Traditional trading and investing strategies rarely provide institutional investors with risk-adjusted excess return.
Goals and Objectives
This use case improves the outcome of investment decisions and generates excess return compared with the average market performance.
Real-time data and analytics to identify out-performance opportunities, Sophisticated modeling and algorithms for additional diversification, AI, NLP-sourced data (natural language processing)
Use Case Summary
Institutional investors and fund managers parse massive data sets and implement sophisticated investment analytics and algorithms to achieve more alpha (risk-adjusted excess return) and “beat the market.”