#Risk-analysis
Showing 29 of 29 repositories tagged #risk-analysis, ranked by stars
Agile Threat Modeling Toolkit
Pre-crisis Risk Management for Personal Finance
Smart Algorithms to predict buying and selling of stocks on the basis of Mutual Funds Analysis, Stock Trends Analysis and Prediction, Portfolio Risk Factor, Stock and Finance Market News Sentiment Analysis and Selling profit ratio. Project developed as a part of NSE-FutureTech-Hackathon 2018, Mumbai. Team : Semicolon
A framework for financial systemic risk valuation and analysis.
MONARC - Method for an Optimised aNAlysis of Risks by @NC3-LU
Legal flags a risk. Finance flags another. We connect and cite. Open-source forensic M&A due diligence: 13 AI agents read your data room across 9 domains (Legal, Finance, Commercial, Tech, Cyber, HR, Tax, Regulatory, ESG), cross-reference findings no single reviewer connects, and trace every one to an exact page & quote.
A structured failure-analysis workflow that assumes your plan already failed and works backward to find every reason why. Based on Gary Klein's premortem method (Harvard Business Review), validated by prospective-hindsight research from Wharton and Cornell
applications for risk management through computational portfolio construction methods
"Very simple but works well" Computer Vision based ID verification solution provided by LibraX.
Technical debt and risk analyzer that predicts bug hotspots by combining cognitive complexity, pattern recognition, coverage gaps, information theory, and git history.
QuantLib with AAD
Open-source portfolio analysis tools for DIY investors and finance enthusiasts.
The ISRA security-risk-assessment-tool project is an Electron based application used to do security risk assessments at a technical level
Open-source investment analytics platform bridging academic research and retail finance. Features include portfolio risk decomposition [Fama-French Five Factor Model], retirement sustainability modeling [Block Bootstrap Monte Carlo], max drawdown/CVaR dashboards, and risk-return optimisation [Markowitz, Ledoit-Wolf] via an intuitive user interface.
Artificial Intelligence for Trading
FAIR cyber risk quantification toolkits, agent-based control simulation (FAIR-CAM), threat event frequency estimator (PyPI), LLM classification validator (PyPI), Monte Carlo risk engine with IRIS benchmarks.
A framework for estimating Basel IV capital requirements.
Advanced ML-powered analyzer for hyperliquid.xyz vaults with portfolio optimization and risk analysis. Features include intelligent weight allocation, risk-adjusted return optimization, performance prediction, and comprehensive reporting
A lightweight static analysis engine for Solidity smart contracts. Extracts code features, detects dangerous patterns (delegatecall, tx.origin, call.value), computes heuristic risk scores, and classifies contracts into Low/Medium/High risk levels. Includes multiple example vulnerabilities and a clean CLI for rapid security assessment.
Fast Risks with QuantLib in Python
LSTM neural network predicting price movements of Bitcoin, backtesting and visualisations.
A complete end-to-end fraud detection system for financial transactions, featuring data pipelines, cost-sensitive ML modeling, explainability with SHAP, threshold optimization, batch scoring, and an interactive Streamlit dashboard. Designed to simulate real-world fintech fraud-risk workflows.
A practical, research-friendly toolkit demonstrating how Python can read, parse, and analyze Solidity smart contracts using feature-engineering techniques. Extracts structural and security-relevant signals from Solidity code, detects risky patterns, builds interpretable features, and forms the basis for heuristic or ML-driven security analysis.
Open-source stablecoin risk dashboard tracking peg stability, liquidity, issuer controls, and dependency risk.
A deep exploration of how human psychology shapes fraud behavior and how those patterns become measurable signals in transaction data. This article reveals the behavioral, cognitive, and economic forces behind fraud, explaining how ML models detect deviations, anomalies, and intent hidden within financial transactions.
A research-grade lab for stress-testing DeFi protocols using Solidity mini-systems, a Python simulation engine, and a Streamlit dashboard. Simulates price crashes, liquidity shifts, AMM behavior, lending liquidations, and systemic risk dynamics. Designed for DeFi engineers, auditors, and researchers.
An Excel integration of OpenGamma Strata.
Multi-broker portfolio analytics — Fama-French, GARCH, covered call strategies (PyPI: pip install clawdfolio)
Multi-factor Risk Models of Asset or Portfolio Returns