Portfolio choice with option implied information (Machine Learning )

  • The increasing pervasiveness of artificial intelligence (AI) and machine learning (ML) technologies has significantly shaped the field of finance, particularly in risk and asset management. ​
  • This research aims to improve the selection of mean variance portfolios with a large number of stocks with option-implied data.​
  • The proposed project will combine machine learning tools (e.g. LASSO) to forecast option returns and utilize the option implied information from the aforementioned forecast .​
  • To support the contribution of this research, a comprehensive literature review will be conducted, focusing on recent studies in AI and finance, especially those employing ML techniques such as LASSO.​