Raptor: An Investment and Risk Management Project

Raptor is a research project mining diverse alphas in stock markets. Alphas are stock prediction models capturing complex trading signals.

Raptor focus on two research directions:

  • In the first direction, we design novel deep learning models as alphas to increase the prediction accuracy.
  • In the second direction, we design an alpha mining framework, AlphaEvolve, to automatically mine formulaic models and recursive models as alphas.

View our Raptor publication on the ACM Special Interest Group on Management of Data (SIGMOD) 2021:

AlphaEvolve: A Learning Framework to Discover Novel Alphas in Quantitative Investment [paper link]


Steering through complex financial phenomena, we devise various methods to deliver diverse alphas with good performance.

Research Highlights

AlphaEvolve Overview

AlphaEvolve is a framework that automatically mines novel alphas with high returns and low correlations with an existing set of alphas.

Overview of Stock Prediction With Noise Awareness

This work focuses on reducing the contribution of noisy instances caused by missing sources of information in model inputs.




Beng Chin Ooi

Distinguished Professor, Computer Science, School of Computing


Wei Wang

Assistant Professor Computer Science, School of Computing, NUS



Zhaojing Luo

Research Fellow in the Database Systems Research Group at NUS


James Can Cui

PhD Student, NUS School of Computing