Quantitative stock portfolio optimization by multi-task learning risk and return

• Main Authors: Ma, Yu, Mao, Rui, Lin, Qika, Wu, Peng, Cambria, Erik
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2024
• Subjects: Engineering::Computer science and engineering; Stock Portfolio Optimization; Quantitative Stock Selection
• Online Access: https://hdl.handle.net/10356/173235
• Institution: Nanyang Technological University

Selecting profitable stocks for investments is a challenging task. Recent research has made significant progress on stock ranking prediction to select top-ranked stocks for portfolio optimization. However, the stocks are only ranked by predicted stock return, ignoring the stock price volatility risk...