Please use this identifier to cite or link to this item: https://ir.iimcal.ac.in:8443/jspui/handle/123456789/935
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dc.contributor.authorSyamala, Sudhakara Reddy
dc.contributor.authorWadhwa, Kavita
dc.date.accessioned2021-08-26T05:55:27Z-
dc.date.available2021-08-26T05:55:27Z-
dc.date.issued2020
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85086790810&doi=10.1016%2fj.ribaf.2020.101283&partnerID=40&md5=12d59c2f9e14033d3bddf676db789839
dc.identifier.urihttps://ir.iimcal.ac.in:8443/jspui/handle/123456789/935-
dc.descriptionSudhakara Reddy Syamala, Finance and Control Group, Indian Institute of Management Calcutta, Kolkata, India; Kavita Wadhwa, Indian Institute of Foreign Trade (IIFT), India
dc.descriptionISSN/ISBN - 02755319
dc.descriptionDOI - 10.1016/j.ribaf.2020.101283
dc.description.abstractIn India, National Stock Exchange directly identifies algorithmic trading participation. Algorithmic traders possess intraday market timing skills. Results are not motivated by extreme short-term signals or transitory price trading. Magnitude of market timing performance in cross-sectional group of traders shows that they earn profit across all the cases, and maximize while providing liquidity. Volume-weighted-average-price decomposition analysis reports algorithmic traders earn profits through intraday market timing performance for five-minute and one-minute intervals, and it is higher compared to short-term market timing performance across all trader groups. Order imbalance and price delay regressions show that algorithmic trading significantly improves price efficiency.
dc.publisherSCOPUS
dc.publisherResearch in International Business and Finance
dc.publisherElsevier Ltd
dc.relation.ispartofseries54
dc.subjectAlgorithmic trading
dc.subjectIntraday trading
dc.subjectTrading performance
dc.subjectVWAP
dc.titleTrading performance and market efficiency: Evidence from algorithmic trading
dc.typeArticle
Appears in Collections:Finance and Control

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