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Limit Order Books

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Cited by:

  1. Ivan Jericevich & Patrick Chang & Tim Gebbie, 2021. "Simulation and estimation of a point-process market-model with a matching engine," Papers 2105.02211, arXiv.org, revised Aug 2021.
  2. Dave Cliff & James Hawkins & James Keen & Roberto Lau-Soto, 2021. "Implementing the BBE Agent-Based Model of a Sports-Betting Exchange," Papers 2108.02419, arXiv.org.
  3. Antoine Jacquier & Hao Liu, 2017. "Optimal liquidation in a Level-I limit order book for large tick stocks," Papers 1701.01327, arXiv.org, revised Nov 2017.
  4. Haeringer, Guillaume & Melton, Hayden, 2020. "High Frequency Fairness," MPRA Paper 103907, University Library of Munich, Germany.
  5. Paulin, James & Calinescu, Anisoara & Wooldridge, Michael, 2019. "Understanding flash crash contagion and systemic risk: A micro–macro agent-based approach," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 200-229.
  6. Roger Martins & Dieter Hendricks, 2016. "The statistical significance of multivariate Hawkes processes fitted to limit order book data," Papers 1604.01824, arXiv.org, revised Apr 2016.
  7. Thomas Spooner & Rahul Savani, 2020. "Robust Market Making via Adversarial Reinforcement Learning," Papers 2003.01820, arXiv.org, revised Jul 2020.
  8. Yamamoto, Ryuichi, 2019. "Dynamic Predictor Selection And Order Splitting In A Limit Order Market," Macroeconomic Dynamics, Cambridge University Press, vol. 23(5), pages 1757-1792, July.
  9. Alberto Ciacci & Takumi Sueshige & Hideki Takayasu & Kim Christensen & Misako Takayasu, 2020. "The microscopic relationships between triangular arbitrage and cross-currency correlations in a simple agent based model of foreign exchange markets," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-19, June.
  10. Ivan Jericevich & Patrick Chang & Tim Gebbie, 2021. "Simulation and estimation of an agent-based market-model with a matching engine," Papers 2108.07806, arXiv.org, revised Aug 2021.
  11. Qing-Qing Yang & Wai-Ki Ching & Jiawen Gu & Tak-Kuen Siu, 2020. "Trading strategy with stochastic volatility in a limit order book market," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 43(1), pages 277-301, June.
  12. 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.
  13. Sudhanshu Pani, 2020. "A Theory of 'Auction as a Search' in speculative markets," Papers 2006.00775, arXiv.org.
  14. Fa-Bin Shi & Xiao-Qian Sun & Jin-Hua Gao & Li Xu & Hua-Wei Shen & Xue-Qi Cheng, 2019. "Anomaly detection in Bitcoin market via price return analysis," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-11, June.
  15. Gu, Gao-Feng & Xiong, Xiong & Zhang, Yong-Jie & Chen, Wei & Zhang, Wei & Zhou, Wei-Xing, 2016. "Stylized facts of price gaps in limit order books," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 48-58.
  16. Abbas Haider & Hui Wang & Bryan Scotney & Glenn Hawe, 2022. "Predictive Market Making via Machine Learning," SN Operations Research Forum, Springer, vol. 3(1), pages 1-21, March.
  17. Julius Bonart & Martin D. Gould, 2017. "Latency and liquidity provision in a limit order book," Quantitative Finance, Taylor & Francis Journals, vol. 17(10), pages 1601-1616, October.
  18. Nino Antulov-Fantulin & Tian Guo & Fabrizio Lillo, 2021. "Temporal mixture ensemble models for probabilistic forecasting of intraday cryptocurrency volume," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 905-940, December.
  19. Xuefeng Gao & S. J. Deng, 2014. "Hydrodynamic limit of order book dynamics," Papers 1411.7502, arXiv.org, revised Feb 2016.
  20. Efstathios Panayi & Gareth Peters, 2015. "Stochastic simulation framework for the Limit Order Book using liquidity motivated agents," Papers 1501.02447, arXiv.org, revised Jan 2015.
  21. Efstathios Panayi & Gareth W. Peters, 2015. "Stochastic simulation framework for the limit order book using liquidity-motivated agents," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 2(02), pages 1-52.
  22. Eduard Silantyev, 2019. "Order flow analysis of cryptocurrency markets," Digital Finance, Springer, vol. 1(1), pages 191-218, November.
