IDEAS home Printed from https://ideas.repec.org/r/hal/journl/hal-02177394.html
   My bibliography  Save this item

Limit Order Books

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Masatoshi Goda, 2021. "Hawkes process and Edgeworth expansion with application to maximum likelihood estimator," Statistical Inference for Stochastic Processes, Springer, vol. 24(2), pages 277-325, July.
  2. Ioane Muni Toke, 2017. "Stationary Distribution Of The Volume At The Best Quote In A Poisson Order Book Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(06), pages 1-22, September.
  3. Yufei Wu & Mahmoud Mahfouz & Daniele Magazzeni & Manuela Veloso, 2021. "Towards Robust Representation of Limit Orders Books for Deep Learning Models," Papers 2110.05479, arXiv.org, revised Dec 2022.
  4. Ioane Muni Toke, 2017. "Stationary Distribution Of The Volume At The Best Quote In A Poisson Order Book Model," Post-Print hal-01705085, HAL.
  5. Tommaso Mariotti & Fabrizio Lillo & Giacomo Toscano, 2022. "From Zero-Intelligence to Queue-Reactive: Limit Order Book modeling for high-frequency volatility estimation and optimal execution," Papers 2202.12137, arXiv.org, revised Sep 2022.
  6. Emmanouil Sfendourakis & Ioane Muni Toke, 2021. "LOB modeling using Hawkes processes with a state-dependent factor," Papers 2107.12872, arXiv.org, revised Dec 2021.
  7. Xiaofei Lu & Frédéric Abergel, 2017. "Limit order book modelling with high dimensional Hawkes processes," Working Papers hal-01512430, HAL.
  8. Charles-Albert Lehalle & Eyal Neuman, 2019. "Incorporating signals into optimal trading," Finance and Stochastics, Springer, vol. 23(2), pages 275-311, April.
  9. Alexander Barzykin & Philippe Bergault & Olivier Gu'eant, 2021. "Algorithmic market making in dealer markets with hedging and market impact," Papers 2106.06974, arXiv.org, revised Dec 2022.
  10. Federico Gonzalez & Mark Schervish, 2017. "Instantaneous order impact and high-frequency strategy optimization in limit order books," Papers 1707.01167, arXiv.org, revised Oct 2017.
  11. Frédéric Abergel & Côme Huré & Huyên Pham, 2019. "Algorithmic trading in a microstructural limit order book model," Working Papers hal-01514987, HAL.
  12. Thomas Spooner & Rahul Savani, 2020. "Robust Market Making via Adversarial Reinforcement Learning," Papers 2003.01820, arXiv.org, revised Jul 2020.
  13. Restocchi, Valerio & McGroarty, Frank & Gerding, Enrico, 2019. "Statistical properties of volume and calendar effects in prediction markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1150-1160.
  14. Peng Wu & Marcello Rambaldi & Jean-François Muzy & Emmanuel Bacry, 2021. "Queue-reactive Hawkes models for the order flow," Working Papers hal-02409073, HAL.
  15. Ingemar Kaj & Mine Caglar, 2017. "A buffer Hawkes process for limit order books," Papers 1710.03506, arXiv.org.
  16. Ioane Muni Toke & Nakahiro Yoshida, 2017. "Modelling intensities of order flows in a limit order book," Post-Print hal-01705080, HAL.
  17. Peng Wu & Marcello Rambaldi & Jean-Franc{c}ois Muzy & Emmanuel Bacry, 2019. "Queue-reactive Hawkes models for the order flow," Papers 1901.08938, arXiv.org.
  18. Xiaofei Lu & Fr'ed'eric Abergel, 2018. "Order-book modelling and market making strategies," Papers 1806.05101, arXiv.org.
  19. Nik Alexandrov & Dave Cliff & Charlie Figuero, 2021. "Exploring Coevolutionary Dynamics of Competitive Arms-Races Between Infinitely Diverse Heterogenous Adaptive Automated Trader-Agents," Papers 2109.10429, arXiv.org.
  20. Ioane Muni Toke & Nakahiro Yoshida, 2016. "Modelling intensities of order flows in a limit order book," Papers 1602.03944, arXiv.org.
  21. Frédéric Abergel & Côme Huré & Huyên Pham, 2020. "Algorithmic trading in a microstructural limit order book model," Post-Print hal-01514987, HAL.
  22. Svitlana Vyetrenko & David Byrd & Nick Petosa & Mahmoud Mahfouz & Danial Dervovic & Manuela Veloso & Tucker Hybinette Balch, 2019. "Get Real: Realism Metrics for Robust Limit Order Book Market Simulations," Papers 1912.04941, arXiv.org.
  23. Thomas Spooner & John Fearnley & Rahul Savani & Andreas Koukorinis, 2018. "Market Making via Reinforcement Learning," Papers 1804.04216, arXiv.org.
  24. Junyi Li & Xitong Wang & Yaoyang Lin & Arunesh Sinha & Micheal P. Wellman, 2020. "Generating Realistic Stock Market Order Streams," Papers 2006.04212, arXiv.org.
  25. Michael Karpe & Jin Fang & Zhongyao Ma & Chen Wang, 2020. "Multi-Agent Reinforcement Learning in a Realistic Limit Order Book Market Simulation," Papers 2006.05574, arXiv.org, revised Sep 2020.
  26. Fr'ed'eric Abergel & C^ome Hur'e & Huy^en Pham, 2017. "Algorithmic trading in a microstructural limit order book model," Papers 1705.01446, arXiv.org, revised Feb 2020.
  27. Antonio Briola & Jeremy Turiel & Tomaso Aste, 2020. "Deep Learning modeling of Limit Order Book: a comparative perspective," Papers 2007.07319, arXiv.org, revised Oct 2020.
  28. Xiaofei Lu & Frédéric Abergel, 2018. "High dimensional Hawkes processes for limit order books Modelling, empirical analysis and numerical calibration," Post-Print hal-01686122, HAL.
  29. Yufei Wu & Mahmoud Mahfouz & Daniele Magazzeni & Manuela Veloso, 2021. "How Robust are Limit Order Book Representations under Data Perturbation?," Papers 2110.04752, arXiv.org.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.