of price trajectories and argue that the new metric has the ability to detect and predict stress in financial markets. We show empirical examples within the Foreign Exchange market where the new measure not only quantifies liquidity but also acts as an early warning signal.

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    File URL: http://arxiv.org/pdf/1402.2198
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    Paper provided by arXiv.org in its series Papers with number 1402.2198.

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    Date of creation: Feb 2014
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    Handle: RePEc:arx:papers:1402.2198
    Contact details of provider: Web page: http://arxiv.org/

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    1. J. B. Glattfelder & A. Dupuis & R. B. Olsen, 2008. "Patterns in high-frequency FX data: Discovery of 12 empirical scaling laws," Papers 0809.1040, arXiv.org, revised Jun 2010.
    2. Alexandros Gabrielsen & Massimiliano Marzo & Paolo Zagaglia, 2012. "Measuring Market Liquidity: An Introductory Survey," Working Paper Series 02_12, The Rimini Centre for Economic Analysis.
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