Financial Data Investment Analysis -- 2

I have an extensive set of financial records attached to an 86-million-dollar portfolio and need them transformed into clear, defensible investment insights. The core purpose is to evaluate current and prospective opportunities, not merely spot trends or forecast performance. Expect to dig into raw transactional data, balance sheets, and market feeds, then surface the strengths, weaknesses, and hidden potential of each holding.

You are free to work in Python (Pandas, NumPy, SciPy), R, SQL, Excel Power Query, or any other toolkit you trust, so long as the outcome is reproducible. I will provide the data in CSV and relational-database dumps; secure transfer protocols are already in place.

Deliverables
• Cleaned and well-documented dataset (with transformation scripts)
• Analytical report highlighting valuation metrics, risk indicators, and recommended buy/hold/sell actions
• Supporting notebooks or dashboards so I can retrace every calculation

Acceptance criteria
• Each recommendation backed by clear quantitative evidence (e.g., discounted cash-flow, Sharpe ratio, or comparable valuation)
• All code, queries, and models run end-to-end on my machine without modification
• Final report written in plain language for board-level presentation

Timeline is flexible within reason, but I value thoughtful analysis over speed. If this scope aligns with your expertise, let’s talk through your approach and milestones.