https://github.com/tudororban/alpheast
An event-driven backtesting engine for trading strategies
https://github.com/tudororban/alpheast
backtesting-engine event-driven-architecture trading-strategies
Last synced: 3 months ago
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An event-driven backtesting engine for trading strategies
- Host: GitHub
- URL: https://github.com/tudororban/alpheast
- Owner: TudorOrban
- License: mit
- Created: 2025-06-06T20:05:21.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-06-16T08:19:24.000Z (12 months ago)
- Last Synced: 2025-08-23T00:16:10.921Z (10 months ago)
- Topics: backtesting-engine, event-driven-architecture, trading-strategies
- Language: Python
- Homepage:
- Size: 335 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.md
- Code of conduct: CODE_OF_CONDUCT.md
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README
# AlphEast Backtesting Engine
[](https://alpheast.readthedocs.io/en/latest/?badge=latest)
---
## 🌟 Overview
AlphEast is an event-driven backtesting engine designed for developing and evaluating quantitative trading strategies. While still in its early stages of development, it provides a robust, extensible framework for simulating and evaluating multi-symbol trading strategies with realistic considerations like transaction costs and slippage.
Our goal is to offer a flexible tool for researchers and traders to quickly prototype and test their ideas, without getting bogged down in boilerplate.
---
## 📚 Documentation
For complete usage instructions, API reference, detailed examples, and guides, please visit our official documentation website:
https://alpheast.readthedocs.io/en/latest/
---
## ✨ Key Features
* **Event-Driven Architecture:** Simulates market conditions and trade executions with a clear, sequential event flow.
* **Multi-Symbol Backtesting:** Simultaneously test strategies across multiple financial instruments.
* **Pluggable Strategies:** Easily define and integrate your own custom trading strategies.
* **Customizable Position Sizing:** Implement various position sizing methods to manage risk and allocate capital.
* **Realistic Simulations:** Accounts for transaction costs (commissions) and slippage to provide more accurate results.
* **Performance Metrics & Visualization:** Generates standard trading performance metrics and plots equity curves for quick analysis.
* **Flexible Data Ingestion:** Designed to integrate with various data sources, from direct in-memory data to custom database repositories.
---
## 🚀 Quick Start
Get your first backtest running in minutes!
### Installation
```bash
pip install alpheast
```
### Basic Usage Example
```python
from datetime import datetime
from typing import Dict, List
from alpheast.config.data_source import DataSource, DataSourceType
from alpheast.engine import BacktestingEngine
from alpheast.config.backtest_config import BacktestingOptions
from alpheast.models.interval import Interval
from alpheast.models.price_bar import PriceBar
from examples.basic.example_strategy import ExampleStrategy
if __name__ == "__main__":
symbol = "AAPL"
options = BacktestingOptions(
symbols=[symbol],
start_date=datetime(2021, 1, 1),
end_date=datetime(2025, 1, 1),
interval=Interval.DAILY,
initial_cash=100_000.0
)
price_bar_data: Dict[str, List[PriceBar]] = {
symbol: [] # Provide your data
}
data_source = DataSource(
type=DataSourceType.DIRECT,
price_bar_data=price_bar_data,
)
engine = BacktestingEngine(
options=options,
data_source=data_source,
strategies=[ExampleStrategy(symbol)],
)
results = engine.run()
if results:
results.print_summary()
results.plot_equity_curve()
```
## ⚡️ Performance
AlphEast is designed for efficiency and demonstrates strong scaling characteristics with both the number of symbols and the backtesting duration. Below are some example execution times measured on a standard setup:
### **Execution Time (seconds)**
| Symbols \ Duration | 1 Year | 5 Years |
| :----------------- | :------- | :------- |
| **1** | 0.2124 | 0.9258 |
| **2** | 0.3027 | 1.2424 |
| **10** | 0.9525 | 3.6243 |
## Status
In mid stages of development.
## Contributing
All contributions are warmly welcomed. Head over to [CONTRIBUTING.md](https://github.com/TudorOrban/AlphEast/blob/main/CONTRIBUTING.md) for details.