Portfolio & Case Studies
A finance student learning to see the full picture - where data, business, and value creation connect.
Building towards the intersection where finance meets business decisions.
Most people learn finance from textbooks. I did too.
But textbooks only show you the separate parts: P&Ls, Balance sheet, Cash flow...
The further I went, the more I wanted to see how they actually connect.
How one business decision affects a company's day-to-day operations, and shows up years later in its valuation.
And that's the intersection I want to work in:
Where financial data meets business decisions.
Detailed structural frameworks for valuation and forecasting
To understand how a company is valued, you have to build the model yourself. So I built a 3-statement model for Coles Group - Australia's second-largest grocery retailer. The goal was to answer one investment question: Does Coles deliver a 15% return and double capital over five years?
A comprehensive 3-statement financial model dissecting the FY21 performance of Coles Group. The study encompasses detailed historical analysis, operational driver forecasting, and full integration across the income statement, balance sheet, and cash flow, culminating in an enterprise valuation and sensitivity analysis.
Starting point: Annual Report — the source document for revenue, segment data, and CapEx figures.
Extracted and structured in Excel — store counts, revenue by segment, FY18–FY21.
Growth rates, margin benchmarks, and CapEx decomposition (Growth vs. Maintenance) integrated directly into the driver engine.
Driver-based forecasting over a 5-year horizon: FY21 historical through FY26 projected.
Store count driver flowing into revenue — 20 new stores per year per management guidance.
Margin assumptions and OpEx per store focusing on mean reversion to historical averages.
Cross-statement integration: assets, liabilities, and equity tracked across the full projection period.
Receivables tied to revenue, inventory and payables structurally tied to COGS.
ROU assets, lease liabilities, and principal repayment flows systematically calculated.
FY21 entry at 10x EBITDA, establishing a realistic investment baseline.
EBITDA × exit multiple, net of debt and leases, bridged directly to equity value.
IRR and MOIC sensitivity mapped across store expansion pace and exit multiple variations.
ROC trajectory analysis — showing an improvement from 15.7% toward 20% over the holding period.
The other half is understanding how a business actually runs.
During my internships, I saw a common problem:
Most company's financial data was raw, messy, and unusable without hours of manual work.
So I learned the tools to fix it:
High-fidelity data visualization for executive oversight
I use Power Query to clean and structure the raw accounting data, And Power BI to turn it into interactive reports to help with the decision-makings:
Monthly revenue, cost, and gross profit tracked across the full year. Performance broken down by store location and product SKU to surface where margins are strongest.
Daily receivables balance: current vs. overdue debt tracked accurately across the full year. Receivables systematically segmented by customer group and days outstanding.
Inventory value by product group, visualizing distribution across categories as of the reporting date. Tracking stock value trends and movement velocity across December.
Every finance team needs someone who can model performance.
And someone who can make sense of the data behind it.
Every project I take on is a deliberate step toward this balance.
If you are looking for someone curious, detail-oriented, and eager to contribute—I would love to be considered.
Harvey Pham
Finance Portfolio 2026
Advisory & BOS Intern
BDO Vietnam
SME Banking Intern
MB Bank
Corporate Finance, NEU
GPA: 3.76 / 4.0
CFA Level 2 Candidate
Passed Level 1
Wall Street Prep
Valuation & Financial Modeling