Status: August 1, 2025
Everyone is currently talking about Novo Nordisk - and many are buying it after the massive price drop because the share is now supposedly "cheap".
But be careful: a price drop of -70 % can be a bargain - but it doesn't have to be.
At the end of July, Novo Nordisk collapsed after a forecast reduction by a further 33 %. The new price simply reflects weaker growth and new risks - not necessarily an undervaluation.
The crucial question:
How do I find out whether a share is actually cheaply valued - or whether the market has simply become more realistic?
There are several approaches to this. One of the most popular - and in my opinion the most sound for many investors - is the discounted cash flow method (DCF).
📌 Important:
- The model cannot macro events (interest rate shocks, recessions) or political surprises - such as a sudden price cap on 🍊 medicines.
- A sharp fall in prices can trigger a short-term technical countermovement (rebound) in the short term - this can be interesting for traders. But for long-term investors, the decisive factor is whether the share is fundamentally is undervalued.
💡 Why DCF?
DCF analysis is so popular because it not only looks at current key figures such as P/E ratios or price/sales, but also evaluates the true core of a share:
How much money will this company earn in the future - and what is this cash flow worth today?
The model forces you to make all important assumptions openly:
- expected sales growth
- profit margins
- Investment requirements (CapEx)
- capital costs (WACC)
- and a long-term, realistic growth target (terminal growth).
Although this makes DCF somewhat more labor-intensive than simply "comparing the P/E ratio with the industry average", it provides a company-specific fair value. company-specific fair value instead of just a relative market opinion.
🤨 Sounds complicated?
There are ready-made spreadsheets for calculating the DCF where you have to enter current data manually.
It's easier with AI.
Particularly capable models such as ChatGPT-o3 or "deep research" (ChatGPT, Gemini, etc.) do not provide an infallible analysis (always double check), but they do research the necessary data for you.
✏️ DIY-Prompt (UPDATE: August 3, 2025)
"[Please insert TICKER]
1. data basis: Use the latest 10-K/10-Q/20-F/6-K/Half-Year-Report (≤ 90 days old) and the current investor presentation.
2. segmentation: Use the segments shown in the report; without segment info → Group as a whole.
3. input data (per segment, amounts in billions): Sales TTM, EBIT TTM, EBIT margin, FCF conversion = (EBIT×(1-Tax)-ΔWC-CapEx)/EBIT, Beta, WACC. Net debt = cash - debt ± pension/lease liabilities; take off-balance liabilities > 5% sales into account.
4. WACC:
- rf = yield on 10-year government bond of reporting currency; MRP = 5.5 % (developed markets, plus country risk premium for emerging markets).
- Beta from 24-month regression against home or sector index.
- Kd (after tax) = average of the last 4 quarters interest expense/gross debt × (1-effective tax rate).
- Capital structure by market value (D/V).
5. forecasts (5 years):
- Sales CAGR: Select smaller value from 5-year history and analyst consensus; if growth rates are historically extremely high (> 10 pp above consensus), model a flattening path.
- EBIT margin: Linear path from 3-year average towards management guidance; justify deviations > ±3 pp.
- CapEx (% sales): Median of the last 3 years as a basis; increase for announced major investments.
- Tax rate: Ø effective tax rate of the last 3 years or statutory rate.
- Buybacks: Ø of the last 3 years, capped at 80% of the forecast FCF.
6. valuation: mid-year discounting; terminal value = 60 % perpetuity (long-term inflation + 0-0.5 pp, max. 2.5 %) + 40 % EV/EBITDA exit multiple (median of the last 5 years or peer median, max. 20×). Three scenarios (bull/base/bear) with adjustments to sales CAGR, margins, CapEx, WACC; additional Monte Carlo simulation (1,000 runs) on WACC, terminal growth and margins.
7th edition:
- Input table.
- DCF summary with segment EV, group EV, net debt and fair value per share (home currency + USD).
