A fast algorithmic trading platform with support for AI based strategies
Project description
Roboquant is an open-source algorithmic trading platform written in Python. It is flexible, user-friendly and completely free to use. It is designed for anyone serious about algo-trading.
So whether you are a beginning retail trader or an established trading firm, roboquant can help you to develop robust and fully automated trading strategies. You can find out more at roboquant.org.
Usage
The following code snippet shows the required steps to run a full back-test on a number of stocks.
import roboquant as rq
feed = rq.feeds.YahooFeed("JPM", "IBM", "F", "TSLA")
strategy = rq.strategies.EMACrossover()
account = rq.run(feed, strategy)
print(account)
Features
Below are some of the key features of roboquant:
- fast back testing and live trading
- AI/ML based strategies
- market data feeds from CSV files, Yahoo Finance, Alpaca and many crypto exchanges
- multi-currency trading
- multi-asset trading, stocks, options, forex and crypto out of the box
- larger-than-memory data feeds
- TaLib based indicators and strategies
- plotting of prices and metrics
- modulair and extensible
Install
Roboquant can be installed like most other Python packages, using tools like uv, pip or conda.
Make sure you have Python version 3.12 or higher installed.
python3 -m pip install --upgrade roboquant
The core installation of roboquant limits the number of dependencies. But you can install roboquant including one or more of the optional dependencies if you require certain additional functionality:
# AI based strategies using PyTorch and SB3
python3 -m pip install --upgrade "roboquant[ai]"
# Integration with Interactive Brokers
python3 -m pip install --upgrade "roboquant[ibkr]"
# Integration with Alpaca broker
python3 -m pip install --upgrade "roboquant[alpaca]"
# Integration many crypto exchanges via CCXT package
python3 -m pip install --upgrade "roboquant[crypto]"
License
Roboquant is made available under the Apache 2.0 license. You can read more about the Apache 2.0 license on this page: https://www.apache.org/licenses/LICENSE-2.0.html
Disclaimer
Absolutely no warranty is implied with this product. Use at your own risk. I provide no guarantee that it will be profitable, or that it won't lose all your money very quickly or does not contain bugs.
All financial trading offers the possibility of loss. Leveraged trading, may result in you losing all your money, and still owing more. Back tested results are no guarantee of future performance. I can take no responsibility for any losses caused by live trading using roboquant. Use at your own risk. I am not registered or authorised by any financial regulator.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file roboquant-2.5.0.tar.gz.
File metadata
- Download URL: roboquant-2.5.0.tar.gz
- Upload date:
- Size: 736.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.11.29 {"installer":{"name":"uv","version":"0.11.29","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"macOS","version":null,"id":null,"libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
76b31b06bda4dbdeff2362c135517e681a5af4ad825424f08cfd06488b080291
|
|
| MD5 |
52ac6db6aa1bc046a9defee1a4ccd40a
|
|
| BLAKE2b-256 |
d46bc52026d7ea7d11c361ef72e4e1dfd577b91353ed0440c07186aa646e9bdf
|
File details
Details for the file roboquant-2.5.0-py3-none-any.whl.
File metadata
- Download URL: roboquant-2.5.0-py3-none-any.whl
- Upload date:
- Size: 759.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.11.29 {"installer":{"name":"uv","version":"0.11.29","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"macOS","version":null,"id":null,"libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
7a9b7f874e02e006adb1b3c8738357964d136182c95ffd499eb39458ee94a55e
|
|
| MD5 |
c4a3b8b2b23cc139cb6e6e0023a9b857
|
|
| BLAKE2b-256 |
11dec846c0dc38297e62b1b09347bbf71b5bedf51d55d8f3888759d419baaf25
|
