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

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

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

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

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

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

A full-stack credit risk platform built with FastAPI and React (Vite). Analyzes financial statements via LangChain + FAISS (RAG) and Claude API, featuring side-by-side prompt tuning evaluations and LLM-as-a-Judge grading audits.

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

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.

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

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.

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 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.

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

Credit risk analysis platform for Norwegian companies. CFA-based scoring, ML probability of default, Altman Z-score and Basel III ROE calculator. Built with Python, Streamlit and scikit-learn.

FRTB-aligned VaR & Expected Shortfall risk engine with GARCH volatility modeling, regulatory backtesting, and Streamlit dashboard — built for Swedish equities.