Open source analytics and market risk library from OpenGamma
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Updated
Apr 1, 2026 - Java
Open source analytics and market risk library from OpenGamma
Fixed Income Analytics, Portfolio Construction Analytics, Transaction Cost Analytics, Counter Party Analytics, Asset Backed Analytics
Using Bidirectional Generative Adversarial Networks to estimate Value-at-Risk for Market Risk Management using TensorFlow.
Machine learning for financial risk management
Practical, hands-on risk modeling, risk assessment and verifications of risk models across major risk classes and understanding risk regulation as well. Implementing risk models in Python, R and Excel.
Measure market risk by CAViaR model
XQRiskCore is a governance-grade risk control engine for trading — with unified trade approval, structured audit logging, role-based access control, and multi-layer enforcement.
An Excel integration of OpenGamma Strata.
Java SDK providing access to the OpenGamma API
Testing Code abount quantitative finance algorithms
Manuel Touyaa's porfotlio of Python projects/assignments for Finance Market Risk.
Excel bindings for OpenGamma's Strata library
Forecasting the performance of an asset and quantifying the uncertainty associated with such a forecast is a difficult task: one that is frequently made more difficult by a shortage of observed market data. This example illustrates one approach for creating a price forecast based on option price data.
Proposed solutions to selected exercises in the book "Value-at-Risk: Theory and Practice" (2nd edition) by Glyn A. Holton.
Comprehensive financial risk analysis toolkit with Altman Z-Score bankruptcy prediction, Value at Risk (VaR) calculations, and historical crisis stress testing. Supports US & European markets with automated company classification.
Repositório com o código-fonte do Derivativos e Risco de Mercado
Financial risks of bonds
Statistical techniques for Market Risk Modelling (VaR and ES)
A MATLAB implementation of the Adrian-Crump-Moench (ACM) term premium model described in "Pricing the Term Structure with Linear Regressions", Federal Reserve Bank of New York Staff Reports, Staff Report No. 340, April 2013.
Market risk analytics dashboard in Python and Streamlit that computes portfolio volatility, drawdowns, VaR/ES, rolling correlations, and stress tests (shocks + COVID‑style crisis window) for equity/ETF portfolios.
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