Fair value vs price: what the per-method breakdown tells you

Every OakBag stock page carries a panel headed “How the fair value is built.” It is the most useful part of the page and the most overlooked. Instead of asking you to trust one fair-value figure, it shows the individual valuation methods that produced it — a small table where each row is one way of pricing the business, and the middle of those rows is the fair value quoted at the top of the page. Learning to read it turns a single colour into a story about why a stock is priced the way it is.

The rows: each method is one opinion

Each row in the table is a separate valuation method, or “leg,” and each puts a dollar value on a share from its own angle. For most companies you will see up to four of them contributing, plus a reference row:

• Peer P/E — the price the shares would carry at the earnings multiple typical of the company’s profitable sector peers.
• Peer EV/EBITDA — a valuation on operating cash earnings against the sector’s enterprise-value multiple.
• ML-justified — a machine-learning estimate of the multiple the company’s own fundamentals deserve.
• Cash-flow DCF — a discounted-cash-flow value on free cash flow per share.
• Graham number — a classic Graham valuation, shown for reference only and left out of the combined figure.

Balance-sheet businesses look different by design: a bank or insurer shows a price-to-book row instead of the cash-flow and EV/EBITDA legs, because those methods do not describe how such firms make money. Why that substitution happens, and how the legs are combined, is covered in the companion guide on how the fair value is computed.

Why the middle row is the answer

The fair value is not the average of the legs — it is their median, the middle value once they are lined up. That choice matters. An average lets one wild reading drag the whole estimate with it; a median ignores the extremes and reports the consensus of the pack. So when you scan the table, the fair value at the top of the page sits in the centre of the rows below, and reading them together tells you how tight or loose that consensus is. A company such as A. O. Smith shows the full set of methods contributing, which is exactly the kind of well-populated table the median was designed for.

The ▲ and ▼ markers: when a leg was capped

Some rows carry a small ▲ or ▼ next to the value. That marker is an honesty signal, and it is important. Before the methods are combined, each one is clipped to a sensible band around the current price — no lower than 0.45× and no higher than 2.2×. A leg whose raw output fell outside that band is capped to the nearest edge, and the marker tells you so: ▲ means the raw estimate was above the ceiling and pulled down to it, ▼ means it was below the floor and pulled up. A capped leg is a number the model reined in rather than measured cleanly, so you should weight it less than an uncapped one. When every leg is pinned to the ceiling, the discount is likely a clipping artefact rather than a real bargain — and, as the fair-value guide explains, that is one of the conditions that can hold a cheap-looking stock at orange instead of green.

Agreement and disagreement between methods

The real payoff of the table is the pattern across the rows. When the legs cluster tightly — P/E, EV/EBITDA, the machine-learning value and the DCF all landing near each other — the fair value rests on a genuine consensus, and the estimate deserves more confidence. When they scatter widely, the methods are disagreeing about the business, and the single fair-value figure is papering over that tension; that is a cue to dig into which method you believe and why. A retailer like Abercrombie & Fitch and a telecom such as Verizon Communications make instructive comparisons here — different industries, different method mixes, and different degrees of agreement between the legs. OakBag even reflects this spread in a confidence figure: the tighter the legs, the higher the confidence.

A balance-sheet example

To see the alternative layout, open a financial. An insurer like Prudential Financial is valued on peer price-to-book rather than on cash flow, so its table leads with a book-value leg, and its green light — if it has one — additionally depends on that book leg confirming the discount. Comparing a financial’s table with an industrial’s is the quickest way to internalise why one valuation method never fits every business, and why a screener that applied cash-flow DCF to a bank would produce numbers you should ignore.

Using the breakdown in practice

Read the table top to bottom before you trust the colour. Note how many legs are contributing — a fair value built on one or two rows is far more fragile than one built on four. Check for ▲/▼ markers and discount the capped legs. See whether the rows agree or argue. Then set the whole picture against the margin of safety and the risk flags elsewhere on the page, because the breakdown answers “how was this valued?” while the margin-of-safety guide answers “and should a low price alone convince me?” Browse a few names from the stocks rated green today with the table open and the habit forms quickly.

As with everything on OakBag, the breakdown is a model estimate from third-party data for research, not a recommendation or a price target. The point of exposing every leg is transparency — so you can see precisely how the number was reached and judge it for yourself. Everything described here is on the free plan, laid out on the pricing and plans page.