Tutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning
A framework for estimating Basel IV capital requirements.
R Packing Calculating Credit Risk Valuation Adjustments
implementing the SA-CCR based on the CRR2 Regulation
Counterparty credit risk model validation workflow: Pillar I capital, CCAR, IFRS 9 and stress testing on a sample portfolio.
Trading R Package
R package implementing the SA-CCR based on the CRR2 Regulation
Portfolio risk an AI agent can drive and a person can read. Historical VaR and Expected Shortfall, signed linear exposure, explicit stress scenarios, counterparty exposure and XVA through a local ORE project. 4 MCP tools, 5 skills, a local dashboard and a hosted service. Research software, not investment advice. Noncommercial licence.
Institutional Securities Lending, Financing, Repo & Prime Brokerage Trading, Risk Management, Optimization & Decision-Support Engine.
Counterparty Credit Risk for securities financing transactions (SFTs).
Portfolio hub and website for independent financial risk models: SA-CCR, SFTs, CVA, IRRBB behavioural models and FRTB-SA. Explore tools and methods for benchmarking, model challenge, audit, advisory and education.
Wrong-Way Risk (WWR) estimation for counterparty credit risk - a minimal, hexagonal, numpy-only Python library (CVA, alpha multiplier, Hull-White & copula models).
Independent Excel/VBA toolkit for SA-CCR calculation, regulatory benchmarking and validation under CRR and Basel, with reproducible tests, reconciliation and audit evidence.
Extract CSA terms with an LLM, check every answer, and rank human review by the SA-CCR exposure each misread would move.
Excel-based quantitative finance models: Brownian motion simulation, Vasicek short-rate Monte Carlo, and a full Basel SA-CCR counterparty exposure engine.
A simplified Python implementation of SA-CCR, Monte Carlo exposure simulation, collateral, CVA, and wrong-way risk.
Python project simulating counterparty credit risk and margin call workflows using real energy market data.
Counterparty credit risk, xVA and ALM from public data — exposure simulation, SA-CCR, PD scorecards, CVA with wrong-way risk, mortgage prepayment and hedge sizing. Every number in the README traces to the script that produced it.
Counterparty Credit Risk (CVA/PFE) & Regulatory Liquidity (LCR/NSFR) Engine (Python, R, PostgreSQL, Power BI, Excel)
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