Quick Start

This guide will get you up and running with AlphEast in minutes.

Installation

You can easily install AlphEast using pip:

pip install alpheast

Understanding the Engine’s Core Components

To run the BacktestingEngine, you need to provide it with four key components:

  1. Backtesting Options: A BacktestingOptions object specifies core parameters like financial symbols, start and end dates, bar interval, and initial capital. You can provide this in code or by placing an alpheast_config.json file in the root of your project.

  2. Data Source: This defines how the engine gets its historical price data. Data can be provided in three ways:

    Directly:

    Set the price_bar_data property of the DataSource directly with your own pre-loaded data (a PriceBar list).

    Custom Client:

    Implement a custom PriceBarClient that fetches data from your preferred data source.

    Standard Client:

    Use a predefined client implementation (currently, only Alpha Vantage is supported) by providing an API key.

  3. Trading Strategy: An object that implements the BaseStrategy interface. You can use one of the predefined strategies found in alpheast.strategy.common or create your own.

  4. Position Sizing Method: An object that implements the BasePositionSizing interface. Similar to strategies, you can use a predefined method from alpheast.position_sizing.common or define a custom one.

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Basic Usage Example

Here’s a basic example demonstrating how to set up and run a simple backtest with AlphEast:

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 alpheast.strategy.common.sma_crossover_strategy import SMACrossoverStrategy
from alpheast.position_sizing.common.fixed_allocation_sizing import FixedAllocationSizing


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=[SMACrossoverStrategy(symbol)],
    position_sizing_method=FixedAllocationSizing(0.5)
)

results = engine.run()

if results:
    results.print_summary()
    results.plot_equity_curve()