Chris R. iAmGiG

Chris Regan

PhD Student | Financial Markets & Machine Learning | Atlanta, GA

Two complementary research threads applying ML to financial market security:

Thread 1: Graph-Based Detection — Gamma-Sieve

Heterophilic GNNs (CARE-GNN, TFE-GNN) detecting fragmented manipulation in options-equity markets
Novel graph schema: 4 node types, 10 edge types for financial transaction networks
Key finding: graph topology detects multi-account coordination (+5.6pp AUC over LSTM), but attack-type-dependent — ensemble required
Domain-shift calibration: 42.5% FPR on real data → 2.4% after fragmentation calibration
ESWA paper in preparation

Thread 2: LLM Market Understanding — gex-llm-patterns

Obfuscation testing methodology for validating LLM understanding of dealer hedging constraints
IEEE BigData 2025 ✅ Published — "Inferring Latent Market Forces: Evaluating LLM Detection of Gamma Exposure Patterns via Obfuscation Testing"
- 2nd International Workshop on Large Language Models for Finance (Macau, December 2025)
- 71.5% detection rate, 91.2% predictive accuracy (242 trading days, 726 evaluations) (arXiv:2512.17923)
AIAI 2026 ✅ Accepted — "Validating LLM Structural Reasoning: Detecting Persistent Market Regimes Through Temporal Obfuscation"
- IFIP International Conference on AI Applications and Innovations, Springer LNCS (camera-ready May 2026)
- 81.2% regime detection 2024 vs 12.1% 2020 (69.1pp separation, φ = 0.672, p < 0.0001), 2,221 evaluations, 0% false positives on controls
JRFM (MDPI) 📄 Under Review — combined journal submission spanning the IEEE BigData methodology and the AIAI multi-day results, plus reviewer-driven additions (full prompt reproducibility, bootstrap CIs, χ² + Fisher contingency tests, threshold sensitivity sweep, Markov-switching benchmark)

Gamma-Sieve — Heterophilic GNN evaluation for adversarial manipulation detection (PhD dissertation)
gex-llm-patterns — LLM pattern detection in gamma exposure analysis (IEEE BigData 2025 published, AIAI 2026 accepted, JRFM under review)
AutoTrader-AgentEdge — Multi-agent trading platform with GEX regime integration
GexVisor — Financial visualization platform for GEX analysis and research tools

ImproveBloodPressureMeasurements ⭐ 9 — ML-based blood pressure measurement accuracy improvement

NLPIntro — Natural language processing exploration
Network-Compression-Analysis — Fast Wavelet Transform compression for neural networks
BotNet Traffic — Botnet traffic detection via federated learning

Primary: Python (99% of work)

Also Proficient: C#, C++, TypeScript, JavaScript, Java

Domains: GNNs, LLMs, Algorithmic Trading, Market Microstructure, NLP, Healthcare ML, Signal Processing

IEEE BigData 2025 ✅ Published — 2nd International Workshop on Large Language Models for Finance (December 2025, Macau, China)
- "Inferring Latent Market Forces: Evaluating LLM Detection of Gamma Exposure Patterns via Obfuscation Testing" (arXiv:2512.17923)
AIAI 2026 ✅ Accepted — IFIP International Conference on AI Applications and Innovations, Springer LNCS (camera-ready May 2026)
- "Validating LLM Structural Reasoning: Detecting Persistent Market Regimes Through Temporal Obfuscation"
JRFM (MDPI) 📄 Under Review — Journal of Risk and Financial Management (submitted March 2026)
- "Validating LLM Structural Reasoning: Detecting Persistent Market Regimes Through Temporal Obfuscation" (combined journal submission of the IEEE BigData methodology and the AIAI regime-detection results)
ESWA (In Preparation) — "Gamma-Sieve: Heterophilic GNN Evaluation for Adversarial Market Manipulation Detection"
PhD Symposium 2025 — Testing LLM Structural Reasoning in Complex Systems

📝 Blog: Post Essentials 📧 GitHub: @iAmGiG

Applying ML to financial market security — from graph topology to language models