Voya’s approach examines the benefits of incorporating alternatives in target date funds by integrating within glide path design critical elements such as risk premia, skill premia and excess returns relative to fees.
Making sense of the massive amounts of ESG inputs with machine intelligence systems.
Learn how the economic reboot may revive long-struggling value stocks.
Voya’s approach examines the benefits of incorporating alternatives in target date funds by integrating within glide path design critical elements such as risk premia, skill premia and excess returns relative to fees.
The breadth and depth of Environmental, Social, and Governance data that investors currently have at their disposal is “a good problem to have”, as it highlights the normative sea-change over the past decade towards a now crucial commitment that companies must make to ESG transparency. Machine learning can help in discerning – and when necessary, creating - signal from noise.
Learn how the economic reboot may revive long-struggling value stocks.
The investment climate has changed dramatically over the last 15 years. The playbook for alpha generation needs to be updated.
In a crowded world where active equity strategies increasingly look alike, machine learning’s potential to deliver genuine differentiation as well as mass-customization make it an invaluable tool for investment managers.
Demystifying the role of machine intelligence in stock selection.
While the phenomenon may seem contained to a handful of stocks, we believe there are broader ramifications for active managers to navigate.
Special needs planning is an emerging issue expected to become critical in the future; today, plan advisors have an opportunity to take the lead in addressing this concern with their clients.
Voya’s Equity Machine Intelligence team aims to take emotion out of the investment process to deliver alpha that is uncorrelated to more traditional equity strategies.