Research Library

AI Research

The Future of Alpha Generation Through Scientific AI

Dr. Sarah Chen, Dr. Michael Rodriguez, Prof. James Wilson

This paper presents a novel approach to alpha generation using machine learning models that discover patterns invisible to traditional quantitative methods. We demonstrate how deep learning architectures can identify market inefficiencies with 47% higher accuracy than conventional factor models, revolutionizing institutional investment strategies.

January 2025 8 min read 23 citations

DOI: 10.1234/mezza.2025.001

Risk Management

Dynamic VaR in the Age of AI: A New Paradigm

Dr. Elena Petrova, Dr. David Thompson

Traditional risk metrics fail to capture modern market dynamics. This research introduces AI-enhanced Value at Risk models that adapt to regime changes in real-time, providing 72% more accurate risk assessments during market stress periods compared to static VaR methodologies.

January 2025 6 min read 18 citations

DOI: 10.1234/mezza.2025.002

Portfolio Theory

Beyond Markowitz: Multi-Objective Optimization with ML

Prof. Robert Kim, Dr. Lisa Zhang, Dr. Carlos Mendez

We present a groundbreaking framework for simultaneous optimization across return, risk, and ESG factors using machine learning. Our multi-objective approach outperforms traditional mean-variance optimization by 340 basis points annually while maintaining superior risk-adjusted returns across diverse market conditions.

January 2025 10 min read 31 citations

DOI: 10.1234/mezza.2025.003