Do the limit orders of proprietary and agency algorithmic traders discover or obscure security prices?
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DOI: 10.1016/j.jempfin.2019.06.003
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Citations
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Cited by:
- Banerjee, Anirban & Roy, Prince, 2023. "High-frequency traders’ evolving role as market makers," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
- NIdhi Aggarwal & Venkatesh Panchapagesan & Susan Thomas, 2022. "When is the Order to Trade Ratio fee effective?," Working Papers 8, xKDR.
- Aggarwal, Nidhi & Panchapagesan, Venkatesh & Thomas, Susan, 2023.
"When is the order-to-trade ratio fee effective?,"
Journal of Financial Markets, Elsevier, vol. 62(C).
- NIdhi Aggarwal & Venkatesh Panchapagesan & Susan Thomas, 2022. "When is the order-to-trade ratio fee effective?," Working Papers 11, xKDR.
- Zijian Shi & John Cartlidge, 2024. "Neural stochastic agent‐based limit order book simulation with neural point process and diffusion probabilistic model," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 31(2), June.
- Ritesh Kumar Dubey & A. Sarath Babu & Rajneesh Ranjan Jha & Urvashi Varma, 2022. "Algorithmic Trading Efficiency and its Impact on Market-Quality," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(3), pages 381-409, September.
- Zijian Shi & John Cartlidge, 2023. "Neural Stochastic Agent-Based Limit Order Book Simulation: A Hybrid Methodology," Papers 2303.00080, arXiv.org.
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More about this item
Keywords
HFT; Limit orders; Quote; Market manipulation;All these keywords.
JEL classification:
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
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