Prototype risk modeling simulation for Portfolio using Arbiter.

Reassessment of P2P Credit Risk Modeling with Macroeconomic Factors

A comprehensive guide to designing economically safe ERC-20 tokens using formal invariants and strict permission boundaries. Covers supply caps, fee ceilings, liquidity guarantees, transfer safety, oracle integrity, upgrade control, and economic threat modeling. Focused on real-world DeFi security and robust token design.

A deep exploration of the economic physics governing DeFi crashes, AMM decay, liquidity spirals, and liquidation cascades. This article models decentralized finance as a nonlinear system driven by invariants, thresholds, and feedback loops, revealing why crashes follow predictable laws of motion.

A research-grade lab for stress-testing DeFi protocols using Solidity mini-systems, a Python simulation engine, and a Streamlit dashboard. Simulates price crashes, liquidity shifts, AMM behavior, lending liquidations, and systemic risk dynamics. Designed for DeFi engineers, auditors, and researchers.

A research-grade tool that analyzes Solidity smart contracts for economic vulnerabilities such as unbounded minting, toxic fee mechanisms, liquidity traps, oracle manipulation, centralized control, and broken financial invariants. Focused on economic correctness, incentive risks, and DeFi system stability.

A research-grade framework for forecasting tokenomic gene evolution across market cycles. Analyzes historical gene frequencies, models behavioral drift, and predicts future gene expression using interpretable trend and moving-average forecasting. Designed for tokenomics research, risk analysis, and evolutionary cryptoeconomics.

Implémentation d'un modèle de scoring (OpenClassrooms | Data Scientist | Projet 7)

Statistical modeling and simulation project analyzing optimal betting strategies across multi-game sports series using R.

🚗 A dynamic pricing and insurance risk modeling system using Python, XGBoost, SHAP, and DVC. Predicts claim severity and probability, enabling risk-adjusted premium strategies with full reproducibility and CI/CD.

End-to-End Python econometric pipeline for modeling geopolitical risk in international trade using advanced Bayesian filtering, high-dimensional fixed effects, and split-panel jackknife inference. Replicates Hardwick's (2025) methodology with full robustness testing and automated reporting.

End-to-end Python notebook that engineers a proxy “bad-client” label, explores drivers of credit risk, and builds a leakage-free XGBoost scorecard with threshold tuning and cross-validation.

Ai-powered hurricane risk assessment model combining loads of data regarding social, climate, infrastructure, and meteorology data.

Quantitative analysis of macroeconomic indicators and market volatility for investment strategy development

Independent rapid-options brief outlining rule-based fraud controls, minimum viable safeguards, KPI structures, and scalable deployment pathways for public finance and payment systems.

🌍 Model political distance and trade dynamics using a quantitative framework to enhance understanding of international trade relationships.

Monte Carlo risk modeling tool for utility Transmission & Distribution projects

Credit risk assessment using FICO score segmentation, loan default modeling, discretization techniques, and log-likelihood evaluation for predictive analytics in financial services.

Quantitative analytic toolkit covering natural gas pricing, storage valuation, loan default risk modeling, and credit rating bucketization, with reusable helpers & visual workflows for pricing and risk teams exploring energy and consumer credit data.

High-recall machine learning model to detect SIM swap fraud and system leakage in mobile money transactions.