1st Edition
by Emmanuel Jurczenko (Editor)
This groundbreaking book on Machine Learning for Asset Management represents a refreshing collaborative effort between sophisticated investment practitioners and researchers, to present practical application of machine learning methodologies. As one can see from the different chapters, machine learning can be applied to different parts of the investment process, from stock picking to tactical allocation, alpha signal enhancement or trading.
As a result, this comprehensive volume is a powerful tool to help practitioners keep abreast of developments in this fast-changing field, and to implement machine-learning methods into their investment value chain.
The future of asset management will likely involve a synthesis of human and artificial intelligence that harnesses the power of both. However, we need to clearly define the sharing of control between machine and manager. Whereas computers excel in responding to well-formulated questions with clear objectives, humans remain key in asking the right questions and interpreting the results.