- Sensitivity heat map for ΔWACC ± 0.5 pp × ΔTerminal-g ± 0.25 pp.
- Monte Carlo histogram.
- Conclusion (≤ 200 words) on spot price, fair value range, key drivers and risks.
8. plausibility checks: segment totals vs. group ≤ 1 % deviation; mark assumptions that significantly exceed historical ranges; round to one decimal place; run model in reporting currency and additionally show fair value in USD with FX rate."
📌 DCF analysis results of 3 examples: (UPDATE: August 3, 2025)
Excerpts from the calculation with Gemini 2.5 Pro Deep Research:
Novo Nordisk $NOVO B (+1,26 %)
- 📈 BULL: 415,50 DKK
- ⚖️ BASE: 332,83 DKK
- 📉 BEAR: 255,75 DKK
Although the recent fall in the share price has made the share more attractive, our fundamental analysis suggests that the risks remain considerable. The calculated intrinsic value in the base case scenario offers a limited margin of safety from the current share price. The discrepancy between our more conservative valuation and the more optimistic analyst consensus indicates a high degree of uncertainty.
Given the balanced risk/reward profile and the possibility of further negative surprises related to competition and market penetration, we rate Novo Nordisk's stock a HoldHold. We set a 12-month price target of DKK 333.00which corresponds to our DCF value in the base case scenario. A re-rating would be justified if the company demonstrates a sustained stabilization of its market share in the US and successfully curbs the threat from the compounding market.
Alphabet $GOOGL (-2,86 %)
- 📈 BULL: $272.80
- ⚖️ BASE: $214,50
- 📉 BEAR: $168.20
The analysis results in a fair value of $214,50 per share in the base scenario, with a range of $168.20 to $272.80. Compared to the current share price of around $189, this indicates an undervaluation. The valuation is largely driven by the pace of margin expansion at Google Cloud and the successful, cost-efficient integration of AI into the core search product. The main risks arise from the uncertain financial impact of the antitrust proceedings and the immense capital expenditure for competition in the AI sector, which will weigh on free cash flow in the short term. The wide valuation range reflects the high level of uncertainty surrounding these key strategic and regulatory factors.
Microsoft $MSFT (-3,8 %)
- 📈 BULL: $652.3
- ⚖️ BASE: $545,8
- 📉 BEAR: $465.1
The fundamental analysis carried out results in a fair value of $545.8 per share in the base scenario. This indicates a slight undervaluation compared to the current price level. The share is trading comfortably within the fair value range derived from the scenario analysis and the Monte Carlo simulation.
The investment thesis is positive and is based on the assumption that Microsoft can successfully translate its leading position in AI transformation into sustainable, profitable growth. The strategic foresight of the management, the technological leadership position and the financial strength of the company outweigh the considerable but manageable risks. Although the massive investment phase is putting pressure on free cash flow in the short term, it is laying the foundations for the next growth decade. For long-term investors, the share represents an attractive investment opportunity at the current level in order to participate in the fundamental technological shift towards the cloud and AI.
FAQ - Why this DCF prompt is optimized
- Flexible for all sectors: Rules fit growth, value, defensive and cyclical stocks.
- Avoids overoptimism: Sales growth is limited by the smaller value from history and analyst consensus.
- Realistic margins & CapEx: Guided by 3-year average and known investment plans.
- Clean cost of capital calculation: WACC is accurately determined using current market data (rf, beta, MRP).
- Segment accuracy: Results per division and comparison with group total for plausibility check.
- Risk adjustment: Scenarios + Monte Carlo simulation cover uncertainties.
- Compact structure: Little continuous text, clear flow → insert and process quickly in AI chat.
Sense of bull/base/bear cases with large spread:
- Shows how much the fair value depends on key assumptions.
- Quantifies opportunities (bull) and risks (bear) alongside the most realistic estimate (base).
- Large spread indicates high uncertainty - important for investment decisions.
- Helps to classify and relativize "best-case euphoria" or "worst-case panic".