WQ-Brain is a Python project for interacting with the WorldQuant Brain platform API, retrieving data fields, generating alpha factors, and running backtests.

• User Authentication: Log in to the WorldQuant Brain platform using your credentials.
• Data Field Retrieval: Fetch data fields in bulk based on various filters (instrumentType, region, delay, universe, etc.).
• Alpha Generation: Automatically generate alpha expressions and payloads from data fields.
• Simulation & Backtesting: Submit simulation jobs and poll for results automatically.

WQ-Brain/
├── brain/
│   ├── AlphaSimulator.py
│   ├── brain1.py
│   ├── brain2.py
│   ├── brain3.py
│   ├── brain4.py
│   └── brain_credentials.txt
├── Alpha_Factory/
│   ├── Alpha Machine Factory.ipynb
│   └── machine_lib.py
└── README.md

• brain1.py
  Minimal end-to-end example: authenticate, submit a single alpha expression (liabilities/assets), poll until completion, and print the result.

• brain2.py
  Refactored workflow: adds functions for authentication, data-field retrieval, alpha list generation, and batch simulations.
  Alpha template: group_rank(({field})/cap, subindustry) applied to all MATRIX-type fields.

• brain3.py
  Robust factor factory: systematic combinatorial alpha generation with multiple operators, lookback windows, and grouping schemes.
  Alpha template: <group_op>(<ts_op>(<field>, <days>), <group>)
  where group ops = {group_rank, group_zscore, group_neutralize},
  ts ops = {ts_rank, ts_zscore, ts_av_diff},
  days = {60, 200}, groups = {market, industry, subindustry, sector, densify(pv13_h_f1_sector)}.
  Also features unified logging, HTTP retries, defensive checks, and periodic re-authentication.

• Python 3.8+
• requests
• pandas

Install dependencies with:

pip install requests pandas

1. Prepare Credentials
   Create a brain_credentials.txt file in the brain/ directory with one of the following formats:

   ["your_username", "your_password"]
   

   or

   {"username": "your_username", "password": "your_password"}
   

2. Run the Main Script
   For example, to run the main workflow:

   python ./brain/brain1.py
   

3. Workflow Overview

   • Authenticate with the platform
   • Retrieve data fields
   • Generate and filter alphas
   • Submit simulations and collect results

• Keep your credentials secure and do not share them.