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Filtering by: Advisor Fossaceca, John Author Sharara, Nasser Ateya Keyword Supervised Machine Learning Type of Work Thesis or Dissertation

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Applying Supervised Machine Learning Models to Classify Day Traders Using the Traders’ Daily Trading Activity Data and the U.S. Stock Market Indices Data

Description:

Some of the U.S. Stock Market trading firms (Firms) have Day Traders (Traders) that use several proprietary strategies that are based on passive - aggressive trading styles. The Traders are classified/grouped, based on their most recent trading profit results, to utilize the proprietary trading...

Author:

Sharara, Nasser Ateya

Keyword:

AI in FinTech, Predicting Traders' Profitability, Traders' Classifications, Artificial Intelligence, and Supervised Machine Learning

GW Unit:

Engineering Management

Degree:

D.Engr.

Advisor:

Fossaceca, John and Islam, Muhammad

Committee Member(s):

Etmadi, Amirhossein, Fossaceca, John, and Islam, Muhammad

Resource Type:

Thesis or Dissertation