What's Stochastix?

Stochastix is a high-performance, open-source quantitative backtesting framework dedicated exclusively to crypto-currencies trading. Engineered in PHP and Symfony, it is designed to provide developers and quantitative analysts with a robust, precise, and extensible environment to build, test, and analyze algorithmic trading strategies.

The framework's primary mission is to enable rigorous, data-driven research by providing tools that ensure simulation realism, computational precision, and deep performance insight.

The Core Principles

Trading strategy development requires rigorous analysis. Stochastix is founded on three fundamental principles that make this possible:

1. Realism: A backtest is only as good as its simulation. Stochastix favors a realistic, event-driven approach that processes data bar-by-bar, handles complex order types natively, and manages portfolio state with precision.
2. Performance: Quantitative analysis involves massive datasets. The framework is architected for speed and memory efficiency, from its custom binary data formats to its use of high-performance PHP extensions, ensuring that your research is not bottlenecked by I/O or processing time.
3. Developer experience: A powerful tool should not be difficult to use. Built on modern PHP and the Symfony framework, Stochastix provides an intuitive, attribute-based system for strategy creation, clear separation of concerns, and a fully automatable command-line interface.

Key Features at a Glance

• Event-driven backtesting engine: Simulates trading on a bar-by-bar basis, providing a realistic environment for strategies that react to market changes as they happen.
• Advanced order management: Native support for Market, Limit, and Stop orders, including automated intra-bar execution of Stop-Loss and Take-Profit levels, partial exits, and programmatic order cancellation.
• Multi-timeframe analysis: Natively request and access secondary timeframes (e.g., 4-hour data within a 1-hour strategy). Data is automatically resampled and aligned with the primary series.
• Comprehensive performance analytics: Go far beyond simple Profit/Loss. The framework automatically generates dozens of institutional-grade summary and time-series metrics, including Sharpe Ratio, Sortino Ratio, Calmar Ratio, CAGR, Max Drawdown, Alpha, and Beta.
• High-performance data formats: Custom binary file formats (.stchx, .stchxi, .stchxm) for storing market data, indicators, and metrics, ensuring minimal storage footprint and maximum read performance.
• Integrated data downloader: A built-in CLI command to fetch high-quality historical OHLCV data from major exchanges via the CCXT library.
• Asynchronous & real-time: Leverages Symfony Messenger and Mercure to run backtests asynchronously while pushing live progress updates to the UI.

Engineered for Performance

Stochastix is meticulously optimized to handle the demands of quantitative research.

Optimized Data Storage: The Binary Formats

Text-based data formats like CSV are inefficient for backtesting. They are slow to parse and consume significant disk space. Stochastix solves this with its own family of binary formats:

• .stchx: For OHLCV market data.
• .stchxi: For indicator time-series data.
• .stchxm: For performance metric time-series data (e.g., equity curve).

These formats provide several key advantages:

• Compact: They use a fraction of the disk space of a comparable CSV file.
• Fast: Data can be read directly into memory without any parsing overhead.
• Efficient: The fixed-size record structure allows for extremely fast time-range lookups using binary search, meaning the engine only reads the data it needs.

Efficient In-Memory Operations: The ds Extension

For operations that occur in memory, such as handling time-series data during a backtest, Stochastix uses the ext-ds PHP extension. The Ds\Vector object provides a more memory-efficient and performant alternative to standard PHP arrays for large, contiguous lists of numerical data, which is precisely what a time-series is.

Designed for Developers

Power and performance are meaningless without a great developer experience (DX).

Intuitive Strategy Creation

Creating a strategy is simple and clean. By extending AbstractStrategy, you gain access to a rich set of helper methods. Strategy metadata and configurable parameters are defined with simple PHP attributes, reducing boilerplate and keeping your code declarative and easy to read.

#[AsStrategy(alias: 'my_strategy', name: 'My Awesome Strategy')]
class MyStrategy extends AbstractStrategy
{
    #[Input(description: 'The period for my indicator.')]
    private int $myPeriod = 20;

    public function onBar(OhlcvSeries $bars): void
    {
        // ... your logic here
    }
}