Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/519584
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dc.date.accessioned2023-10-22T05:21:36Z-
dc.date.available2023-10-22T05:21:36Z-
dc.identifier.urihttp://hdl.handle.net/10603/519584-
dc.description.abstractWith the existence of a heterogeneous market compounded by asymmetric information, technology has become one of the major newlineenablers in stock market development. Introduction of algorithms for trading gave a fillip to many stock market participants and allowed them to trade rapidly and profitably. In the present day in Indian stock market, newlinewe have two types of market players; algorithmic traders and nonalgorithmic traders. The algorithmic traders are playing a dominant role in order placement, order modification and order execution while the newlinenon-algorithmic traders still continue to use their intuition. This study aims to understand the trading activity of both the market participants. The study uses the Limit Order Book data from Bombay Stock Exchange. newlineThe LOB data of selected nine stocks is considered for the study whose variables namely Order Added, Order Updated and Order Deleted data along with the Bid Ask Quotes are considered for measurement. Based on newlinethe Limit Orders it is observed that there is a statistically significant difference in the trading behavior of algorithmic and non-algorithmic traders based on stock market session timings and market capitalization. newlineThe market making ability of the algorithmic traders was examined using Order-to trade Ratio and it is observed that large number of orders are not executed indicating that there is no significant Market Making happening. newlineThe algorithmic traders possess an edge over the non-algorithmic traders in Order Modification resulting in dominance in the Stock market. The Mann Kendal Trend test indicates upward and downward trend in newlinevolume adjusted spread indicating that market making is happening especially in the stocks where algorithmic activity is high. This study enables regulatory authorities to monitor stock market activity especially during pre- open session. This study provides sufficient scope for further research on future of algorithmic trading activity and its ramifications on non-algorithmic trading activity in the future.
dc.format.extentxiii, 173p.;
dc.languageEnglish
dc.relation85
dc.rightsuniversity
dc.titleAlgorithmic and non algorithmic trading activity in the bse using limit order book of select stocks
dc.title.alternative
dc.creator.researcherAcharya, Shubhashree P K
dc.subject.keywordAlgorithmic trading,
dc.subject.keywordBusiness Finance
dc.subject.keywordEconomics and Business
dc.subject.keywordMarket Capitalization,
dc.subject.keywordMarket Making.
dc.subject.keywordMarket Session,
dc.subject.keywordNon-Algorithmic Trading,
dc.subject.keywordSocial Sciences
dc.description.note
dc.contributor.guideP S, Anuradha
dc.publisher.placeBangalore
dc.publisher.universityCHRIST University
dc.publisher.institutionDepartment of Commerce
dc.date.registered2016
dc.date.completed2022
dc.date.awarded2022
dc.format.dimensionsA4
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Commerce

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01_title.pdfAttached File182.42 kBAdobe PDFView/Open
02_prelim pages.pdf950.44 kBAdobe PDFView/Open
03_abstract.pdf5.58 kBAdobe PDFView/Open
04_table_of_contents.pdf12.01 kBAdobe PDFView/Open
05_chapter1.pdf403.01 kBAdobe PDFView/Open
06_chapter2.pdf172.06 kBAdobe PDFView/Open
07_chapter3.pdf343.22 kBAdobe PDFView/Open
08_chapter4.pdf1.16 MBAdobe PDFView/Open
09_chapter5.pdf192.95 kBAdobe PDFView/Open
10_annexures.pdf3.54 MBAdobe PDFView/Open
80_recommendation.pdf371.55 kBAdobe PDFView/Open


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