Rebalance Ep 14: Faster History & Pairs Trading

Rebalance is a weekly flash briefing of new features and updates for you, our QC community. In our 14th episode we’re happy to share:

  1. Faster history requests and documentation updates! We put several new features in production aimed at improving your user experience. Recently our team increased the speed of history requests, added “type-trees” to documentation on alternative data types, and released new documentation on using the Train() method for machine learning strategies.
  2. Symbol helpers for competition tickers! Our second Alpha Streams contest, The Liquid ETF Competition, is accepting submissions through December 22nd! We’ve created symbol helpers to group competition tickers for you. Submit to the Liquid ETF competition here.
  3. An implementation of a stationarity test! In this week’s “From Research to Production”, Jack walks us through two concepts that improve an Alpha’s ability to forecast. He tests for stationarity with the Augmented Dickey-Fuller (ADF) test and normalizes the data based on z-scores. Find the “Research to Production” template using stationarity testing here.
  4. A new Boot Camp on pairs trading! The lesson uses the Algorithm Framework to implement a pairs trading strategy on Pepsi and Coca-Cola. You’ll find the concepts “pair” quite well with this wee’s “Research to Production” topics! Try out the new Boot Camp here.
Sherry Yang

By: Sherry Yang

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