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Comparing Open-Source Trading Platforms and Research Setups

Article Quant Q&A · Author: Datageek

Summary

The document surveys algorithmic trading platforms and tools, including hosted research environments, open-source backtesting engines, and locally assembled development stacks. It describes Quantopian and Zipline as Python-centered research and backtesting tools, and Lean as an event-driven system with support for multiple languages, asset classes, and trading frictions such as costs and margin. Other replies mention additional projects and crypto bots, but mostly as brief suggestions rather than evaluated alternatives.

The discussion highlights practical selection criteria: programming-language fit, data resolution and coverage, asset support, execution realism, extensibility, and the ability to use custom libraries. Contributors disagree about whether hosted platforms offer enough flexibility for professional research, while one recommends building a local environment. The material is a dated, crowdsourced overview, not a controlled comparison; several claims come from platform contributors or users, and availability and capabilities may have changed. It offers starting points and tradeoffs, but no standardized performance or reliability evidence.

Key ideas

  • Trading research platforms vary in language support, asset coverage, data resolution, and backtesting architecture.
  • Zipline is presented as an open-source backtesting engine associated with a Python research environment.
  • Lean is described as an event-driven framework that models trading constraints and supports several languages and asset classes.
  • A local research setup can offer more control over libraries and data than a hosted platform.
  • The platform descriptions are anecdotal and dated, with no standardized comparison of accuracy or reliability.

Tags

Full text
# What open source trading platform are available


# What open source trading platform are available












I would like to compile a list of open source trading platforms. Something that would give an overview and comparison of different architectures and approaches.

## Answer by Andrew Campbell (score 26)

https://quant.stackexchange.com/a/16214

Definitely check out Quantopian and Zipline.

Quantopian provides a free research environment, backtester, and live trading rig (algos can be hooked up to Interactive Brokers). The algorithm development environment includes really handy collaboration tools and an open source debugger. They provide tons of data (even Morningstar fundamentals!) free of charge.

Quantopian's platform is built around Python and includes all the open source goodness that that the Python community has to offer (Pandas, NumPy, SciKitLearn, iPython Notebook, etc.)

Successful live traders will be offered spots in the Quantopian Managers Program, a crowd-sourced hedge fund.

Zipline is the open source backtesting engine powering Quantopian. It provides a large Pythonic algorithmic trading library that closely approximates how live-trading systems operate.

(full disclosure: I work at Quantopian)

## Answer by JaredBroad (score 16)

https://quant.stackexchange.com/a/18161

QuantConnect provides an open-source, community-driven project called Lean. The project has thousands of engineers using it to create event-driven strategies, on any resolution data, any market, or asset class.

Our system models margin leverage and margin calls, cash limitations, transaction costs. We maintain a full cashbook of your currencies. It's about as close to reality as possible. It's 20x faster than Zipline and runs on any asset class or market. We provide tick, second or minute data in Equities and Forex for free.

QuantConnect supports Python, C#, and F#

I'm a founder @ QuantConnect

January 2017: We now offer intraday Options, Futures, Forex, CFD, and US Equities backtesting through QuantConnect.com

October 2017: We have added crypto trading on GDAX.

April 2018: We have created a modular algorithm framework; separate algorithm components that can be plugged together for rapid algorithm development.

Jan 2019: Launched an Alpha Marketplace, with submissions from quants around the world.

July 2020: We broke apart the platform into services like AWS. Allowing you to spin up different parts of our platform and only pay for what you use.

August 2020: We added L1-Spread data and fill models for equities backtesting.

December 2020: We added future-options support.

January: 2021: Deployed cloud-optimization to test parameter sensitivity.

February 2021: Opened our alpha market place to all investors containing hundreds of strategies with SR >1.

## Answer by Datageek (score 5)

https://quant.stackexchange.com/a/10906

List of links/projects I stumbled upon while doing the research:

- Open Source Trading Platforms (might be outdated)

## Answer by AlgoTrader7869 (score 5)

https://quant.stackexchange.com/a/21407

As a beginner in AlgoTrading QuantConnect and Quantopian are great for practice and improving your skills but for a serious Algo Trader , they are basically useless. An Algo Trader requires flexibility to investigate trading ideas and add or remove libraries or parts of the system that do not work. You need to automatically and constantly reevaluate your systems . At this level of trading , Quantopian and Quantconnect are very rigid and completely not capable. May be in a few years they will be at a level where implementing new trading ideas with more advanced libraries is possible. This two startups are looking for money , plain and simple. If you have been developing algos that are actually profitable and you are in know in the trading industry. if you have worked with the Big boys, Hedge funds, HFT firms, and Trading firms you will know why i say this. Just be careful do not put all your eggs in one basket

## Answer by user16907 (score 4)

https://quant.stackexchange.com/a/23224

QuantConnect and Quantopian were the first algorithmic trading platforms that became available and they are the most advanced (even though they need a lot more work for a professional trader, they are a good starting point).