  23. Dave Cliff, 2021. "BBE: Simulating the Microstructural Dynamics of an In-Play Betting Exchange via Agent-Based Modelling," Papers 2105.08310, arXiv.org.
  24. Jian Zhou & Gao-Feng Gu & Zhi-Qiang Jiang & Xiong Xiong & Wei Chen & Wei Zhang & Wei-Xing Zhou, 2017. "Computational Experiments Successfully Predict the Emergence of Autocorrelations in Ultra-High-Frequency Stock Returns," Computational Economics, Springer;Society for Computational Economics, vol. 50(4), pages 579-594, December.
  25. Ismael Lemhadri, 2018. "Market Impact in a Latent Order Book," Papers 1802.06101, arXiv.org, revised Sep 2020.
  26. Frank Kelly & Elena Yudovina, 2015. "A Markov model of a limit order book: thresholds, recurrence, and trading strategies," Papers 1504.00579, arXiv.org, revised Mar 2017.
  27. Qiyue He & Anatoliy Swishchuk, 2019. "Quantitative and Comparative Analyses of Limit Order Books with General Compound Hawkes Processes," Risks, MDPI, vol. 7(4), pages 1-21, November.
  28. Ioane Muni Toke & Nakahiro Yoshida, 2019. "Analyzing order flows in limit order books with ratios of Cox-type intensities," Working Papers hal-01799398, HAL.
  29. Ismael Lemhadri, 2018. "Market impact in a latent order book," Working Papers hal-01711192, HAL.
  30. Pankaj Kumar, 2021. "Deep Hawkes Process for High-Frequency Market Making," Papers 2109.15110, arXiv.org.
  31. Anatoliy Swishchuk & Tyler Hofmeister & Katharina Cera & Julia Schmidt, 2017. "General Semi-Markov Model For Limit Order Books," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(03), pages 1-21, May.
  32. Andrew Todd & Peter Beling & William Scherer, 2016. "Crossed and Locked Quotes in a Multi-Market Simulation," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-19, March.
  33. Adamantios Ntakaris & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2020. "Mid-price prediction based on machine learning methods with technical and quantitative indicators," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-39, June.
  34. Martin D. Gould & Nikolaus Hautsch & Sam D. Howison & Mason A. Porter, 2020. "Counterparty Credit Limits: The Impact of a Risk-Mitigation Measure on Everyday Trading," Applied Mathematical Finance, Taylor & Francis Journals, vol. 27(6), pages 520-548, November.
  35. Ben Hambly & Jasdeep Kalsi & James Newbury, 2018. "Limit order books, diffusion approximations and reflected SPDEs: from microscopic to macroscopic models," Papers 1808.07107, arXiv.org, revised Jun 2019.
  36. Fabien Guilbaud & Huyen Pham, 2011. "Optimal High Frequency Trading with limit and market orders," Working Papers hal-00603385, HAL.
  37. Vygintas Gontis, 2021. "Order flow in the financial markets from the perspective of the Fractional L\'evy stable motion," Papers 2105.02057, arXiv.org, revised Nov 2021.
  38. Konark Jain & Nick Firoozye & Jonathan Kochems & Philip Treleaven, 2024. "Limit Order Book Simulations: A Review," Papers 2402.17359, arXiv.org, revised Mar 2024.
  39. Martin D. Gould & Julius Bonart, 2015. "Queue Imbalance as a One-Tick-Ahead Price Predictor in a Limit Order Book," Papers 1512.03492, arXiv.org.
  40. Jian Guo & Saizhuo Wang & Lionel M. Ni & Heung-Yeung Shum, 2022. "Quant 4.0: Engineering Quantitative Investment with Automated, Explainable and Knowledge-driven Artificial Intelligence," Papers 2301.04020, arXiv.org.
  41. Claudio Altafini, 2016. "The Geometric Phase of Stock Trading," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-13, August.
  42. Maxime Morariu-Patrichi & Mikko S. Pakkanen, 2017. "Hybrid marked point processes: characterisation, existence and uniqueness," Papers 1707.06970, arXiv.org, revised Oct 2018.
  43. Zihao Zhang & Stefan Zohren & Stephen Roberts, 2018. "DeepLOB: Deep Convolutional Neural Networks for Limit Order Books," Papers 1808.03668, arXiv.org, revised Jan 2020.
