 Indecisive algos: Do limit order revisions increase market load?Stephen N. Jurich, Ajay Kumar Mishra and Bhavik Parikh Journal of Behavioral and Experimental Finance, 2020, vol. 28, issue C Abstract: This study examines the behavior of algorithmic and non-algorithmic (human) traders on the National Stock Exchange (NSE) of India around the flash-crash that occurred on October 5, 2012. We analyze the prevalence of orders, cancellations, and modifications by algorithmic and human traders. Over half of the orders in the sample are canceled, while the submitted orders are modified over 15 times. Algorithmic traders dominate over human traders and are more likely to cancel and/or modify their orders in normal market conditions. However, human traders canceled more orders prior to the flash-crash event, whereas algorithmic traders modified their orders. Following the crash event, humans were quick to resume trading, while algorithmic trading increased gradually. Our findings demonstrate behavioral differences between algorithmic and human traders around uncertain periods. Keywords: Order, Revision, Cancellation, Algorithmic traders, Market quality (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:beexfi:v:28:y:2020:i:c:s221463502030335x DOI: 10.1016/j.jbef.2020.100408 Access Statistics for this article Journal of Behavioral and Experimental Finance is currently edited by Michael Dowling and Jürgen Huber More articles in Journal of Behavioral and Experimental Finance from Elsevier |
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