🔬 Your Monthly Alpha Lab Deep Dive

Get Python set up, data downloaded, and your backtests running

Welcome to your monthly Alpha Lab deep dive.

At the end of each month, you’ll get a deep dive featuring Python code to backtest and analyze a live trading strategy. Remember, you can also drive the conversation and support topics your way. Create new threads to start conversations about the code, strategies, and topics you care about.

In this month’s deep dive inside PyQuant News Alpha Lab, you’ll set up a production-ready Python research environment for algorithmic trading.

We’ll walk through installing Anaconda, creating a dedicated alpha-lab environment, and setting up the Zipline Reloaded ecosystem (Zipline, PyFolio, Alphalens, Jupyter). You’ll also connect either free Nasdaq Datalink data for quick prototyping or Norgate Data for survivorship‑bias–free, professional backtests.

By the end of this month’s deep dive, you’ll have a fully configured environment and data pipeline ready for institutional‑style backtesting and research.