This is an emerging market, lots of startups are rising. Nowadays new platforms are available, for example:

- www.cloud9trader.com

- alta5.com

- quantiacs.com

Every platform has is own characteristics, but all in all they are all work in progress. it will take few more years before being able to have a stable trading platform that you can rely on and that offers all you need for professional trading.

## Answer by Theodore (score 3)

https://quant.stackexchange.com/a/39959

It depends on either the language(s) you know or which languages you wish to learn.

Python is a must, and the two major platforms I know of (Quantopian and Quantconnect) offer support for Python. In fact, a vast majority of the trading algorithms on the forums and discussions are in Python. This is especially the case given Quantopian only has support for Python and nothing else, Quantconnect however offers support C# and F# as well. In my experience, Quantconnect has been better as they offer the language closest to what I know the best (that language being C# and the one I am good at being C++), plus they offer higher resolution data for various asset classes (they not only have equities and futures, but options, forex and cryptocurrencies). They offer tick level data for crypto, equities, forex and futures. This was not an advertisement for Quantconnect however... I do not even use it.

For work I do in Python, I use a Jupyter notebook running locally on my computer. Libraries I use for Python primarily are

- Pandas

- NumPy

- SciPy

- Scikit-learn

- ARCH

- PyFlux

- TensorFlow (rarely)

In C++, which is where I do most of my work, since I'm into high frequency trading, I use Quantlib which is mostly useful for coming up with derivatives pricing models, as well as Armadillo, the GNU Scientific Library (GSL), the GNU linear programming kit (GLPK), and TaLib (technical analysis library).

I use Vim C++ for whatever that's worth and I would urge you to invest in cultivating your own environment for research because if you are really planning on doing real research and thorough backtesting, you are going to need a lot more flexibility with respect to libraries and the data being utilized.

## Answer by Pam (score 2)

https://quant.stackexchange.com/a/14007

Can take a look the other pointers from wikipedia http://en.wikipedia.org/wiki/Algorithmic_trading

Another list is here: http://algotradingindia.blogspot.it/2012/05/open-source-trading-platforms-list.html

For hedge funds there is a famous top solution publicly available (referenced by wiki), but not "open source". ("Open source" stuff is usually put around by enthusiasts with no clue about real algo trading.)

## Answer by Kevin Parker (score 1)

https://quant.stackexchange.com/a/24635

There's this one written by me a few years back called autoStock. Worth taking a look.

https://github.com/expresspotato/autoStock

## Answer by Roberto (score 1)

https://quant.stackexchange.com/a/31823

Still in early stages but if you can code in Java / Python this might be worth taking a look: https://github.com/melphi/algobox

## Answer by poordeveloper (score 0)

https://quant.stackexchange.com/a/43005

OpenTrade An open source OEMS, and algorithmic trading platform in modern C++

## Answer by AI Quant (score 0)

https://quant.stackexchange.com/a/54609

If you only like to use methods of technical analysis in java, here is a good code to read: algorithmic trading in java

## Answer by BrunoS (score -1)

https://quant.stackexchange.com/a/40948

FreqTrade Bot is excelent option right now.

Still under heavy development and in early stages but has lots of features and could quickly put a strategy to test in the cryptocurrency makets, connected with CCXT library.

## Answer by babelproofreader (score -1)

https://quant.stackexchange.com/a/42711

On GNU/Linux (and hence other Unix-like systems) you could use Qtstalker, which "...is 100% free software, distributed under the terms of the GNU GPL."

## Answer by Vivek Kathiriya (score -2)

https://quant.stackexchange.com/a/29757

I think you have to check http://www.modulusfe.com/products/ for a high frequency trading solution with open source code.

## Answer by Dave08 (score -4)

https://quant.stackexchange.com/a/42018

What about the API OANDA as trading API?

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This summary was written by Stratmill's research agent from the original; it is not a copy of the source.