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wrds-data-pull

Extract and integrate WRDS Compustat and CRSP data into quarterly financial-panel datasets.

Updated Feb 1, 2026
Search Tags:#validation#linking#panel-data#wrds#compustat#crsp#data-pull
One-click install
npx skills add https://github.com/Agentic-Assets/Agent-Skills --skill wrds-data-pull
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: wrds-data-pull
Source: https://github.com/Agentic-Assets/Agent-Skills/tree/main/skills/wrds-data-pull
Command: npx skills add https://github.com/Agentic-Assets/Agent-Skills --skill wrds-data-pull

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires wrds, pandas, numpy, pyarrow, statsmodels, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates extraction and integration of WRDS data (Compustat and CRSP) into ready-to-analyze panel datasets, reducing manual data wrangling and saving researchers time.

Core Features & Use Cases

  • Automated data pulls: Retrieve quarterly Compustat and CRSP data from WRDS with caching to speed up repeated analyses.
  • Linking and validation: Uses linking tables to align records across databases, performs date-range validation, and reports data quality.
  • End-to-end workflows: Orchestrates pulling, merging, cleaning, and optional variable construction (e.g., financial ratios) for panel studies.
  • Use Case: A researcher needs a quarter-by-quarter panel of firm fundamentals and stock returns; this Skill builds the dataset and provides diagnostics.

Quick Start

Run the WRDS data-pull pipeline to generate a cleaned, merged Compustat-CRSP dataset and validate it with panel diagnostics.

Frequently Asked Questions about wrds-data-pull

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate pulling and linking Compustat and CRSP data from WRDS into a panel dataset?▼

Automating WRDS data pulls uses Python scripts with the wrds library to retrieve Compustat and CRSP data, apply CCM linking, align calendar quarters, and output a merged, validated financial panel dataset.

What is the best way to link Compustat fundamentals with CRSP stock returns across quarterly panels?▼

Linking Compustat fundamentals with CRSP stock returns requires using CCM linking tables to align records across databases, performing date-range validation, and merging them into a quarter-by-quarter panel dataset.

Does this WRDS data extraction pipeline cache Compustat and CRSP queries for repeated analysis?▼

Yes, the WRDS data extraction pipeline caches Compustat and CRSP query results to speed up repeated analyses and reduce redundant database connections during panel data construction.

Can I construct financial ratios and custom variables after pulling WRDS Compustat and CRSP data?▼

Yes, you can construct financial ratios and custom variables after pulling WRDS data, as the pipeline supports optional variable construction through modular Python components using pandas and numpy.

Do I need a WRDS account and Python libraries like pandas and pyarrow to run this data pull?▼

Yes, you need a valid WRDS account and Python dependencies including wrds, pandas, numpy, pyarrow, and statsmodels to execute the data extraction, linking, and panel validation workflows.

Why does my Compustat-CRSP merged panel data have misaligned dates or missing records?▼

Misaligned dates or missing records in a Compustat-CRSP merged panel often result from incorrect CCM linking or failing to apply calendar-quarter alignment and date-range validation during the data pull.

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