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.

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

Treasury decision deck for FX exposure, liquidity monitoring, and scenario-aware finance workflows.

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

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.

LiquidityVaR

A modular Python engine for banking book ALM, integrating IRRBB, liquidity risk (LCR/NSFR), stress testing, and treasury management actions.

Life-cycle portfolio choice with liquidity risk, labor-income risk, and consumption adjustment frictions. Inspired by Adams (2026).

Asymmetric liquidity flow dynamics in financial networks, interpreted via effective geometry and stability under the Victoria-Nash Asymmetric Equilibrium (VNAE).

A data-driven liquidity risk assessment and cash-flow simulation for a $20M+ highly leveraged real estate PF project, analyzing DSCR and equity runway under occupancy delays.

Mobile-first MRI-based market regime interpretation engine with risk-adjusted confidence modeling.