This portfolio is being developed as a professional proof layer. The work below has a real analytical foundation; the public case studies will be expanded as the models, reports, and supporting evidence are prepared for external review.
A strong case study needs more than a polished card. Each future entry will show the question, assumptions, method, model structure, sensitivities, conclusion, limitations, and a professional deliverable.
A Python-based forecasting framework using VAR and machine-learning techniques across 40+ macroeconomic indicators, paired with DCF and fundamental analysis to inform sector and security-level views.
Equity research developed from company filings, earnings materials, industry context, and valuation work. The next version will package the thesis, key drivers, sensitivities, and conclusion into a recruiter-ready research case study.
A five-round fictional capital-allocation challenge spanning capacity, margin pressure, M&A structure, interest rates, and reforecasting. Choose, compare, and confirm each trade-off before seeing the resulting decision profile.
A rebuilt version of the original Wealth Management Game. Adjust income, spending, debt, and age to explore monthly cash flow, a simple essential buffer range, and long-term contribution capacity.
A clear decision, stakeholder, or investment question—plus why it matters.
Data sources, assumptions, model architecture, methodology, and sensitivity work.
An interpretable conclusion, limitations, model, memo, report, deck, or repository.
This is intentionally a quality-over-quantity portfolio. New projects will be added when the underlying financial analysis and documentation can withstand interview-level scrutiny.
Discuss the work →