Investment Valuation — Damodaran: COMPLETE

Damodaran begins where Graham ended: the price is set by supply and demand and driven by hope and fear — value is driven by cash flow, growth, and risk. The entire discipline of valuation rests on that difference. His most quoted thesis, from Narrative and Numbers (2017), runs roughly: a valuation is a bridge between stories and numbers. Without the story the numbers become a numbers game; without numbers the story becomes a fable.

AKM1's margin of safety (the buffer: price against intrinsic value) is precisely the operationalization of that gap: in this course's terms, a price of 152 kronor against a computed value of 120 kronor gives no buy signal until you understand why the market pays more — and who is right.

The book's philosophical core is its view of the market's rationality. Under perfect rationality the price adjusts to value immediately and every deviation is arbitraged away — all that remains for the valuer is to explain why the price is right. Damodaran takes the position he calls practical rationality: the market is right most of the time, but it makes mistakes — sometimes large ones, sometimes across whole sectors, and sometimes for a long time.

It is in that in-between space that an active investor lives. Note too that valuation is needed even by those who believe in efficient markets: in IPO pricing, acquisitions, fairness opinions, inheritance, and taxation someone must set a value regardless of what the stock exchange says on the day.

Damodaran distinguishes absolute models (discounted cash flows — value from the company itself), relative models (valuation multiples — price against comparables), and contingent models (contingent claims). And he warns on the very first page about bias: valuation is not an objective search for truth. Preconceptions slip in through the back door — we choose the assumptions that give the conclusion we want.

His antidote is concrete, and it is a standing rule of this course: value the company before you look at the price, and force yourself to write the story the numbers have to support. That is exactly the discipline the AKM1 ecosystem trains.

Absolute models (DCF) derive value from the company itself: estimate cash flows, growth, and risk, then discount. Relative models (valuation multiples) set a price through comparison with other companies — Damodaran calls it pricing as distinct from valuation. Contingent models, finally, price uncertainty and flexibility with option theory.

Three families, three questions: what is the company worth in itself, what does it cost against comparables, and what is the flexibility worth? Mature craftsmanship means mastering all three — and knowing that the multiple gives you a price while the DCF gives you value (the AKM1 valuation variables V04–V06 reason the same way).

The DCF family has three main variants. The dividend discount model (DDM) values only what is actually paid out — it suits mature companies with a stable dividend policy, such as banks and utilities. FCFE values the cash flow that could have been paid to the owners — right when the dividend departs from capacity, for instance when the company is hoarding cash or buying its own stocks back (a share buyback).

FCFF values the flow to all capital and yields enterprise value (EV) — right when the debt structure is changing or for capital-intensive companies. Damodaran adds excess-return models: value = invested capital + present value of future excess returns — elegant precisely when ROIC is the heart of the story (the moat variables V13–V15 in AKM1).

Throughout the book the consistency rule is the same: the same three inputs — cash flow, growth, and discount rate — drive every model. A valuation multiple is a DCF in compressed form: all the assumptions are still there, they are just invisible.

A P/E of 20 is not 'expensive' or 'cheap' until you know what growth, risk, and ROIC are baked into it. That is why every relative analysis in AKM1 ends with the same question as the DCF: what story am I paying for?