Manuel Touyaa's porfotlio of Python projects/assignments for Finance Market Risk.

Simulated 1-day 99% Monte Carlo VaR with Basel III regulatory backtesting

Balance sheet forecasting tool for banks - capital management, liquidity management, and stress testing with Basel III compliance

A credit risk scorecard webapp that lets finance teams and analysts run Basel-compliant loan default predictions.

End-to-end sell-side market-risk engine: VaR/ES across four methods, FRTB Expected Shortfall with liquidity horizons, Basel III vs FRTB capital, Kupiec/Christoffersen backtesting, stress testing and component-VaR attribution.

Regulatory reporting pipeline (LCR Bâle III) built with dbt Core & Snowflake, Medallion architecture, data quality tests, Phase 2: Airflow orchestration

Bob The Judge-Migration Cutover Decision Advisor powered by IBM Bob — IBM Bob Hackathon 2026 CyberFalcon team

A Basel III mortgage capital project comparing STD vs IRB RWA/CET1, using Logistic Regression PD modelling.

An AI-powered credit risk assessment and regulatory compliance platform. Analyzes financial queries and statements using LangChain + FAISS (RAG) and the Claude API, featuring side-by-side prompt tuning comparisons (Zero-Shot, Few-Shot, CoT) and an LLM-as-a-Judge grading rubric.

Calculadora de FPR (Fator de Ponderação de Risco) - Res. BCB 229/2022. Calcula RWACPAD para risco de crédito com suporte completo a todas classes de ativos.

Multi-asset market risk framework: VaR, Expected Shortfall, stress testing, and backtesting across equity, IG/HY credit, and US Treasury instruments.

End-to-end risk analytics platform for retail banking: PD model, IFRS 9 ECL staging, fraud detection (rules + ML), and customer analytics. Built with Python and scikit-learn.

A collection of projects applying mathematical rigor to financial problems, including Basel III Market Risk backtesting, ARIMA-based sales forecasting, and neural networks for credit approval. Developed using Python (TensorFlow, Scikit-learn) and R (astsa, zoo).

Quantitative risk analytics and portfolio construction in Python. Covers Monte Carlo VaR/CVaR (Basel III), Markowitz & Risk Parity optimization, and 20+ quant finance concepts from factor models to backtesting methodology. Built for Quant Risk / ML in Finance roles.

Reference implementation of the BCBS 239 risk-data-aggregation lakehouse pattern on Databricks + Delta Lake + Unity Catalog + dbt-databricks. Portfolio piece, MIT, synthetic data only.

SQL data quality framework and Basel III regulatory calculations for credit risk management

Serverless AWS liquidity risk monitoring system - calculates Basel III LCR and alerts on regulatory breaches

A quantitative framework for modeling Operational Risk Capital under Basel III standards using the Loss Distribution Approach (LDA). Implements Monte Carlo convolution of Poisson frequency and Generalized Pareto (Heavy-Tailed) severity distributions to calculate the 99.9% Value at Risk (VaR).

Built a macro factor risk model using PCA and multi-factor regression on FRED macro variables to decompose returns across equities, bonds, credit, and gold. Estimated factor exposures, systematic risk, and regime-driven stress impacts (rate shock, recession, risk-off) across SPY, TLT, LQD, and GLD.

This notebook demonstrates a multi-period enterprise-wide stress testing (EWST) framework aligned with OSFI ICAAP expectations.