AI
AQuA: A Bipartite Agentic Framework for Autonomous Quantitative Finance
Researchers from Princeton, Ant Group, and Stanford have introduced AQuA, a two-part agentic framework designed for autonomous factor discovery and model development in quantitative finance. The system addresses the problem of evidence corruption in quantitative research agents, where ineffective "leaky features" can be erroneously validated and propagated in future iterations, a flaw not mitigated by prompt-level instructions or reviewer agents.
Carlos "Emérito" López Lovera
