← Current development

Wall Street Prep · In progress

Learning to make every valuation assumption earn its place.

The modelling foundations are familiar. My current focus is the professional judgement behind them: selecting defensible drivers, estimating risk without false precision, triangulating methods and leaving an audit trail another analyst can challenge.

View the official curriculum ↗

What I'm refining

The judgement behind a defensible valuation.

A strong model is not the one with the most detail. It is the one where the key drivers are evidence-based, the logic is internally consistent and the conclusion survives a sensible challenge.

01

Operating forecast drivers

Translate the business model into a revenue build, segment margins, working capital and reinvestment assumptions. Back-test each driver against historical performance and operating evidence before extending it forward.

02

Beta and cost of capital

Build a relevant peer-beta set, identify distorted observations, unlever and relever beta to the target capital structure, and reconcile WACC inputs with the company’s underlying operating and financial risk.

03

Trading comparables

Select peers by revenue model, end-market, geography, growth, margin profile and capital intensity. Normalise LTM and NTM metrics, investigate outliers and document why each company belongs in—or outside—the set.

04

DCF and terminal value

Forecast unlevered free cash flow, align long-run growth and margin assumptions with economic reality, and cross-check perpetuity-growth and exit-multiple terminal values before interpreting the valuation range.

05

Precedent transactions

Filter transactions for timing, size, geography, control and deal context. Separate market-cycle effects, premiums and expected synergies so historical purchase prices are not treated as directly comparable without adjustment.

06

Transaction and LBO analysis

Connect purchase accounting, accretion or dilution, sources and uses, debt schedules and returns. Pressure-test operating downside, deleveraging and exit assumptions to identify what genuinely drives the investment case.

Modelling standard

Precision without false confidence.

  • Evidence before formula: source and explain each material driver before refining the mechanics around it.
  • Audit-ready logic: separate inputs, calculations and outputs; use consistent signs, units, dates and model checks.
  • Triangulate value: reconcile DCF, trading and transaction evidence instead of forcing one method to carry the conclusion.
  • Pressure-test the thesis: show which assumptions move value, where downside appears and what evidence would change the view.