Credit & company risk
Health, governance, sentiment and default-risk models, including tail-risk-aware approaches.
Explore methodology in contextResearch
Explore credit-risk modeling, Topological Data Analysis, Market Shape and AI for financial markets. Follow the methods and evidence behind QXFin’s financial risk intelligence.
Research & methodology
Health, governance, sentiment and default-risk models, including tail-risk-aware approaches.
Explore methodology in contextTopological Data Analysis, structural market change, regime behavior and interpretation of signals.
Explore methodology in contextDocument intelligence, source-labeled estimates, analyst validation and research synthesis.
Explore methodology in contextPerspectives
Perspectives
A deep-dive into the failure modes of Gaussian default probability models during market stress, and how the q-Gaussian framework captures heavy-tail events more faithfully.
How persistent homology and TDA detect structural fractures in equity market geometry that volatility models systematically miss.
Traditional financial models often miss the "fore-shocks" of a crisis because they assume markets are stable and follow a "normal" pattern. But as any risk manager knows, markets are complex, unpredictable, and rarely follow a straight line.
Techniques for maintaining rigorous credit surveillance on data-sparse private entities using synthetic data generation and alternative signals.
From days to minutes: a walkthrough of how autonomous agents source, reconcile, and structure investment-grade credit memos at scale.
Why supplier concentration, technology dependencies, and regulatory overlaps are the most underpriced risks in modern credit analysis.
Selected research references relevant to QXFin’s analytical methods. Inclusion does not imply QXFin authorship or endorsement.
Academic Publications
Joint research, validation studies, and Enterprise model design begin with a conversation.