openclaw-trading-assistant 2.0.0

OpenClaw Trading Assistant - Technical Analysis & Trading Signals

🚀 OpenClaw Trading Assistant

Version: v1.5.0 (2026-03-26)
Author: OpenClaw Community
License: MIT

📚 Docs Website • Features • Installation • Usage

---

🌐 Language / 语言

Switch to Chinese →

---

---

📖 Introduction

OpenClaw Trading Assistant is a complete trading decision support system that provides technical analysis, trading signals, position management, and risk monitoring.

✨ Key Features

• 📊 Support & Resistance Levels - Automatic calculation with multiple algorithms
• 📈 Trading Signals - Multi-indicator analysis (RSI, MACD, Moving Averages)
• 💰 Position Calculator - Risk-based position sizing
• 🎯 Stop Loss & Take Profit - Price alerts and trigger detection
• ⚠️ Risk Management - Risk/Reward ratio, potential profit/loss
• 🔔 Notifications - Feishu, DingTalk, Email (configurable)

🎯 Perfect For

• Stock/ETF investors
• Technical analysis enthusiasts
• Quantitative trading beginners
• OpenClaw users

---

✨ Features

1. Support & Resistance Levels

• Automatic calculation of key price levels
• Multiple algorithms: Previous High/Low, Moving Averages, Fibonacci, Pivot Points
• Strength indicator (strong/medium/weak)

Example Output:

NVDA Current Price: $175.64
Resistance: $177.26 (+0.9%), $180.00 (+2.5%)
Support: $175.00 (-0.4%), $171.72 (-2.2%)

---

2. Trading Signals

• Multi-indicator analysis (RSI, MACD, Moving Averages)
• Combined signal scoring
• Recommendations: Strong Buy / Buy / Hold / Sell / Strong Sell

Example Output:

RSI: 52.34 [Neutral]
MACD: 0.1234 [Bullish]
Moving Averages: [Bullish]
Combined: Bullish (score: 3)
Recommendation: BUY (Confidence: Medium)

---

3. Position Calculator

• Risk-based position sizing
• Risk profiles: Conservative / Moderate / Aggressive
• Confidence adjustment
• Stop-loss calculation
• Portfolio allocation

Example Output:

Total Capital: $100,000
Entry Price: $175.64
Stop Loss: $165.00
Risk Profile: Moderate

Position: 562 shares ($98,710, 98.7%)
Risk: $5,964 (5.96%)
Risk/Reward: 1:2.0

---

🛠️ Installation

📚 Complete guides: https://xuxuclassmate.github.io/trading-assistant/guides/install-overview/

Quick Comparison

Method	Command	Time
Docker ⭐	docker run -it ghcr.io/xuxuclassmate/trading-assistant:latest	5 min
pip	pip install openclaw-trading-assistant	10 min
npm	npm install -g @xuxuclassmate/openclaw-trading-assistant	10 min
Source	git clone + pip install -e .	15 min

Prerequisites

• Twelve Data API Key (Get Free - 800 calls/day)
• Alpha Vantage API Key (Get Free - 25 calls/day)

🐳 Docker Installation (Recommended)

Pull from GitHub Container Registry:

docker pull ghcr.io/xuxuclassmate/trading-assistant:latest

Pull from Docker Hub:

docker pull xuxuclassmate/trading-assistant:latest

Quick Start:

# Create config directory
mkdir -p trading-assistant-config
cd trading-assistant-config

# Download example config
curl -O https://raw.githubusercontent.com/XuXuClassMate/trading-assistant/main/.env.example
cp .env.example .env

# Edit .env with your API keys
nano .env  # or use your favorite editor

# Run the container
docker run --rm -it \
  -v $(pwd)/.env:/app/.env \
  -v $(pwd)/watchlist.txt:/app/watchlist.txt \
  ghcr.io/xuxuclassmate/trading-assistant:latest \
  --help

Available Images:

• ghcr.io/xuxuclassmate/trading-assistant:1.2.0 - Specific version
• ghcr.io/xuxuclassmate/trading-assistant:latest - Latest stable
• xuxuclassmate/trading-assistant:1.2.0 - Docker Hub (versioned)
• xuxuclassmate/trading-assistant:latest - Docker Hub (latest)

Supported Platforms: linux/amd64, linux/arm64

---

🖥️ CLI Usage

🚀 Quick Start

# Start interactive mode (short & sweet!)
ta

# Full name also works
openclaw-trading-assistant

📋 Available Commands

Command	Example	Description
ta	ta	Start interactive mode / 交互模式
ta sr	ta sr	Analyze support/resistance / 分析支撑阻力位
ta sig	ta sig --symbol NVDA	Generate signals / 生成信号
ta pos	ta pos --symbol NVDA --price 175 --capital 10000	Calculate position / 计算仓位
ta alerts	ta alerts check	Manage alerts / 管理提醒
ta all	ta all	Run all analysis / 运行所有分析
ta v	ta v	Show version / 显示版本
ta h	ta h	Show help / 显示帮助

💡 Examples

Interactive Mode:

$ ta

============================================================
  OpenClaw Trading Assistant CLI
  Version: 1.3.0
============================================================

ta> help
ta> sig
ta> pos --symbol NVDA --price 175.64 --capital 10000
ta> exit

Direct Commands:

ta sr                      # Support/Resistance
ta sig                     # Signals for watchlist
ta sig --symbol NVDA       # Signals for specific stock
ta pos --symbol NVDA --price 175.64 --capital 10000
ta alerts check
ta all                     # Run everything

🐳 Docker CLI Usage

# Interactive mode in Docker
docker run --rm -it \
  -v $(pwd)/.env:/app/.env \
  -v $(pwd)/watchlist.txt:/app/watchlist.txt \
  ghcr.io/xuxuclassmate/trading-assistant:latest

