An advanced equity analysis agent for screening, backtesting, and managing FTSE 350 stock positions with integrated sentiment and risk logic.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install openclaw-lse-trading-agent
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 openclaw-lse-trading-agent 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 LSE Trading Agent?
The LSE Trading Agent is a professional-grade tool built for the London Stock Exchange, providing a robust framework for technical analysis and news-driven sentiment. As a key component of the Openclaw Skills library, it allows users to automate the complex process of screening the FTSE 350 for high-probability setups. By synthesizing multiple data points—including technical indicators, real-time news, and sector-specific trends—it offers a disciplined approach to UK equity trading.
This agent operates through a structured five-layer architecture: data fetching, technical computation, sentiment analysis, decision synthesis, and risk validation. It is designed for traders who require a quantitative edge, ensuring that every recommendation is backed by hard data and validated against strict risk parameters like the half-Kelly criterion and ATR-based stops. Using Openclaw Skills like this helps bridge the gap between raw market data and actionable investment intelligence.
LSE Trading Agent Use Cases
- Scanning the entire FTSE 350 index to identify tickers with the highest composite technical scores.
- Performing deep-dive analysis on specific UK equities using RSI, MACD, Bollinger Bands, and VWAP.
- Conducting LLM-powered sentiment analysis on Yahoo Finance news headlines to gauge market conviction.
- Backtesting trading strategies against 5+ years of historical LSE data including slippage and SDRT costs.
- Managing a paper trading portfolio with automated sector exposure tracking and drawdown alerts.
How LSE Trading Agent Works
- Data Acquisition: The agent utilizes Python-based pipes to fetch live price history and news headlines for LSE tickers.
- Technical Computation: Scripts calculate complex indicators such as EMA crossovers, Bollinger Squeezes, and On-Balance Volume.
- Sentiment Processing: News headlines are aggregated, allowing the agent to provide a qualitative assessment of market mood.
- Composite Scoring: All signals are weighted (Trend 25%, Momentum 25%, Volatility 15%, Volume 15%, Sentiment 20%) to generate a buy/sell score.
- Risk Management: Proposed trades are passed through a risk engine to calculate position sizing and validate against portfolio constraints.
LSE Trading Agent Setup
To get started with this agent in the Openclaw Skills ecosystem, ensure you have the uv package manager installed.
# Install the uv package manager
brew install uv
# List all FTSE 350 tickers
uv run scripts/ftse350.py
# Scan the market for the top 20 opportunities
uv run scripts/screener.py --top 20
LSE Trading Agent Data Schema & Taxonomy
The skill organizes trading data into structured JSON outputs to maintain a clear audit trail and facilitate agent interpretation.
| Data Type | Storage/Format | Key Metrics Included |
|---|---|---|
| Portfolio | data/portfolio.json |
Ticker, shares, entry price, P&L, and GICS sector. |
| Technicals | JSON Pipe | RSI, MACD Signal, Bollinger Position, ATR, and VWAP. |
| Backtest | JSON Output | Sharpe Ratio, Win Rate, Profit Factor, and Max Drawdown. |
| Risk | JSON Validation | Half-Kelly size, ATR stop-loss, and SDRT tax impact. |
LSE Trading Agent Advanced Features
- Intelligent sector exposure tracking to prevent over-concentration in specific GICS categories.
- ATR-based trailing stop-loss calculations to protect capital during volatile market phases.
- Automated inclusion of 0.5% SDRT (Stamp Duty Reserve Tax) and slippage for realistic performance modeling.
- Composite signal logic that prevents trading unless a high-confidence threshold (|score| > 0.4) is met.
- Integrated drawdown circuit breakers that recommend halting trades if portfolio loss exceeds 15%.
SKILL.md
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