ETFs - Machine Learning-Enhanced Sparse Portfolio Construction

Download this research report to find out more about ML-enhanced portfolio construction approaches that can be used, for example, in the active management of fixed income ETFs. Aimed at investment managers and risk specialists, this study provides a descriptive overview and a quantitative comparison between traditional optimization techniques with supervised or unsupervised machine-learning enhancements. The presented approaches leverage the SS&C Algorithmics simulation-based methodology.