Machine learning for financial risk management
A research-grade tool that analyzes Solidity smart contracts for economic vulnerabilities such as unbounded minting, toxic fee mechanisms, liquidity traps, oracle manipulation, centralized control, and broken financial invariants. Focused on economic correctness, incentive risks, and DeFi system stability.
Testing Code abount quantitative finance algorithms
Stress Testing Financial Portfolios using S&P 500 Stock Data from Kaggle.
Independent public-data framework for FICC Treasury-clearing liquidity stress testing and model validation using Federal Reserve data.
Economic applications of the SymC framework. Applies χ ≈ 1 stability principles to market microstructure, distinguishing governed systems (HFT-stabilized) from ungoverned systems (selection-driven). Demonstrates framework universality in human adaptive systems.Retry
Forensic reconstruction of the July 2026 Situational Awareness LP collapse from SEC 13F/13D filings — attribution, a liquidity model validated against a documented forced sale, out-of-sample testing, and a live crowded-trade screen.
Interest rate sensitivity and liquidity stress test model built in Excel to analyze the impact of parallel rate shocks on net interest income and cash position. The model applies scenario analysis with clearly defined assumptions to provide a transparent framework for understanding interest rate and liquidity risk exposure.
Temporal liquidity risk simulation demonstrating threshold failure under synchronised demand
A modular Python engine for banking book ALM, integrating IRRBB, liquidity risk (LCR/NSFR), stress testing, and treasury management actions.
Python + Plotly Dash analytics dashboard for trading floor liquidity, funding, and collateral monitoring. 5,500+ synthetic positions. Docker-ready.
Liquidity Management Tools calibration workflow.
Selected fund risk workflow examples using simulated UCITS and AIFMD-style data, covering liquidity, leverage and LMT mechanics.
Simulation-based EMI risk analytics system analyzing how liquidity stress distorts fraud signal interpretation under statistical detection models (SPI, CSI, Z-score).
A quantitative risk‑modelling toolkit for Lombard lending, providing volatility models, liquidity and concentration adjustments, stress utilities, and a unified haircut/LTV evaluation pipeline.
Python fund risk analytics for AIFM / ManCo workflows, covering leverage, VaR, stress testing, derivatives and liquidity methodology.
[MOVED to Jo2234/finance-labs] Offline market microstructure stress analytics for liquidity, spread, and order-book imbalance signals.
Asymmetric liquidity flow dynamics in financial networks, interpreted via effective geometry and stability under the Victoria-Nash Asymmetric Equilibrium (VNAE).
Treasury decision deck for FX exposure, liquidity monitoring, and scenario-aware finance workflows.
Add a description, image, and links to the liquidity-risk topic page so that developers can more easily learn about it.
To associate your repository with the liquidity-risk topic, visit your repo's landing page and select "manage topics."