How a Property Is Valued on the Existing Market

A valuation is only as strong as the basis it rests on. That sounds obvious, but it is the very mistake that makes most estimates unreliable: the figure gets all the attention, while the assumptions — which transactions it builds on, how comparable they are, and what actually sets the property apart from its neighbour — get pushed into the background. For anyone who has to defend a number in front of a credit committee, a seller or a court, it is precisely the assumptions that decide whether the valuation holds.

This guide walks through how a property valuation is built up on the existing market: the factors that genuinely move value, why quality level and location carry different weight, and how to assess the confidence behind an estimate — without promising anything about where the market is heading. We are talking about market value today, on the transactions that have actually been completed, not about a forecast.

What market value actually means

Market value is the price a property could reasonably be expected to trade at between a willing buyer and a willing seller, at arm’s length, after a reasonable marketing period. It is a hypothetical price — the property is usually not for sale at the moment it is valued — and it is therefore estimated by looking at what comparable properties have actually traded for.

It matters to keep market value distinct from two other figures that are often confused with it. The public property assessment is an authority-set tax base that follows its own model and frequently diverges sharply from the actual transaction price — we covered why in why market value and the public assessment diverge. And the asking price is the seller’s wish, not a fact; only once a transaction is registered in the tingbogen (the Land Registry) do you know what the market actually paid.

The point is that a serious valuation always works backwards from realised transactions, not forwards from expectations. That is also why the estimate is a snapshot: it describes the market as it is, on the data available right now.

The factors that genuinely carry the estimate

When you decompose a valuation, the load-bearing valuation factors fall into a few categories that weigh heavily, plus a long tail of factors that fine-tune. The heavy ones are:

• Location — at several levels at once: region, town, district and right down to the individual street. Two identical houses a few hundred metres apart can have markedly different values, because one sits on a quiet residential street and the other faces a busy arterial road.
• Area and area type — living area, basement, converted loft, garage and plot size do not weigh equally. A basement square metre is not a living-area square metre, and the area concepts in BBR (the Buildings & Dwellings Register) must be understood precisely before they are used in a calculation.
• Building type and age — detached, terraced or apartment; year of construction and any renovations.
• Condition and quality — the quality level, which we return to below, because it is the factor most people underestimate.
• Site conditions and amenities — view, proximity to water, south-facing garden, noise, shading from neighbouring buildings.

On top of that sits a long series of smaller factors — energy label, roof type, number of toilets and bathrooms, heat source, whether there is district heating in the area — each of which moves the figure a little, but which together can explain a substantial spread. A thorough model works with dozens of factors precisely because the small contributions accumulate.

Why location is not one factor

It is tempting to treat location as a single variable, but it is one of the most common sources of skewed valuations. Location operates on a hierarchy: there is a general price level for the municipality, a lower one for the postcode, and a micro-location for the specific address. When an estimate builds on transactions pulled from too wide a radius, micro-locations get blended together, and the result is an average that fits none of the properties. The closer the comparable transactions lie to the property being valued — in geography and in time — the sharper the estimate.

Price per square metre — useful, but never the whole answer

Price per square metre is the most widely used reference point in the industry, because it makes wildly different properties comparable. But it is a derived figure, not a foundation. Two traps recur:

First, price per square metre is non-linear. A small house typically has a higher price per m² than a large one, because the kitchen, bathroom and roof are fixed costs spread over fewer square metres. Multiplying a large property’s area by a price per m² drawn from smaller homes systematically overvalues it.

Second, an average price per m² for an area says nothing about the spread. An area can have a respectable average price and at the same time contain everything from newly renovated to run-down properties. We have described how the figure is calculated and interpreted correctly in how the price per square metre for an area is calculated and read — the short version is that a price per m² without a measure of spread and a count of the underlying transactions is almost useless.

Rule of thumb: never apply an area’s average price per m² directly to a specific property. It is a starting value that must be adjusted for area, condition and micro-location — not a verdict.

Quality level: the factor most people underestimate

Two properties on the same street, the same size, the same year of construction, can trade at prices that lie far apart. The difference is often condition. A newly renovated kitchen, new bathrooms, a new roof and fresh surfaces move the price noticeably — and a run-down property with deferred maintenance pulls it down correspondingly, because the buyer prices in the tradesman’s bills to come.

That is why a mature valuation model works with several quality levels rather than a binary “good/bad”. A fine-grained level makes it possible to place the property precisely between the comparable transactions instead of lumping them together. Setting the level consistently is a discipline in its own right, and this is where many valuations slip — because condition is the hardest thing to read from register data alone. We go into the mechanics in what a building’s condition does to its value.

The practical move is to let the quality level adjust the raw estimate: you find the area’s price level for a property in normal condition and correct up or down for the specific level. On an ordinary single-family house, the jump between run-down and newly refurbished can amount to a substantial share of the total value — and it is precisely that share which means two “identical” houses are not identical.

Confidence: how to read the certainty behind the figure

An estimate without a measure of certainty is a guess in nice typography. The professional difference lies in being able to say how certain the figure is — and why. Confidence in a valuation depends primarily on three things:

• Data density — how many comparable transactions sit behind the estimate? Three transactions give a weaker conclusion than thirty.
• Comparability — how similar are the underlying transactions? Same property type, same order of magnitude, same micro-location, same time window. The more uniform the basis, the more trust you can place in it.
• Spread — how much do the transactions agree? If comparable properties trade close to one another, the market is “in agreement” and the estimate is sharp. If the prices are scattered, the uncertainty is real and should be reflected in a wider range.

In practice this means a valuation should be expressed as a range with a confidence level, not a single figure. A high confidence level belongs to properties in a homogeneous area with many fresh, comparable transactions. A low confidence level is the honest answer for atypical properties — a large premium home, a house with a rare amenity value, or a property in a thinly traded area where there simply aren’t enough comparables to draw on.

When confidence is low, it is a signal — not a flaw

The most important thing to understand is that low confidence is not a weakness of the method, but information. It tells you that the property requires human judgement on top of the data-driven estimate: a physical inspection, a qualified view on amenity value, or a broader search for comparable transactions in other areas of similar character. A valuation that presents an atypical object with high certainty should make you suspicious — not comfortable.

The manual exercise, put into a system

Everything above can be done by hand, and skilled valuers and agents do it daily: pull the realised transactions, weed out the non-comparable, adjust for area and condition, and land on a range with a reasoned certainty. It is thorough, but it is also time-consuming — and it is hard to do completely consistently from case to case.

That is exactly the exercise Arcili’s Boligvurdering (Valuation) puts into a system. The model pulls realised transactions close to the specific property — within a controlled radius and a bounded time window — weighs dozens of factors, adjusts for a fine-grained quality level, and delivers an estimate with an explicit confidence level, so you can see how strong the basis is, not just what the figure sounds like. It does not replace your professional judgement; it gives you a reproducible starting point, so your judgement can be applied where it matters — on the atypical, where confidence is low. If you want to dig into how accurately an automated estimate actually lands, we have covered it in how accurate an automated property valuation really is.

Arcili brings data, analysis and valuation together in one workflow. If you want to see the Boligvurdering (Valuation) on your own cases, you can book a walkthrough.