
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Corporate Insider Holdings and Analyst Recommendations</dc:title>
  <dc:creator>Gogolak, William Peter</dc:creator>
  <dc:subject>Finance</dc:subject>
  <dc:subject>Management</dc:subject>
  <dc:subject>analyst recommendations</dc:subject>
  <dc:subject>forecasting models</dc:subject>
  <dc:subject>insider stock holding levels</dc:subject>
  <dc:subject>investor relations</dc:subject>
  <dc:subject>top management team</dc:subject>
  <dc:description>I pursued two competing theories about insider stock holding levels and analyst recommendations. The complementary hypothesis states that top management and analysts conduct actions in a comparable manner; the contradicting hypothesis states that insiders and analysts exhibit opposite market actions (Hsieh and Ng, 2019). I examined insider stock holding levels and analyst recommendations. I analyzed a sample of S&amp;P 500 firms from 2011-2020. In this sample, I found that the relationship between insider holding levels and analyst recommendations are opposite in concurrent time periods; thus, supporting the contradictory hypothesis. I also analyzed lagged insider holdings levels in a granger causality test. This test supports the idea that top management stock holdings increase when analysts downgrade stocks, and the opposite effect it true when analysts upgrade stocks. Using a sample of S&amp;P 500 firms from 2011 – 2020, I provided support to my hypothesis that aggregated analyst recommendations forecast future aggregate equity returns. Furthermore, I conducted a test to support my conclusion that changes to insider holding levels should be used to forecast changes in future equity returns, beyond what is already explained by analyst recommendations. I argue two compelling additions that I make to the existing body of work regarding aggregate stock prediction. First, I build upon existing papers by using Bloomberg aggregate analyst recommendations as opposed to the IBES datasets. Second, I expand upon recent index forecasting papers by incorporating both aggregate analyst recommendations and aggregate insider holding levels into aggregate stock return models.</dc:description>
  <dc:contributor>Cai, Li</dc:contributor>
  <dc:contributor>Anand, Smriti</dc:contributor>
  <dc:date>2022</dc:date>
  <dc:type>Dissertation</dc:type>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>islandora:1024852</dc:identifier>
  <dc:identifier>http://hdl.handle.net/10560/islandora:1024852</dc:identifier>
  <dc:source></dc:source>
  <dc:source>Illinois Institute of Technology</dc:source>
  <dc:source>SSB / Stuart School of Business</dc:source>
  <dc:source></dc:source>
  <dc:language>en</dc:language>
  <dc:rights>In
                Copyright</dc:rights>
  <dc:rights>http://rightsstatements.org/page/InC/1.0/</dc:rights>
  <dc:rights>Restricted Access</dc:rights>
</oai_dc:dc>
