Fundamental Valuation of Schlumberger (SLB)
This project presents a complete equity valuation of Schlumberger (NYSE: SLB) using two core methodologies:
- Discounted Cash Flow (DCF) Analysis
- Comparable Company Analysis (Comps Model)
It includes a full 3-statement financial model (Income Statement, Balance Sheet, Cash Flow), sensitivity analysis, scenario logic, and valuation triangulation.
| File/Folder | Description |
|---|---|
Final Report SLB.pdf |
A 14-page investment-grade valuation report detailing methodology, assumptions, outputs, and investment recommendation |
Schlumberger_Valuation.xlsx |
Full Excel model including DCF valuation, comps model, 3-statement forecast, ratios, and assumptions |
- Forecast Horizon: FY2025βFY2029
- WACC: 9.2% (based on CAPM and capital structure)
- Terminal Growth Rate: 1.0 - 2.0%
- UFCF calculated as:
EBIT*(1 β tax) + D&A β CapEx β ΞWorking Capital - Sensitivity analysis across WACC and perpetuity growth rate
- Peer Set: Halliburton (HAL), Baker Hughes (BKR), Weatherford (WFRD), Tenaris (TS), NOV Inc. (NOV)
- Valuation multiples: EV/Revenue, EV/EBITDA, P/E
- Market data from public filings and investor platforms (as of June 2025)
| Method | Implied Equity Value ($b) | Implied Value per Share ($) |
|---|---|---|
| DCF β Optimistic Case | $90.3b | $66.1 |
| DCF β Base Case | $75.9b | $55.5 |
| DCF β Conservative Case | $66.4b | $48.6 |
| Comps β EV/Revenue | $33.4b | $24.44 |
| Comps β EV/EBITDA | $36.1b | $26.43 |
| Comps β P/E | $36.2b | $26.49 |
| Market Cap and Price (21.06.2025) | $48.96b | $35.84 |
Recommendation: BUY
SLB appears undervalued on a DCF basis with strong cash flows, while trading at a reasonable premium to comps due to scale, diversification, and digital innovation leadership.
All sources are cited in the report and compiled in Harvard format.
Key sources include:
- SLB Investor Relations: https://investorcenter.slb.com
- SLB Annual Reports 2023,2024
- Finviz, Yahoo Finance, ScienceDirect, Wikipedia (technical tools and history)
This project was independently executed by Arsen Tagibekov using financial modeling best practices, with AI-assisted support from ChatGPT (OpenAI) for logic structuring, Excel validation, and formatting feedback.