Learning QuantConnect - Part III: Universe Selection (Python)
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.
QuantConnect can be a bit of a beast when it comes to complexity. The thing is packed with features and, let's be real, wading through the docs can feel like trying to read hieroglyphics. So in this series I tried to break it down into bite-sized pieces that won't make your head hurt. In this part we will take a look at how to perform Universe Selection for different asset types.
Suggested Reads:
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 are Universes?
Universes are sets of assets that you can use to make trades or for financial analysis. The process of universe selection are the steps to apply different criteria to select assets from the set of available ones.
QuantConnect offers a large diversity of Universes to chose from like Equity, Crypto, Futures, Options and even custom Universes. Dynamic selection of assets, for example the inclusion of assets that were delisted, reduces survivorship bias when backtesting.
Take the emotions out of trading and free up hours of screen time by letting the algorithms do the work for you. Join Algohive and get an exclusive 50% discount on our membership.