Equity

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.

Voya’s Large Cap Value team believes that excess capital yield (ECY) provides a holistic view of the amount of capital a company has available to create value. We apply our ECY framework to evaluate stocks from a relative value perspective and construct a diversified portfolio with a higher yield than the benchmark.

Learn how the economic reboot may revive long-struggling value stocks.

Seeking effective ESG integration that puts alpha over ratings

While today’s retirees are far more exposed to market risks than previous generations, shifting macro trends have rendered some traditional sources of retirement stability less reliable. Rethinking retirement asset allocation should include a high dividend, low volatility equity strategy.

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.

An effective factor investing strategy should be both contextual, that is, able to take into account differences across business segments, and adaptable as markets change over time.

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.  

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.