Welcome to NautilusTrader!

It’s important to note that the API Reference documentation should be considered the source of truth for the platform. If there are any discrepancies between concepts described here and the API Reference, then the API Reference should be considered the correct information. We are working to ensure that concepts stay up-to-date with the API Reference and will be introducing doc tests in the near future to help with this.


The terms “NautilusTrader”, “Nautilus” and “platform” are used interchageably throughout the documentation.

There are three main use cases for this software package:

  • Backtesting trading systems with historical data ( backtest )

  • Testing trading systems with real-time data and simulated execution ( sandbox )

  • Deploying trading systems with real-time data and executing on venues with real (or paper) accounts ( live )

The projects codebase provides a framework for implementing the software layer of systems which achieve the above. You will find the default backtest and live system implementations in their respectively named subpackages. A sandbox environment can be built using the sandbox adapter.


All examples will utilize these default system implementations.


We consider trading strategies to be subcomponents of end-to-end trading systems, these systems include the application and infrastructure layers.


The platform is designed to be easily integrated into a larger distributed system. To facilitate this, nearly all configuration and domain objects can be serialized using JSON, MessagePack or Apache Arrow (Feather) for communication over the network.

Common core

The common system core is utilized by both the backtest, sandbox, and live trading nodes. User-defined Actor and Strategy components are managed consistently across these environment contexts.


Backtesting can be achieved by first making data available to a BacktestEngine either directly or via a higher level BacktestNode and ParquetDataCatalog , and then running the data through the system with nanosecond resolution.

Live trading

A TradingNode can ingest data and events from multiple data and execution clients. Live deployments can use both demo/paper trading accounts, or real accounts.

For live trading, a TradingNode can ingest data and events from multiple data and execution clients. The system supports both demo/paper trading accounts and real accounts. High performance can be achieved by running asynchronously on a single event loop , with the potential to further boost performance by leveraging the uvloop implementation (available for Linux and macOS).

Domain model

The platform features a comprehensive trading domain model that includes various value types such as Price and Quantity , as well as more complex entities such as Order and Position objects, which are used to aggregate multiple events to determine state.

Data Types

The following market data types can be requested historically, and also subscribed to as live streams when available from a data publisher, and implemented in an integrations adapter.

  • OrderBookDelta

  • OrderBookDeltas (L1/L2/L3)

  • Ticker

  • QuoteTick

  • TradeTick

  • Bar

  • Instrument

  • VenueStatusUpdate

  • InstrumentStatusUpdate

The following PriceType options can be used for bar aggregations;

  • BID

  • ASK

  • MID

  • LAST

The following BarAggregation options are possible;




  • HOUR

  • DAY

  • WEEK


  • TICK


  • VALUE (a.k.a Dollar bars)







The price types and bar aggregations can be combined with step sizes >= 1 in any way through a BarSpecification . This enables maximum flexibility and now allows alternative bars to be aggregated for live trading.

Account Types

The following account types are available for both live and backtest environments;

  • Cash single-currency (base currency)

  • Cash multi-currency

  • Margin single-currency (base currency)

  • Margin multi-currency

  • Betting single-currency

Order Types

The following order types are available (when possible on an exchange);