# Direct command in Docker
docker run --rm -it \
  -v $(pwd)/.env:/app/.env \
  -v $(pwd)/watchlist.txt:/app/watchlist.txt \
  ghcr.io/xuxuclassmate/trading-assistant:latest \
  ta sig

---

🌍 Internationalization

Default Language: English (en)

Switch Language:

# Method 1: Environment Variable
export TRADING_ASSISTANT_LANG=zh_CN

# Method 2: In Code
from i18n import set_language
set_language("zh_CN")

# Method 3: Config File
# Add to config.json: {"language": "zh_CN"}

Supported Languages:

• English (en) - Default
• Chinese Simplified (zh_CN)

📚 See I18N Documentation

---

⚙️ Configuration

Required

1. API Keys - Twelve Data & Alpha Vantage
2. Watchlist - Your stock list

Optional

1. Notifications - Feishu, DingTalk, Email (leave empty to disable)
2. Risk Profile - Conservative/Moderate/Aggressive
3. Language - English/Chinese

📚 See Full Configuration Guide

---

📖 Usage

Basic Usage

# Support & Resistance
from support_resistance import calculate_support_resistance
result = calculate_support_resistance("NVDA")

# Trading Signals
from trading_signals import generate_trading_signal
result = generate_trading_signal("AAPL")

# Position Calculation
from position_calculator import calculate_position_size
result = calculate_position_size(
    total_capital=100000,
    entry_price=175.64,
    stop_loss_price=165.00,
    risk_profile="moderate"
)

📚 See Full Usage Guide

---

📁 Project Structure

trading-assistant/
├── config.py                    # Configuration
├── i18n.py                      # Internationalization
├── support_resistance.py        # Support/Resistance (Day 1)
├── trading_signals.py           # Trading Signals (Day 1)
├── position_calculator.py       # Position Calculator (Day 1)
├── stop_loss_alerts.py          # Stop Loss & Take Profit (Day 2)
├── locales/
│   ├── en.json                  # English translations
│   └── zh_CN.json               # Chinese translations
├── data/
│   └── alerts/                  # Alert persistence (JSON)
├── logs/                        # Log files
├── docs/
│   ├── I18N.md                  # i18n documentation
│   ├── CONFIGURATION.md         # Configuration guide
│   ├── PUBLISHING.md            # Package publishing guide
│   └── V1.1.0_SUCCESS.md        # v1.1.0 release summary
├── .github/
│   └── workflows/
│       ├── publish.yml          # Auto-publish workflow
│       └── publish-gh.yml       # GitHub Packages workflow
├── scripts/                     # Utility scripts
├── requirements.txt             # Dependencies
├── pyproject.toml               # Python package config
├── .env.example                 # Environment template
├── watchlist.txt.example        # Watchlist template
├── LICENSE                      # MIT License
├── README.md                    # This file (English)
└── README_zh.md                 # Chinese version

---

🧪 Testing

# Test all modules
python3 support_resistance.py
python3 trading_signals.py
python3 position_calculator.py

# Run unit tests
python3 -m pytest tests/

---

📊 Version History

v1.1.0 (2026-03-24) - Stop Loss & Take Profit Alerts

New Features:

• ✅ Stop Loss & Take Profit alert system
• ✅ Automatic price trigger detection
• ✅ Risk/Reward ratio calculation
• ✅ Potential profit/loss estimation
• ✅ JSON-based alert persistence
• ✅ Detailed logging

Files Added:

• stop_loss_alerts.py - Alert management module
• data/alerts/ - Alert data storage
• logs/ - Log file directory

Usage Example:

from stop_loss_alerts import StopLossAlert, calculate_stop_loss_levels

# Calculate levels
levels = calculate_stop_loss_levels(
    entry_price=175.64,
    stop_loss_percent=5.0,
    take_profit_percent=10.0
)

# Create alert
alert = StopLossAlert("NVDA", 175.64)
alert.create_alert(
    entry_price=175.64,
    stop_loss_price=levels['stop_loss_price'],
    take_profit_price=levels['take_profit_price'],
    shares=100
)

---

v1.0.0 (2026-03-24) - Initial Release

Features:

• ✅ Support & Resistance calculation
• ✅ Trading signal generation (RSI, MACD, MA)
• ✅ Position size calculator
• ✅ Multi-language support (EN/ZH)
• ✅ Configurable notifications
• ✅ Portfolio allocation

📚 See Full Release Notes

---

⚠️ Disclaimer

This software is for educational and research purposes only. It does not constitute investment advice.

• Trading involves substantial risk
• Past performance does not guarantee future results
• Users should make independent decisions and bear their own risks
• The developers are not liable for any investment losses

---

🤝 Contributing

Contributions are welcome! Please feel free to submit issues or pull requests.

---

📚 Documentation

• 📖 README_CLAWHUB.md - Detailed guide
• 🌍 docs/I18N.md - Internationalization guide
• ⚙️ docs/CONFIGURATION.md - Configuration guide
• 📝 CHANGELOG.md - Version history
• ❓ FAQ.md - Frequently asked questions

---

🙏 Acknowledgments

Thanks to these open-source projects:

• OpenClaw - AI assistant framework
• Twelve Data - Financial market data API
• Alpha Vantage - Stock/Forex data API
• ClawHub - OpenClaw skills community

---

📬 Contact

• GitHub: https://github.com/XuXuClassMate/trading-assistant
• Issues: https://github.com/XuXuClassMate/trading-assistant/issues
• ClawHub: https://clawhub.com

---

Made with ❤️ by OpenClaw Community

📖 Documentation • 🐛 Report Issue • ⭐ Star Project

Last Updated: 2026-03-24 14:05 UTC
Version: v1.1.0