首页|New Machine Learning Study Findings Have Been Published by Researchers at Sohar University (Determinates of investor opinion gap around IPOs: A machine learning approach)
New Machine Learning Study Findings Have Been Published by Researchers at Sohar University (Determinates of investor opinion gap around IPOs: A machine learning approach)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on ar tificial intelligence. According to news reporting out of Sohar University by Ne wsRx editors, research stated, “The current study examines the factors influenci ng investor opinions on issues related to listed firms during the first day of I nitial Public Offerings (IPOs), focusing on a sample of 350 fixed-priced IPOs li sted on the Malaysian stock exchange (Bursa Malaysia) from 2004 to 2021.” Our news journalists obtained a quote from the research from Sohar University: “ This research contributes to existing literature by employing various machine le arning methods, which address the limitations of traditional linear regression m odels commonly used in previous studies. Specifically, five methods-extra tree r egressor (ETR), single feature selection (SFS), reverse single feature (RSF), re cursive feature elimination (RFE), and sequential modelling feature adding (SMFA )-are utilized to assess the importance of features in predicting the investor o pinion gap within the dataset. The study’s experiments indicate that these metho ds effectively mitigate noisy data, enhancing their reliability for this type of analysis.”
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