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Deep Recurrent Modelling of Stationary Bitcoin Price Formation Using the Order Flow

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  • Ye-Sheen Lim
  • Denise Gorse

Abstract

In this paper we propose a deep recurrent model based on the order flow for the stationary modelling of the high-frequency directional prices movements. The order flow is the microsecond stream of orders arriving at the exchange, driving the formation of prices seen on the price chart of a stock or currency. To test the stationarity of our proposed model we train our model on data before the 2017 Bitcoin bubble period and test our model during and after the bubble. We show that without any retraining, the proposed model is temporally stable even as Bitcoin trading shifts into an extremely volatile "bubble trouble" period. The significance of the result is shown by benchmarking against existing state-of-the-art models in the literature for modelling price formation using deep learning.

Suggested Citation

  • Ye-Sheen Lim & Denise Gorse, 2020. "Deep Recurrent Modelling of Stationary Bitcoin Price Formation Using the Order Flow," Papers 2004.01499, arXiv.org.
  • Handle: RePEc:arx:papers:2004.01499
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    References listed on IDEAS

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    1. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.
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    3. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2013. "Limit order books," Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1709-1742, November.
    4. Justin Sirignano & Rama Cont, 2019. "Universal features of price formation in financial markets: perspectives from deep learning," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1449-1459, September.
    5. Jerome L Kreuser & Didier Sornette, 2018. "Bitcoin Bubble Trouble," Swiss Finance Institute Research Paper Series 18-24, Swiss Finance Institute, revised Jun 2018.
    6. Emmanuel Bacry & Jean-Fran�ois Muzy, 2014. "Hawkes model for price and trades high-frequency dynamics," Quantitative Finance, Taylor & Francis Journals, vol. 14(7), pages 1147-1166, July.
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