  44. Kyle Bechler & Michael Ludkovski, 2017. "Order Flows and Limit Order Book Resiliency on the Meso-Scale," Papers 1708.02715, arXiv.org.
  45. Peng Wu & Marcello Rambaldi & Jean-François Muzy & Emmanuel Bacry, 2021. "Queue-reactive Hawkes models for the order flow," Working Papers hal-02409073, HAL.
  46. Ranjan R. Chakravarty & Sudhanshu Pani, 2021. "A Data Paradigm to Operationalise Expanded Filtration: Realized Volatilities and Kernels from Non-Synchronous NASDAQ Quotes and Trades," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(4), pages 617-652, December.
  47. Wu, Liang & Yan, Xin & Fu, Zhiming & Zhang, Rui, 2019. "Do investors choose trade-size according to liquidity, empirical evidence from the S&P 500 index future market," Finance Research Letters, Elsevier, vol. 28(C), pages 275-280.
  48. Frank Kelly & Elena Yudovina, 2018. "A Markov Model of a Limit Order Book: Thresholds, Recurrence, and Trading Strategies," Mathematics of Operations Research, INFORMS, vol. 43(1), pages 181-203, February.
  49. Mohammad Zare & Omid Naghshineh Arjmand & Erfan Salavati & Adel Mohammadpour, 2021. "An Agent‐Based model for Limit Order Book: Estimation and simulation," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1112-1121, January.
  50. Martin D. Gould & Mason A. Porter & Sam D. Howison, 2015. "The Long Memory of Order Flow in the Foreign Exchange Spot Market," Papers 1504.04354, arXiv.org, revised Oct 2015.
  51. Hugh L. Christensen & Richard E. Turner & Simon I. Hill & Simon J. Godsill, 2013. "Rebuilding the limit order book: sequential Bayesian inference on hidden states," Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1779-1799, November.
  52. Johannes Bleher & Michael Bleher & Thomas Dimpfl, 2020. "From orders to prices: A stochastic description of the limit order book to forecast intraday returns," Papers 2004.11953, arXiv.org, revised May 2021.
  53. Adamantios Ntakaris & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2019. "Mid-price Prediction Based on Machine Learning Methods with Technical and Quantitative Indicators," Papers 1907.09452, arXiv.org.
  54. Kyungsub Lee & Byoung Ki Seo, 2021. "Analytic formula for option margin with liquidity costs under dynamic delta hedging," Papers 2103.15302, arXiv.org.
  55. Thomas Stöckl, 2013. "Price efficiency and trading behavior in limit order markets with competing insiders," Working Papers 2013-11, Faculty of Economics and Statistics, Universität Innsbruck.
  56. Julius Bonart & Martin Gould, 2015. "Latency and liquidity provision in a limit order book," Papers 1511.04116, arXiv.org, revised Jun 2016.
  57. 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.
  58. Saran Ahuja & George Papanicolaou & Weiluo Ren & Tzu-Wei Yang, 2016. "Limit order trading with a mean reverting reference price," Papers 1607.00454, arXiv.org, revised Nov 2016.
  59. Arzandeh, Mehdi & Frank, Julieta, 2017. "The Information Content of the Limit Order Book," 7th Annual Canadian Agri-Food Policy Conference, January 11-13, 2017, Ottawa, ON 253251, Canadian Agricultural Economics Society.
  60. Vasilios Mavroudis & Hayden Melton, 2019. "Libra: Fair Order-Matching for Electronic Financial Exchanges," Papers 1910.00321, arXiv.org.
  61. Gareth W. Peters & Efstathios Panayi & Francois Septier, 2015. "SMC-ABC methods for the estimation of stochastic simulation models of the limit order book," Papers 1504.05806, arXiv.org.
  62. James Wallbridge, 2020. "Transformers for Limit Order Books," Papers 2003.00130, arXiv.org.
  63. Mehdi Arzandeh & Julieta Frank, 2019. "Price Discovery in Agricultural Futures Markets: Should We Look beyond the Best Bid‐Ask Spread?," American Journal of Agricultural Economics, John Wiley & Sons, vol. 101(5), pages 1482-1498, October.
  64. Siikanen, Milla & Kanniainen, Juho & Valli, Jaakko, 2017. "Limit order books and liquidity around scheduled and non-scheduled announcements: Empirical evidence from NASDAQ Nordic," Finance Research Letters, Elsevier, vol. 21(C), pages 264-271.
