Manuel Touyaa's porfotlio of Python projects/assignments for Finance Market Risk.
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Updated
Mar 5, 2022 - Jupyter Notebook
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
Multi-asset market risk framework: VaR, Expected Shortfall, stress testing, and backtesting across equity, IG/HY credit, and US Treasury instruments.
A Basel III mortgage capital project comparing STD vs IRB RWA/CET1, using Logistic Regression PD modelling.
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.
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).
FP&A Virtual Experience Program by Citi through Forage
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).
SQL data quality framework and Basel III regulatory calculations for credit risk management
Production-grade Basel III RWA calculation pipeline processing 120M+ records/day with Spark, Airflow, and AWS
Serverless AWS liquidity risk monitoring system - calculates Basel III LCR and alerts on regulatory breaches
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.
Basel III is a global regulatory framework developed by the Basel Committee on Banking Supervision to strengthen bank capital requirements, introduce new liquidity standards, and reduce risk in the financial sector.
Basel III-compliant credit risk models: PD, LGD, EAD estimation with explainability and regulatory validation frameworks
Feasibility analysis of a captive insurance subsidiary for CIBC in the Cayman Islands — whitepaper, presentation, and RISC program infographic.
📊 Model operational risk capital using the Loss Distribution Approach (LDA) and Monte Carlo methods for accurate economic risk assessment.
End-to-end Credit Risk Scorecard development. Implemented Weight of Evidence (WoE) binning and Information Value (IV) analysis for feature selection. Validated via Basel-III standards using Gini and AUC-ROC metrics.
Production-grade credit risk modelling platform — Probability of Default, Loss Given Default, Exposure at Default models, Monte Carlo Value at Risk, Basel III Risk-Weighted Assets, and EBA stress testing. Built with Python, Streamlit, and SQLite.
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