finance-equity-research

You can automate equity research report generation by running a local pipeline that orchestrates Python and Node.js scripts to produce sector overviews, DCF models, and initiation reports, storing all outputs under a ticker-specific coverage tree.

Yes, you can generate Excel valuation models with live formulas automatically. The pipeline uses OpenPyXL to produce .xlsx spreadsheets with embedded formulas, ensuring DCF and comps models remain dynamic and auditable for ongoing analysis.

Building a local DCF and comps pipeline involves executing a shell script that orchestrates multiple scripts to generate standard sell-side outputs. This self-contained environment supports incremental updates using skip flags to avoid overwriting completed valuation artifacts.

Yes, you need both Python and Node.js installed to run the equity research workflow. The pipeline orchestrates Python scripts using OpenPyXL for Excel outputs and Node.js scripts for generating Word documents and other research artifacts.

You can update existing valuation models without overwriting previous outputs by re-running the pipeline with the --skip-existing flag. This enables incremental updates, preserving complete artifact history per ticker while generating new ongoing monitoring trackers.

Yes, the equity research pipeline supports generating initiation reports in Word format. It uses the docx library to produce live .docx documents, creating standard sell-side initiation reports alongside Excel valuation models within the ticker coverage directory.