Nautilus Trader

Nautilus Trader is a framework allowing quantitative traders to backtest portfolios of automated algorithmic trading strategies on historical data. These same portfolios of strategies can then be hosted on a TradingNode and traded live with with no changes to the TradingStrategy scripts.

Features

• Fast: C level speed and type safety provided through Cython. ZeroMQ message transport, MsgPack wire serialization.
• Flexible: Any FIX or REST broker API can be integrated into the platform, with no changes to your strategy scripts.
• Backtesting: Multiple instruments and strategies simultaneously with historical tick and/or bar data.
• AI Agent Training: Backtest engine fast enough to be used to train AI trading agents (RL/ES).
• Teams Support: Support for teams with many trader boxes. Suitable for professional algorithmic traders or hedge funds.
• Cloud Enabled: Flexible deployment schemas - run with data and execution services embedded on a single box, or deploy across many boxes in a networked or cloud environment.
• Encryption: Curve encryption support for ZeroMQ. Run trading boxes remote from co-located data and execution services.

API Documentation

Installation

To run backtesting research locally install via pip;

$ pip install -U git+https://github.com/nautechsystems/nautilus_trader

Encryption

For effective remote deployment of TradingNode (s) on boxes, encryption keys must be generated by the client trader. The currently supported encryption scheme is that which is built into ZeroMQ being Curve25519 elliptic curve algorithms. This allows perfect forward security with ephemeral keys being exchanged per connection. The public server.key must be shared with the trader ahead of time and contained in the keys\ directory.

To generate new key pairs from a python console or .py run the following;

import zmq
keys = zmq.auth('client.key', '')

Live Deployment

The trader must assemble a directory including the following;

• config.json for configuration settings
• keys/ directory containing the client.key, client.key_secret, server.key
• launch.py referring to the strategies to run
• trading strategy python or cython files

To deploy a live TradingNode, pull and run the latest docker image;

$ docker pull nautilus_trader
$ docker run nautilus_trader -d <path_to_trading_directory>

Development

Development Documentation

To run the tests, first compile the C extensions for the package;

$ python setup.py build_ext --inplace

All tests can be run via the run_tests.py script, or through pytest.

Support

Please direct all questions, comments or bug reports to [email protected]

Copyright (C) 2015-2020 Nautech Systems Pty Ltd. All rights reserved.

https://nautechsystems.io