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https://github.com/0xnu/day_trading_agents
ADTA leverages CrewAI and OpenAI's LLM Model for market analysis, signal generation, and risk management—operating strictly during US market hours.
https://github.com/0xnu/day_trading_agents
ai-agents bollinger-bands financial-markets llm macd market market-data money-market rsi
Last synced: about 5 hours ago
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ADTA leverages CrewAI and OpenAI's LLM Model for market analysis, signal generation, and risk management—operating strictly during US market hours.
- Host: GitHub
- URL: https://github.com/0xnu/day_trading_agents
- Owner: 0xnu
- License: bsd-3-clause
- Created: 2024-12-16T17:27:45.000Z (7 days ago)
- Default Branch: main
- Last Pushed: 2024-12-17T23:29:14.000Z (5 days ago)
- Last Synced: 2024-12-18T00:25:54.837Z (5 days ago)
- Topics: ai-agents, bollinger-bands, financial-markets, llm, macd, market, market-data, money-market, rsi
- Language: Python
- Homepage:
- Size: 14.6 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Codeowners: CODEOWNERS
- Security: SECURITY.md
Awesome Lists containing this project
README
## Automated Day Trading Agents (ADTA)
ADTA leverages [CrewAI](https://www.crewai.com/) and OpenAI's [LLM Model](https://platform.openai.com/docs/models/) for market analysis, signal generation, and risk management—operating strictly during US market hours.
> [!WARNING]
> Disclaimer: ADTA provides simulated trading signals for educational purposes only. Real-time trading behaviour may differ. Not intended for actual investment decisions. Consult a qualified financial advisor.
### Features
* Real-time market data collection and validation (WIP; might evolve in the future)
* Technical analysis using RSI, MACD, and Bollinger Bands®
* Risk management and portfolio protection
* Data processing with Polars DataFrames
* Market schedule awareness (9:30 AM - 4:00 PM ET, weekdays only)
* Multi-agent system using CrewAI framework
### Prerequisites
* Python 3.8+
* OpenAI API key
* Required Python packages:
- crewai
- langchain-openai
- polars
- pandas
- numpy
- tqdm
- icecream
- python-dotenv
- pydantic
- requests
### Installation
1. Clone the repository:
```bash
git clone [email protected]:0xnu/day_trading_agents.git
cd day_trading_agents
```
2. Install dependencies:
```bash
## Prerequisites
python3 -m venv .venv
source .venv/bin/activate
uv pip install -r requirements.txt
python3 -m pip install --upgrade pip
## When you finish
deactivate
```
3. Set up environment variables:
```bash
cp .env.example .env
# Edit .env file with your OpenAI and Alpha Vantage API keys
```
### Project Structure
```bash
day_trading_agents/
├── scripts/
│ ├── day_trading_agents.py
│ ├── day_trading_agents_advanced.py
│ └── market_news_agent_terminal.py
├── trading_data/
│ ├── signals/
│ │ ├── csv/ # Polars DataFrame storage
│ │ └── json/ # JSON signal storage
│ └── results/ # Trading session results
├── requirements.txt
└── .env
```
### Debug Mode
Enable debug tracking:
```python
# In scripts/day_trading_agents.py
DEBUG = True # Enables icecream logging
```
Debug features include:
* Configuration validation
* Agent initialisation tracking
* Signal processing progress
* File storage operations
* Exception details
### Market Hours
Disable and bypass market hours:
```python
# In scripts/day_trading_agents_advanced.py
enforce_market_hours=False
```
### Usage
Run the trading system:
```bash
python3 -m scripts.day_trading_agents ## Simple
python3 -m scripts.day_trading_agents_advanced ## Advanced
python3 -m scripts.market_news_agent_terminal ## Market News Terminal
```
The system will:
1. Verify market hours (US Eastern Time)
2. Process each stock with progress tracking
3. Generate and store trading signals
4. Track all operations with debug logging when enabled
### Agents (Simple)
#### MarketDataAgent
Collects and validates real-time market data using GPT-4 Turbo, ensuring data quality and completeness.
#### TechnicalAnalysisAgent
Analyses market data using technical indicators (RSI, MACD, Bollinger Bands®) to generate trading signals with confidence scores.
#### RiskManagementAgent
Evaluates trading signals, manages risk parameters, and provides portfolio protection strategies.
### Data Models
* `Config`: System configuration and parameters
* `StockInfo`: Basic stock information
* `MarketData`: Market data validation model
* `TechnicalSignal`: Technical analysis signals with confidence scores
### Agents (Advanced)
#### MarketDataAgent
Handles real-time market data collection and validation using [Alpha Vantage API](https://www.alphavantage.co/). The agent:
- Retrieves current and historical price data with rate limiting (5 calls/minute)
- Implements caching to minimise API calls (60-second expiry)
- Validates data quality and completeness
- Processes batch requests for multiple stock symbols
- Stores data in both CSV and JSON formats for analysis
#### TechnicalAnalysisAgent
Performs technical analysis using multiple indicators:
- RSI (Relative Strength Index)
- Calculates momentum with 14-period default
- Generates buy signals below 30
- Generates sell signals above 70
- MACD (Moving Average Convergence Divergence)
- Uses 12/26/9 standard periods
- Identifies trend reversals and momentum
- Generates signals based on line crossovers
- Bollinger Bands®
- Implements 20-period moving average with 2 standard deviations
- Generates buy signals at lower band crosses
- Generates sell signals at upper band crosses
#### RiskManagementAgent
Evaluates trading signals and manages portfolio risk:
- Analyses confidence scores for each technical signal
- Monitors signal metadata and technical indicators
- Provides risk assessments based on market conditions
- Generates trade recommendations with risk parameters
- Stores assessment results for future analysis
#### Data Models
##### `Config`: Advanced configuration model with settings:
- API keys for OpenAI and Alpha Vantage (SecretStr for security)
- Model selection and parameters (temperature, max tokens)
- File paths for data and signal storage
- Market hours enforcement flags
- Stock symbol list with descriptions
- Debugging and logging settings
##### `StockInfo`: Detailed stock information model containing:
- Trading symbol
- Company name
- Market sector
- Market capitalisation
- Average trading volume
##### `MarketData`: Market data validation model with temporal features:
- Trading symbol
- Timestamp with timezone awareness
- OHLC (Open, High, Low, Close) prices
- Trading volume
- Data validation status
##### `TechnicalSignal`: Technical analysis signal model:
- Trading symbol and timestamp
- Indicator type (RSI, MACD, Bollinger Bands®)
- Signal value and direction (Buy, Sell, Hold)
- Confidence score (0-1 range)
- Technical metadata dictionary containing:
- RSI values
- MACD line and signal line
- Bollinger Band values (upper, middle, lower)
- Additional indicator-specific data
##### `SignalStorage`: Storage handler for trading signals:
- Structured storage in CSV and JSON formats
- Timestamp-based file organisation
- Historical signal retrieval
- Data persistence and backup
- Signal aggregation and filtering
### Contributing
1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request
### License
This project is licensed under the [BSD 3-Clause](LICENSE) License.
### Citation
```tex
@misc{afoadta2024,
author = {Oketunji, A.F.},
title = {Automated Day Trading Agents (ADTA)},
year = 2024,
version = {2.0.1},
publisher = {Zenodo},
doi = {10.5281/zenodo.14536356},
url = {https://doi.org/10.5281/zenodo.14536356}
}
```
### Copyright
(c) 2024 [Finbarrs Oketunji](https://finbarrs.eu). All Rights Reserved.