  65. Ye-Sheen Lim & Denise Gorse, 2020. "Deep Probabilistic Modelling of Price Movements for High-Frequency Trading," Papers 2004.01498, arXiv.org.
  66. James Paulin & Anisoara Calinescu & Michael Wooldridge, 2018. "Understanding Flash Crash Contagion and Systemic Risk: A Micro-Macro Agent-Based Approach," Papers 1805.08454, arXiv.org.
  67. Tucker Hybinette Balch & Mahmoud Mahfouz & Joshua Lockhart & Maria Hybinette & David Byrd, 2019. "How to Evaluate Trading Strategies: Single Agent Market Replay or Multiple Agent Interactive Simulation?," Papers 1906.12010, arXiv.org.
  68. Schnaubelt, Matthias, 2022. "Deep reinforcement learning for the optimal placement of cryptocurrency limit orders," European Journal of Operational Research, Elsevier, vol. 296(3), pages 993-1006.
  69. Schnaubelt, Matthias, 2020. "Deep reinforcement learning for the optimal placement of cryptocurrency limit orders," FAU Discussion Papers in Economics 05/2020, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  70. Jonathan A. Ch'avez-Casillas & Jos'e E. Figueroa-L'opez, 2014. "One-level limit order book models with memory and variable spread," Papers 1407.5684, arXiv.org, revised Mar 2016.
  71. Chávez-Casillas, Jonathan A. & Figueroa-López, José E., 2017. "A one-level limit order book model with memory and variable spread," Stochastic Processes and their Applications, Elsevier, vol. 127(8), pages 2447-2481.
  72. Nikolaus Graf von Luckner & Rüdiger Kiesel, 2021. "Modeling Market Order Arrivals on the German Intraday Electricity Market with the Hawkes Process," JRFM, MDPI, vol. 14(4), pages 1-31, April.
  73. Stefan Palan & Thomas Stöckl, 2014. "When chasing the offender hurts the victim: Collateral damage from insider legislation," Working Paper Series, Social and Economic Sciences 2014-03, Faculty of Social and Economic Sciences, Karl-Franzens-University Graz.
  74. Ye-Sheen Lim & Denise Gorse, 2020. "Deep Recurrent Modelling of Stationary Bitcoin Price Formation Using the Order Flow," Papers 2004.01499, arXiv.org.
  75. Thomas Stöckl, 2014. "Price efficiency and trading behavior in limit order markets with competing insiders," Experimental Economics, Springer;Economic Science Association, vol. 17(2), pages 314-334, June.
  76. Schasfoort, Joeri & Stockermans, Christopher, 2017. "Fundamentals unknown: Momentum, mean-reversion and price-to-earnings trading in an artificial stock market," Economics Discussion Papers 2017-63, Kiel Institute for the World Economy (IfW Kiel).
  77. Weibing Huang & Mathieu Rosenbaum & Pamela Saliba, 2019. "From Glosten-Milgrom to the whole limit order book and applications to financial regulation," Papers 1902.10743, arXiv.org.
  78. Mehdi Arzandeh & Julieta Frank, 2019. "Price Discovery in Agricultural Futures Markets: Should We Look beyond the Best Bid-Ask Spread?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 101(5), pages 1482-1498.
  79. Johannes C. Müller & Sebastian Pokutta & Alexander Martin & Susanne Pape & Andrea Peter & Thomas Winter, 2017. "Pricing and clearing combinatorial markets with singleton and swap orders," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 85(2), pages 155-177, April.
  80. Adamantios Ntakaris & Martin Magris & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2017. "Benchmark Dataset for Mid-Price Forecasting of Limit Order Book Data with Machine Learning Methods," Papers 1705.03233, arXiv.org, revised Mar 2020.
  81. Chiarella, Carl & He, Xue-Zhong & Wei, Lijian, 2015. "Learning, information processing and order submission in limit order markets," Journal of Economic Dynamics and Control, Elsevier, vol. 61(C), pages 245-268.
  82. Masashi Ieda, 2015. "A dynamic optimal execution strategy under stochastic price recovery," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 2(04), pages 1-24, December.
