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http://hdl.handle.net/11718/27077
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Banerjee, Anirban | - |
dc.contributor.author | Nawn, Samarpan | - |
dc.date.accessioned | 2024-02-05T06:30:37Z | - |
dc.date.available | 2024-02-05T06:30:37Z | - |
dc.date.issued | 2024-01-25 | - |
dc.identifier.issn | 15446123 | - |
dc.identifier.uri | http://hdl.handle.net/11718/27077 | - |
dc.description.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. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.relation.ispartof | Finance Research Letters | en_US |
dc.subject | Market microstructure | en_US |
dc.subject | HFT | en_US |
dc.subject | Liquidity crisis | en_US |
dc.subject | Passivity | en_US |
dc.title | Proprietary algorithmic traders and liquidity supply during the pandemic | en_US |
Appears in Collections: | Journal Articles |
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