Learning QuantConnect - Part VIII: Implementing a Mean Reversion Strategy (Python) π
Screenshot: QuantConnect Strategy results
QuantConnect is a powerful open-source, cloud-based platform for algorithmic trading platform. It allows users to design, test, and deploy trading strategies across various financial markets including equities, FX, futures, options, and cryptocurrencies.
Over the past weeks I created tutorials to learn the different basic concepts of QuantConnect, for example how to perform universe selections, how to work with data and indicators and how to place orders.
For me this was a great learning experience, so in this post I wanted to combine all concepts to build a classic Mean Reversion strategy in QuantConnect that has all the bells and whistles from universe selection to risk management.
Suggested Reads:
Learning QuantConnect - Part II: Portfolio, Security Holding & Cashbook
Learning QuantConnect - Part IV: Working with Data and DataSets
Learning QuantConnect - Part VI: Indicators & Candlestick Patterns
This story is solely for general information purposes, and should not be relied upon for trading recommendations or financial advice. Source code and information is provided for educational purposes only, and should not be relied upon to make an investment decision. Please review my full cautionary guidance before continuing
What is QuantConnect?
QuantConnect is an open-source, cloud-based algorithmic trading platform, founded in 2011 by Jared Broad. It allows users to design, test, and deploy trading strategies across various financial markets including equities, FX, futures, options, and cryptocurrencies. The platform caters to a diverse audience ranging from individual traders to hedge funds and brokerages.
The key features of QuantConnect include extensive market data for backtesting strategies, the Lean Algorithmic Trading Engine for local development and customization, and support for Python and C# coding. Additionally, its Alpha Streams feature lets users license their trading strategies to funds. While basic backtesting is free, live trading and advanced features require a subscription.
QuantConnect combines comprehensive data resources, a robust trading engine, and a supportive community, making it a valuable tool for those in the field of quantitative finance and algorithmic trading.
Useful links: