portfolio-risk

Best Multi-Asset Correlation Heatmap & Risk Matrix for MetaTrader 2026

Quantitative geopolitical risk dashboard tracking Iran-Israel conflict escalation via market signals, GDELT news analytics, and probabilistic portfolio regime guidance.

Portfolio Value-at-Risk (VaR) and Conditional VaR (Expected Shortfall) engine calculating tail risk across parametric and historical loss distributions.

Portfolio Value-at-Risk (VaR) and Conditional VaR (Expected Shortfall) engine calculating tail risk across parametric and historical loss distributions.

Finance and accounting workflows for DeepSeek Harness, adapted from Anthropic Finance

本地优先的 A 股研究与投资决策纪律工作台：账户复核、持仓风控、市场观察与盘后研究；不连接券商、不自动交易。

Risk attribution report for portfolio management, using MatLab and Excel

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.

A market state factor based on graph automorphism group analysis. Detects market homogeneity through orbital structure of stock correlation networks, providing signals for risk management and portfolio construction.

Essential techniques to assess financial risks

Repository represents python usability of measuring and managing risks (practice tasks and real cases)

Build a USE4-style (Barra) equity factor risk model from scratch on Sharadar data — specs + a full textbook; you write the code.

Daily exit decisions and greek risk heatmaps for a book of credit spreads, built from your OptionStrat positions.

元启β是一套面向券商、财富管理机构和投顾服务场景的组合风险分析工作台。系统以客户持仓为入口，支持手动录入、Excel/CSV 导入和文本解析，运行压力测试后，可在风险仪表盘中展示组合总市值、Beta、最大回撤、最坏压力损失和关键风险提示。 在情景分析层，系统内置历史情景和假设情景，并支持 AI 根据自然语言生成定制化情景，将客户对宏观、政策、行业或地缘事件的担忧转化为结构化压力测试草稿。风险指标层进一步提供 VaR、CVaR、行业与资产大类暴露、因子与市场敏感性、蒙特卡洛模拟和模型验证。调仓建议层则基于风险优化策略输出调仓前后指标对比、资产配置变化和操作清单。 系统强调“辅助分析、人工确认、合规表达”，适合用于投顾服务提效、客户风险沟通、投资者教育和机构内部产品演示。

Calculate VaR of Tesla Equity share with Historical, Variance-Covariance and MonteCarlo simulations methods

Quantitative analysis techniques with Python and Pandas to determine which portfolio is performing best across many areas: volatility, returns, risk, and Sharpe Ratios.

Multi-asset market risk terminal — parametric & historical VaR, component/marginal VaR decomposition, stress testing and an SMA×R:R grid-search backtester. Streamlit.

Quantitative risk infrastructure for Meridian Private Bank. Three Monte Carlo methods - LHS for venture valuation, scenario-based correlated simulation for macro stress testing, and historical simulation for LP reporting. Calibrated against Q1 2026 Iran war oil shock.

Decimal-only, exchange-neutral pre-trade sizing and portfolio risk gates.

Fixed-income portfolio risk framework covering bond pricing, duration, convexity, DV01, key-rate duration, yield-curve stress testing and hedge optimization.