  83. Ingemar Kaj & Mine Caglar, 2017. "A buffer Hawkes process for limit order books," Papers 1710.03506, arXiv.org.
  84. Anatoliy Swishchuk, 2020. "Stochastic Modelling of Big Data in Finance," Methodology and Computing in Applied Probability, Springer, vol. 22(4), pages 1613-1630, December.
  85. Arifovic, Jasmina & He, Xue-zhong & Wei, Lijian, 2022. "Machine learning and speed in high-frequency trading," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
  86. Martin D. Gould & Mason A. Porter & Sam D. Howison, 2015. "Quasi-Centralized Limit Order Books," Papers 1502.00680, arXiv.org, revised Oct 2016.
  87. Zihao Zhang & Stefan Zohren, 2021. "Multi-Horizon Forecasting for Limit Order Books: Novel Deep Learning Approaches and Hardware Acceleration using Intelligent Processing Units," Papers 2105.10430, arXiv.org, revised Aug 2021.
  88. Gould, Martin D. & Hautsch, Nikolaus & Howison, Sam D. & Porter, Mason A., 2017. "Counterparty credit limits: An effective tool for mitigating counterparty risk?," CFS Working Paper Series 581, Center for Financial Studies (CFS).
  89. Mohammad Zare & Omid Naghshineh A. & Erfan Salavati & Adel Mohammadpour, 2021. "An agent-based model and detect price manipulation based on intraday transaction data with simulation," Applied Economics, Taylor & Francis Journals, vol. 53(43), pages 4931-4949, September.
  90. Vasilios Mavroudis, 2019. "Bounded Temporal Fairness for FIFO Financial Markets," Papers 1911.09209, arXiv.org.
  91. Michiel Leur, 2018. "Information and Efficiency in Thin Buyer–Seller Markets over Random Networks," Computational Economics, Springer;Society for Computational Economics, vol. 51(4), pages 1069-1095, April.
  92. Marcello Rambaldi & Emmanuel Bacry & Fabrizio Lillo, 2016. "The role of volume in order book dynamics: a multivariate Hawkes process analysis," Papers 1602.07663, arXiv.org.
  93. Ioane Muni Toke & Nakahiro Yoshida, 2018. "Analyzing order flows in limit order books with ratios of Cox-type intensities," Papers 1805.06682, arXiv.org, revised Aug 2019.
  94. Nino Antulov-Fantulin & Tian Guo & Fabrizio Lillo, 2020. "Temporal mixture ensemble models for intraday volume forecasting in cryptocurrency exchange markets," Papers 2005.09356, arXiv.org, revised Dec 2020.
  95. Thomas Spooner & John Fearnley & Rahul Savani & Andreas Koukorinis, 2018. "Market Making via Reinforcement Learning," Papers 1804.04216, arXiv.org.
  96. 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.
  97. Fabien Guilbaud & Huyen Pham, 2011. "Optimal High Frequency Trading with limit and market orders," Papers 1106.5040, arXiv.org.
  98. Ionel Popescu & Tushar Vaidya, 2019. "Averaging plus Learning Models and Their Asymptotics," Papers 1904.08131, arXiv.org, revised Jul 2023.
  99. Ke Xu & Martin D. Gould & Sam D. Howison, 2019. "Multi-Level Order-Flow Imbalance in a Limit Order Book," Papers 1907.06230, arXiv.org, revised Oct 2019.
  100. Joseph Jerome & Leandro Sanchez-Betancourt & Rahul Savani & Martin Herdegen, 2022. "Model-based gym environments for limit order book trading," Papers 2209.07823, arXiv.org.
  101. Ioane Muni Toke & Nakahiro Yoshida, 2020. "Analyzing order flows in limit order books with ratios of Cox-type intensities," Post-Print hal-01799398, HAL.
  102. Ningyuan Chen & Steven Kou & Chun Wang, 2018. "A Partitioning Algorithm for Markov Decision Processes with Applications to Market Microstructure," Management Science, INFORMS, vol. 64(2), pages 784-803, February.
  103. Masashi Ieda, 2015. "A dynamic optimal execution strategy under stochastic price recovery," Papers 1502.04521, arXiv.org.
  104. Hai-Chuan Xu & Wei Chen & Xiong Xiong & Wei Zhang & Wei-Xing Zhou & H Eugene Stanley, 2016. "Limit-order book resiliency after effective market orders: Spread, depth and intensity," Papers 1602.00731, arXiv.org, revised Feb 2017.
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