A sophisticated financial modeling tool for risk parity portfolio optimization and historical backtesting using local market data.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install financial-analysis-skill
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install financial-analysis-skill using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Financial Analysis Skill?
The Financial Analysis Skill is a robust technical solution designed for investment portfolio analysis, risk assessment, and performance evaluation. It specializes in risk parity strategies, allowing users to balance asset weights based on inverse volatility to ensure equal risk contribution across various asset classes like stocks, bonds, and commodities. This tool is a cornerstone for developers building investment tools within the Openclaw Skills ecosystem.
Built with a privacy-first approach, this skill operates entirely on local CSV data, eliminating the need for external API keys or network requests. It integrates advanced rolling window logic and expanding windows to calculate volatility, ensuring that financial models remain realistic by strictly avoiding look-ahead bias during the backtesting process.
Financial Analysis Skill Use Cases
- Evaluating multi-asset portfolio risk profiles and asset allocation efficiency.
- Running historical backtests for risk parity strategies on local China market data or global symbols.
- Automating the generation of monthly rebalancing reports and performance metrics.
- Visualizing correlation heatmaps and return curves for investment reviews.
How Financial Analysis Skill Works
- The skill ingests local CSV files containing historical return data and date information.
- It processes raw data, handling missing values and converting percentage strings into numerical returns.
- Volatility is calculated using an expanding window (minimum 252 trading days) to ensure statistical significance.
- Weights are dynamically assigned using an inverse volatility methodology to achieve risk parity.
- A backtesting engine simulates daily returns and monthly rebalancing based on historical weights.
- The system computes comprehensive performance indicators including Sharpe Ratio, Max Drawdown, and Annualized Returns.
- Detailed visual charts and a text-based summary report are exported to the designated output directory.
Financial Analysis Skill Setup
To utilize this skill within Openclaw Skills, ensure you have Python installed along with the necessary data science libraries:
pip install yfinance pandas numpy matplotlib seaborn plotly
Run the analysis by pointing to your local CSV data source:
python optimized_risk_parity_skill.py --csv "path/to/marketdata.csv" --output ./analysis_results
Financial Analysis Skill Data Schema & Taxonomy
The skill organizes its analysis into several structured formats to ensure data clarity and easy integration:
| Data Type | Format | Description |
|---|---|---|
| Input Data | CSV | Historical daily returns with Date and Symbol columns |
| Portfolio Config | JSON | Key-value pairs of asset symbols and their initial weights |
| Performance Report | TXT | Human-readable summary of returns, risk, and allocation |
| Raw Metrics | JSON | Detailed calculation results for rolling weights and daily returns |
| Visualizations | PNG | Includes return curves, allocation pie charts, and correlation heatmaps |
Financial Analysis Skill Advanced Features
- Expanding window calculations to prevent future data leakage and ensure backtest integrity.
- Monthly dynamic rebalancing logic that adjusts weights based on shifting market volatility.
- Multi-asset support including stocks, bonds, and commodity futures.
- Comprehensive risk analytics including rolling weight change tracking and annualized volatility metrics.
- Local-only execution path for high-security financial data processing within Openclaw Skills.
SKILL.md
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