Comparative Equity Growth Modeling

I need a robust quantitative framework that will let me measure, visualise, and compare the growth trajectory of multiple equity instruments over time. The model should ingest clean price-action information alongside any fundamental or market-wide inputs that improve explanatory power, then output clear growth curves and relative-performance metrics that can be refreshed on demand.

Here’s what I expect to receive:
• A well-documented modelling script or notebook (Python, R, or a similar analytical language) that pulls data from at least one reliable source—financial reports, historical price databases, live market feeds, or a combination—then normalises and merges those streams.
• A set of functions or classes that calculate cumulative growth, volatility-adjusted returns, and peer comparisons across chosen tickers or indices.
• Easy-to-read visualisations (static or interactive) that highlight relative out- or under-performance over selectable periods.
• A brief read-me explaining data connections, libraries used, and instructions for extending the coverage universe.

Acceptance criteria
The code must run end-to-end with sample tickers supplied by you, produce consistent figures when rerun, and remain configurable so I can swap in new instruments or data vendors without structural rewrites.

If you are comfortable building quantitative equity tools and can deliver clean, reproducible code with concise documentation, I’d like to see a short outline of your proposed approach and any similar work you have shipped before.