Lisbon decision profile

Lisbon, in structure.

Atlantic capital comparison market with a distinct regulatory and tax environment.

High data coverage · 7/7 official metricsCompare with others

Registered price

€4,310 / m²

Lisboa (município) · Q4 2025 · Instituto Nacional de Estatística (Portugal) · high confidence

This is a structured decision model, not a prediction and not a valuation.

Price direction

+9.1% year on year

Price trend

Lisboa · Q4 2025 · Instituto Nacional de Estatística (Portugal) · high confidence

Market activity

11,900 recorded sales

Transaction volume

Área Metropolitana de Lisboa · 2025 · Instituto Nacional de Estatística (Portugal) · partial confidence

Buyer mix

11.8% of recorded purchases

Foreign buyer activity

Portugal · 2025 · Instituto Nacional de Estatística (Portugal) · partial confidence · National figure; no Lisbon-only split is published.

Finance

3.1% average new mortgage

Mortgage context

Portugal · Q4 2025 · Instituto Nacional de Estatística (Portugal) · partial confidence

Supply

4,220 permits issued

New-build activity

Área Metropolitana de Lisboa · 2025 · Instituto Nacional de Estatística (Portugal) · partial confidence

Regulation

Short-term rental (AL) licensing has been repeatedly reformed; verify current status per address.
Residence-by-investment routes for property have been withdrawn.

Lifestyle fit

Recorded strengths: Urban culture, Coast within 30 minutes, International community, Walkable. Build your SWIP profile to personalise this.

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Data quality

High data coverage

Buyer pressure model

Domestically weighted buyer base
11.8% foreign purchases
Rising transaction activity
+5.4% year on year
Rising registered prices
+9.1% year on year
Verified new-build activity recorded
4,220 permits issued

SWIP analysis

Prices and activity are both recorded higher. That is a straightforward reading, though the registered average is sensitive to which segments happened to trade.

How this was built

Model rules: No score is produced. Each statement restates one published series; the analysis names the pattern and the limits of reading it.
Input data: Only metrics carried in the SWIP source library. Each figure keeps its publisher, geography, period and confidence.
Periods: Latest published period per series. Periods differ between series and are shown per figure.
Geographies: Geography is stated per figure. Where a municipal figure does not exist, a regional or national series may be shown as context and is labelled as such.
Limitations: Averages are sensitive to the mix of properties that happened to transact. Low-volume municipalities produce volatile averages. Nothing here is a valuation or a forecast.
Interpretation method: Models combine published values using stated rules. No weighting is hidden and no score is generated that the rules above do not fully explain.

Ownership friction model

MEDIUM

2 recorded regulatory considerations
Short-term rental (AL) licensing has been repeatedly reformed; verify current status per address.
Tourist-rental restrictions apply
Regulatory notes
Moderate financing cost
3.1% average rate
Cross-border ownership structure required
Jurisdiction differs from SWIP's home market

How this was built

Model rules: One point per recorded regulatory consideration. Two points where tourist-rental restrictions are recorded. Two points where average financing cost is 4% or above; one point where no official series exists. One or two points for partial or low official data coverage. One point where ownership sits outside SWIP's home jurisdiction. 0–4 LOW · 5–7 MEDIUM · 8+ HIGH.
Input data: Only metrics carried in the SWIP source library. Each figure keeps its publisher, geography, period and confidence.
Periods: Latest published period per series. Periods differ between series and are shown per figure.
Geographies: Geography is stated per figure. Where a municipal figure does not exist, a regional or national series may be shown as context and is labelled as such.
Limitations: Averages are sensitive to the mix of properties that happened to transact. Low-volume municipalities produce volatile averages. Nothing here is a valuation or a forecast.
Interpretation method: Models combine published values using stated rules. No weighting is hidden and no score is generated that the rules above do not fully explain.

Cross-sectional decision profile

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