Competition among liquidity providers with access to high-frequency trading technology
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DOI: 10.1016/j.jfineco.2020.11.002
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Citations
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Cited by:
- He, Xue-Zhong & Lin, Shen, 2022. "Reinforcement Learning Equilibrium in Limit Order Markets," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
- Nan Qin & Vijay Singal, 2023. "Effect of high‐frequency trading on mutual fund performance," The Financial Review, Eastern Finance Association, vol. 58(2), pages 369-394, May.
- Irtisam, Rasheek & Sokolov, Konstantin, 2023. "Do stock exchanges specialize? Evidence from the New Jersey transaction tax proposal," Journal of Banking & Finance, Elsevier, vol. 154(C).
- K.C., Bevin & Verma, Ashu, 2023. "Decentralized local electricity market model using Automated Market Maker," Applied Energy, Elsevier, vol. 334(C).
- Banerjee, Anirban & Nawn, Samarpan, 2024. "Proprietary algorithmic traders and liquidity supply during the pandemic," Finance Research Letters, Elsevier, vol. 61(C).
- Ekinci, Cumhur & Ersan, Oğuz, 2022. "High-frequency trading and market quality: The case of a “slightly exposed” market," International Review of Financial Analysis, Elsevier, vol. 79(C).
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More about this item
Keywords
Adverse selection; Liquidity; Latency; Informed trading; Trading technology;All these keywords.
JEL classification:
- D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
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