Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
Sector concentration checks (max_sector_concentration, sector_limits, sector_exposures), trigger phrases in description, updated methodology docs
What This Skill Does
Connects to the RiskOfficer API to manage investment portfolios and run financial risk analysis. Supports VaR (historical, parametric, GARCH), Monte Carlo simulation, stress testing against historical crises, and portfolio optimization via Risk Parity, Calmar ratio, and Black-Litterman. Also handles ticker search, broker sync, pre-trade checks, and cross-portfolio PnL correlation.
Combines ticker validation, portfolio CRUD, async risk calculations, and multi-method optimization in one API-connected skill, removing the need to run separate quant scripts or manually switch between tools.
When to use it
- Calculate 1-day 95% VaR for a stock portfolio before rebalancing
- Stress test holdings against the 2008 financial crisis or COVID-19 scenario
- Optimize portfolio weights using Black-Litterman with custom return views per ticker
- Run a pre-trade check to catch sector concentration or VaR limit violations before executing
- Measure PnL correlation across multiple brokerage sub-portfolios under normal and crisis regimes
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: What is the 1-day 95% VaR for my main portfolio?
- 1Lists portfolios via GET /portfolios/list to identify the target snapshot ID
- 2Posts a VaR calculation request with method 'historical' and confidence 0.95
- 3Polls GET /risk/calculation/{id} every 2-3 seconds until status is 'done'
- 4Presents VaR, CVaR, Sharpe ratio, and per-position risk contributions
1-day 95% VaR: 3.2% ($32,000 on a $1M portfolio). CVaR: 4.8%. Sharpe ratio: 1.31. Top risk contributor: SBER at 38% of total portfolio risk.
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.