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Quant Risk Dashboard
by
jason-aka-chen
· GitHub ↗
· v1.0.0
· MIT-0
168
Downloads
0
Stars
1
Active Installs
1
Versions
Install in OpenClaw
/install quant-risk-dashboard
Description
Professional quantitative trading risk management dashboard. Real-time VaR/CVaR calculation, stress testing, position limits, exposure monitoring, drawdown a...
Usage Guidance
This skill appears coherent for running a local risk dashboard and uses standard numeric and visualization libraries. Before installing or running: (1) review the truncated portion of quant_risk.py to ensure there are no network calls, hidden remote endpoints, or code that reads system secrets; (2) run the code in an isolated virtual environment or sandbox and install the listed pip packages into a venv; (3) be cautious when exposing the dashboard port (default 8050) — bind to localhost and firewall appropriately if you do not want external access; (4) note the code uses mock historical returns in the visible portion, so you should provide real market data sources and validate calculations before relying on this in production; (5) if you plan to integrate with a trading system, audit the integration code for any places where credentials or order-execution logic could be sent to or accepted from this skill.
Capability Analysis
Type: OpenClaw Skill
Name: quant-risk-dashboard
Version: 1.0.0
The quant-risk-dashboard skill is a legitimate implementation of a quantitative trading risk management tool. The code in quant_risk.py performs standard financial calculations (VaR, CVaR, Sharpe ratio) using numpy and scipy, and the SKILL.md provides clear, non-malicious instructions for its use. No indicators of data exfiltration, malicious execution, or prompt injection were found.
Capability Assessment
Purpose & Capability
Name/description (quant risk dashboard, VaR/CVaR, stress tests, web UI) match the included SKILL.md usage examples and the quant_risk.py implementation: position management, VaR/CVaR calculations, reporting, and a local web dashboard. The dependencies referenced in SKILL.md (pandas, numpy, scipy, plotly, dash) are appropriate for this functionality.
Instruction Scope
SKILL.md contains concrete usage examples (adding positions, getting metrics, starting a dashboard on localhost) and does not instruct the agent to read unrelated system files, environment secrets, or to transmit data to external endpoints. The code shown implements purely local computations and in-memory state. Note: SKILL.md and the visible source use mock/hypothetical data loaders for historical returns; the truncated portion should be reviewed to confirm it does not add network I/O.
Install Mechanism
There is no registry install spec (skill is instruction-only). SKILL.md suggests installing common Python packages via pip; that is a normal, low-risk developer instruction. No downloads from arbitrary URLs or archive extraction are present.
Credentials
The skill declares no required environment variables, credentials, or config paths. The code does not reference secrets or external service tokens in the provided portion. This is proportionate for a local dashboard library.
Persistence & Privilege
The skill does not request always:true and will not be force-included. It does not modify agent-wide settings or other skills. Autonomous invocation is allowed (platform default) but the skill itself has no elevated persistence or privilege requests.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install quant-risk-dashboard - After installation, invoke the skill by name or use
/quant-risk-dashboard - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of quant-risk-dashboard, a professional risk management dashboard for quantitative trading.
- Real-time VaR/CVaR calculation and stress testing features
- Position limits, exposure monitoring, and drawdown alerts
- Comprehensive risk metrics: volatility, beta, Sharpe/Sortino ratios, and more
- Interactive web dashboard with advanced visualization and reporting tools
- Configurable alerts, custom reporting, and trading system integration
Metadata
Frequently Asked Questions
What is Quant Risk Dashboard?
Professional quantitative trading risk management dashboard. Real-time VaR/CVaR calculation, stress testing, position limits, exposure monitoring, drawdown a... It is an AI Agent Skill for Claude Code / OpenClaw, with 168 downloads so far.
How do I install Quant Risk Dashboard?
Run "/install quant-risk-dashboard" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Quant Risk Dashboard free?
Yes, Quant Risk Dashboard is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Quant Risk Dashboard support?
Quant Risk Dashboard is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Quant Risk Dashboard?
It is built and maintained by jason-aka-chen (@jason-aka-chen); the current version is v1.0.0.
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