Python Library Support – LEAN Release Notes v2.4.0.0

This release adds full python support to enable using common python libraries in your algorithm.It is implemented using the PythonNet library which allows importing C# classes into python and vice versa. The new python algorithms are fully supported in local and cloud trading. There are some minor API adjustments to use the new library but […]


Tracking and Managing Orders

Tracking and managing orders is an important piece of an automated trading strategy. In this video tutorial we demonstrate the QuantConnect API and how to use order management methods in your algorithm.

Consolidating Data to Build Bars

Consolidators are used to combine data together from finer resolutions into larger ones. This can be useful for indicators with specific data requirements or to perform long term analysis in conjunction with short term signals. Consolidators should be constructed and setup in your Initialize() method; this ensures they are only initialized once. There are three […]

Introducing The Co-Pilot: Your Coding Companion

We’re happy to announce the release of the Co-Pilot; a rich automated documentation generator built to give you relevant hints while you’re building your strategy. With deep API’s it is impossible to memorize all the methods available; and time consuming to constantly search the documentation. As a coding companion, the co-pilot can inspect the types […]

How do I use the API File Provider?

Ensuring a high data quality is one of the hardest parts of setting reliable backtesting. There are many challenges to ensuring your data is in the right format, free of errors or omissions and historically accurate. We’ve tried to address this for you by opening the LEAN Data Library and letting you download our data. […]


Our Answer to NYSE Eliminating Stop Orders

From February 26th investors will no longer be able to use Stop or Good Till Cancelled order types on the NYSE, according to a recent press release from Reuters. Typically Stop Market orders are used to place a market order when the stock exceeds a trigger price. On August 24th, 2015 many investors had their […]


The Future of Quant Trading

QuantConnect believes algorithmic, quantitative trading will be the primary investment vehicle of the future, and we plan to be the open source, community driven vehicle which makes this future a reality.
We’re often asked what the differences are between QuantConnect and Quantopian and so we decided to address this question here transparently in a blog. We believe QuantConnect is the only company with the vision and technical ability to execute on the quantitative trading future!

RSI Indicator with Martingale Position Sizing

Martingale is a bet sizing technique for increasing odds of winning at the expense of increased risk. The classic example is a coin flipping game where the gambler doubles his bet if he loses, in the hopes of making back any losses to break even. He will continue doubling his bet through subsequent losses until […]


History of Non-Market Data Correlations

Over the course of the history of the stock market, quantitative observers have built up a comprehensive database of non-market data correlations. From solar flares to hurricane cycles, biota growth and New York City temperature. Figures like Consumer Sentiment data and other broadly distributed survey data have been used by market participants when deciding market […]


Interview with Mebane Faber of Cambria Investment Management

Mebane Faber had a chat with our Growth Hacker Simon Burns on the learning curve in becoming an algorithmic/quant trader, correlating non-market data and the move towards democratization of algorithmic model creation among. Mebane runs a long form qualitative and quantitative analysis blog at Mebane Faber, is the author of Shareholder Yield: A Better Approach […]