Quantitative Finance Research Hub

This hub serves as the primary research entry point for modern, ML-driven investment management. It bridges the gap between raw data science and the rigorous causal discovery required for institutional asset allocation.

Ⅰ. Informational NLP & Sentiment Alpha

Focuses on extracting predictive utility from unstructured textual data.

• Sentiment Analysis for Financial Markets — High-fidelity signal processing, Finance-BERT vs. GPT-4o benchmarks, and the MSC Framework (Minimum Sentiment Connectedness).
• Text Analysis with Data Science — Mathematical foundations of text representation (Sparse TF-IDF vs. Dense Transformers).

Ⅱ. Machine Learning & Optimization

Theoretical frameworks for robust portfolio construction and factor discovery.

• Machine Learning for Investing: A Survey — 2026 state-of-the-art survey covering Causal Factor Investing and Scientific Causal Discovery.
• Hierarchical Risk Parity (HRP) — Analytical proofs of noise reduction and overcoming Markowitz's instability.
• Reinforcement Learning Fundamentals — Foundations of sequential decision-making applied to trade execution.

Ⅲ. Risk & Geopolitics

Modeling systemic shocks and supply chain vulnerabilities.

• Geopolitical Risk and Investing — Categorization of shocks (Kinetic vs. Semantic) and conflict-resilient portfolio construction.
• The 2026 Iran War Shock — Case study on the "Correlation Breakdown" and how ML maintained diversification.
• Supply Chain Risk (GNNs) — modeling systemic risk propagation via Graph Neural Networks.

Ⅳ. Foundational Mathematics

The underlying rigorous methods driving the ML layer.

• Topological Data Analysis — Using persistent homology to extract structural features from high-dimensional manifolds.
• TimeSeriesForecasting — Advanced temporal modeling using XGBoost lag features and Walk-Forward Validation.
• Numerical Methods — Engineering continuous reality into finite-precision arithmetic.

See Also

• Operations Research Hub — For the logistics and sequencing math sitting beneath manufacturing and trade.
• Database Performance Monitoring Hub — For the data infrastructure required to feed high-frequency signal pipelines.