QuantRocket is a Python-based platform for researching, backtesting, and running automated, quantitative trading strategies. It provides data collection tools, multiple data vendors, a research environment, multiple backtesters, and live and paper trading through Interactive Brokers (IB). It provides scheduling, notification, and maintenance tools to allow your strategies to run fully automated. It allows you to track and analyze your live performance on a strategy-by-strategy basis.
Absolutely! QuantRocket was built from the ground up with global markets in mind and offers first-class support for running your trading strategies on international markets.
QuantRocket users include experienced software developers as well as traders and data scientists who are "quants first, programmers second."
QuantRocket provides turn-key infrastructure and data management tools so that you don't have to be a professional software developer to trade your strategies.
Experienced software developers appreciate QuantRocket's modern, Docker-based stack, cloud integrations, clean APIs, flexibility, and developer-centric workflows.
If you need help, we offer custom development.
The "home base" for interacting with QuantRocket is a web-based Jupyter research environment in which you can view, create, and edit your research notebooks, algorithm files, and configuration files. You can use QuantRocket's Python API within your notebooks and algorithms, or you can open a terminal inside the Jupyter interface and use QuantRocket's command line interface.
The intro video provides a demonstration of the Jupyter environment.
QuantRocket installs on your hardware. This could be your local computer or a server in the cloud.
See the installation guide.
QuantRocket runs anywhere Docker runs: Windows, Linux, or Mac. For Windows users, Windows 10 Professional or higher is required.
Your computer should have at least 8 GB of memory to ensure a good user experience.
See more about system requirements.
It depends on the use case.
An IB account is required in order to collect data from IB or trade with IB. (IB is currently the only supported broker for trading.) QuantRocket offers a top-notch experience for quantitative trading with IB because it is custom-built around IB's strengths and capabilities.
If you plan to use data from providers other than IB and you do not intend to trade or connect to IB, no IB account is required.
QuantRocket connects to IB using IB Gateway, a slimmed-down version of Trader Workstation (TWS) which provides access to the IB API for collecting market data, placing orders, checking your account balance, etc.
IB Gateway is bundled with QuantRocket and doesn't need to be installed separately.
IB offers listings on over 60 global exchanges. With QuantRocket you can trade nearly all of them.
The exchange selector on the account page (login required) shows the approximate number of listings for each exchange.
Please note that, due to restrictions imposed by the exchanges, IB does not provide market data via API for Norway or mainland China stocks, therefore these exchanges are currently unsupported by QuantRocket.
QuantRocket supports equities, futures, currencies, and options. Combos such as futures spreads and option combos are also supported.
You can trade Bitcoin futures on CME. QuantRocket does not support spot cryptocurrency trading.
IB customers can access global end-of-day and intraday data from IB. Subscribe to the relevant market data through IB Client Portal then use QuantRocket to collect the data from IB. Learn much more about IB historical data in the usage guide.
For US stocks, survivorship-bias-free end-of-day price data is available from Sharadar. See pricing.
For IB customers, QuantRocket can collect Reuters global fundamental data from IB and store it in a database for analysis, backtesting, and trading. Learn more in the Reuters Worldwide Fundamentals data guide.
QuantRocket provides a powerful feature set for collecting, querying, and streaming real-time market data from Interactive Brokers. Highlights include:
Learn more in the usage guide.
For futures contracts with a corresponding index, you can also collect data for the index and use it as a stand-in for a continuous futures contract.
Moonshot is a fast, Pandas-based backtester that supports daily or intraday data, multi-strategy backtests and parameter scans, and live trading. It is well-suited for running cross-sectional strategies or screens involving hundreds or even thousands of securities.
Learn more about Moonshot in the usage guide.
Moonshot works with equities, futures, and currencies. For futures, individual contracts or continuous contracts can be used.
Yes, Moonshot supports both intraday and end-of-day strategies.
Live trading with Moonshot can be thought of as running a backtest on up-to-date data and placing a batch of orders based on the latest signals generated by the backtest.
Yes, Moonshot supports walk-forward optimization of machine learning and deep learning strategies. Learn more.
Like Quantopian, QuantRocket is a platform for developing automated, quantitative trading strategies using Python. Like Quantopian, QuantRocket can be used for strategies that screen hundreds or thousands of securities. QuantRocket integrates several open source Python libraries developed by Quantopian, including Zipline, Alphalens, Pyfolio, and QGrid.
Unlike Quantopian, QuantRocket supports live trading and does not run contests or license user-created algorithms for capital allocations. Rather, QuantRocket customers use QuantRocket to trade their own money.
QuantRocket supports backtesting with Zipline. We do not yet support live trading with Zipline but we plan to add this capability in the future.
You can live trade your Quantopian algo by porting it to Moonshot. If you need help, we offer a paid service for porting your Quantopian algo to QuantRocket.
You can use Reuters Worldwide Fundamentals. Check out the Reuters fundamentals data guide page.
Yes, but for large universes of stocks your strategy will need to utilize a bar size larger than 1-minute (for example, 15 or 30 minutes). See the usage guide regarding the total data quantity for intraday strategies in Moonshot.