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      <namePart>Wang, Chao</namePart>
   </name>
   <titleInfo>
      <title>High Frequency Trading and Its Impact on Market Quality in U.S. Futures Market</title>
   </titleInfo>
   <originInfo>
      <dateCreated keyDate="yes">2020</dateCreated>
   </originInfo>
   <note displayLabel="Degree Awarded">Summer 2020</note>
   <typeOfResource authority="aat" valueURI="http://vocab.getty.edu/page/aat/300028029">Dissertation</typeOfResource>
   <name type="corporate">
      <affiliation>Illinois Institute of Technology</affiliation>
   </name>
   <name type="corporate">
      <namePart>SSB / Stuart School of Business</namePart>
   </name>
   <name authority="wikidata" authorityURI="https://www.wikidata.org" valueURI="https://www.wikidata.org/wiki/Q132135224">
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      <namePart>Cooper, Ricky</namePart>
   </name>
   <subject>
      <topic>Management</topic>
   </subject>
   <subject>
      <topic>Finance</topic>
   </subject>
   <subject>
      <topic>Cancel Cluster</topic>
   </subject>
   <subject>
      <topic>Futures</topic>
   </subject>
   <subject>
      <topic>High Frequency Trading</topic>
   </subject>
   <subject>
      <topic>Market Liquidity</topic>
   </subject>
   <subject>
      <topic>Market Microstructure</topic>
   </subject>
   <subject>
      <topic>Price Discovery</topic>
   </subject>
   <language>
      <languageTerm type="code" authority="rfc3066">en</languageTerm>
   </language>
   <abstract>This research focuses on the effects of high frequency trading (HFT) on market liquidity in US futures market. This research utilizes a unique data set consisting of all book events for multiple underlying assets and contracts during calendar year 2018, covering all trading days information of E-mini S&amp;P 500, Gold, Eurodollar, Crude Oil, Corn and Soybean futures with their nearby and deferred contract data each day. This study extends findings from existing HFT equity research (e.g. Brocher et al., 2016; Frino et al., 2019, etc.) that HFT promotes market liquidity, into the commodity market. It also addresses HFT’s contributions to price discovery, and find it varies by types of commodities. Furthermore, the research identifies how an HFT phenomenon, the Cancel Cluster, impacts the futures market. Also, this research verifies and extends the models in Frino et al. (2019) to multiple commodities. Finally, a series of promising future analyses are suggested.</abstract>
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