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Proprietary algorithmic traders and liquidity supply during the pandemic

Author

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  • Banerjee, Anirban
  • Nawn, Samarpan

Abstract

This study documents the liquidity-supplying behavior of proprietary algorithmic traders during the abrupt and sustained market decline caused by the COVID-19 outbreak. The findings suggest that these endogenous liquidity providers reduced their supply of liquidity during sustained market stress that lasted several days. Proprietary algorithmic traders showed a greater propensity to trade via market orders, reduced the fraction of contrarian trades, and reduced their share of order book depth compared to other traders during the in-COVID period. Our work provides the first direct evidence of the behavior of proprietary algorithmic traders during the pandemic.

Suggested Citation

  • Banerjee, Anirban & Nawn, Samarpan, 2024. "Proprietary algorithmic traders and liquidity supply during the pandemic," Finance Research Letters, Elsevier, vol. 61(C).
    • Handle: RePEc:eee:finlet:v:61:y:2024:i:c:s1544612324000825
    DOI: 10.1016/j.frl.2024.105052
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Market microstructure; HFT; Liquidity crisis; Passivity;
    All these keywords.

    JEL classification:

    • 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
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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