 Stock liquidity and algorithmic market making during the COVID-19 crisisBidisha Chakrabarty and Roberto Pascual Journal of Banking & Finance, 2023, vol. 147, issue C Abstract: Much of the liquidity supply in modern markets comes from algorithmic traders (ATs). Prompted by concerns of fragility induced by such voluntary market making, we examine ATs’ liquidity-provision role during the COVID-19 crisis. We find that amidst the turmoil as market liquidity declined, ATs did not (disproportionately) withdraw liquidity supply. Stocks with the highest algorithmic trading (AT) experienced lower liquidity reduction compared to stocks with the lowest AT activity. High AT stocks did not experience greater reduction in either competition for liquidity provision or price improvements than low AT stocks. Multiple tests indicate that high AT did not associate with any greater deterioration in price efficiency vis-à-vis low AT stocks. Stocks in the industries hardest hit by COVID-19 did not see any less AT competition for liquidity supply or price efficiency than stocks in the least affected ones. Overall, our results allay some concerns that the current levels of AT make markets more susceptible to liquidity withdrawal in times of crises. Keywords: COVID-19; Algorithmic trading; Liquidity; Efficiency; Competition (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:147:y:2023:i:c:s0378426622000152 DOI: 10.1016/j.jbankfin.2022.106415 Access Statistics for this article Journal of Banking & Finance is currently edited by Ike Mathur More articles in Journal of Banking & Finance from Elsevier |
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