Compare second homes across Europe: a financial model guide

Build a spreadsheet model to compare second homes across European regions. Step-by-step guide to calculate cashflow, ROI, and break-even occupancy for any two properties.

Browsing listing portals across Spain, Portugal, France, Italy, Greece, Sweden, and Croatia is straightforward enough. The hard part is translating five different price tags in four currencies, with varying transaction costs, tax regimes, and rental income potential, into a single, honest comparison. Most buyers stop at the listing price. That decision costs them significantly.

This guide walks you through a structured, spreadsheet-based approach for comparing second homes across European regions like an investor. By the end, you'll have a working model that produces projected cashflow, ROI, and sensitivity scenarios for any two properties in any two countries, and you'll know exactly where to source the inputs.

What you'll need: a Google Sheets or Excel account, 60-90 minutes to populate the template, and listing data from at least two properties in different countries.

Difficulty: Intermediate. No financial modeling background required.

Build your comparison spreadsheet: the core tool

The single biggest gap in existing resources for comparing second homes in Europe is the absence of a unified financial model. The OECD House Price Tracker provides trend data but offers no buyer-oriented workflow. The EU's official "Buying a house" overview on europa.eu runs to roughly 80 words before redirecting you elsewhere. Property portal roundups aggregate listings but rarely connect price to tax, rental yield, or currency risk.

A well-structured comparison spreadsheet closes all three gaps. Its job is to translate raw listing data into three actionable outputs:

• Net cashflow by year (annual rental income minus mortgage service, taxes, and operating costs, expressed in a single base currency)
• Cash-on-cash ROI and total ROI (returns as a percentage of your actual cash invested)
• Break-even occupancy (the minimum occupancy rate at which the property covers its annual costs)

Set up two columns in your spreadsheet, one for each property. Every row is an input or a calculated output. The structure below defines what goes in each row.

Required inputs at a glance

Keep the input cells clearly labeled and color-coded. Outputs should reference input cells only, so changing a single assumption updates every downstream figure instantly.

How to fill each input correctly

Purchase and closing costs

Enter the listed price from whichever portal you're using. For cross-European search with a single login, platforms like Homestra are useful here: the platform covers over 200,000 properties across multiple countries and formats listings consistently, which makes extracting comparable price data faster than toggling between country-specific portals like Idealista (Spain/Portugal/Italy), Green-Acres (France), Kyero (Spain/Portugal), or Immobiliare.it (Italy).

Closing costs in Europe vary significantly by country. Model them as a percentage of purchase price in a separate cell so you can adjust per market. As a starting point for research:

• Spain: Transfer tax (ITP) on resale properties varies by region, typically 6-10%; plus notary, registry, and agency fees adding 1-2%.
• Portugal: IMT (property transfer tax) is progressive up to 8% for non-residents; IMI stamp duty at 0.8%; plus notary/registry fees.
• France: Notaire fees on older properties run approximately 7-8% of purchase price.
• Sweden: Lagfart (title registration stamp duty) is 1.5% of purchase price or assessed value, whichever is higher, plus a fixed registration fee of 825 SEK (Homestra, February 2026).
• Greece and Croatia: Both have transfer taxes in the range of 3-4%, but verify the current assessed basis with a local notary before modeling.

Always verify these figures against official government sources or a qualified local lawyer before treating them as final. Tax rates change, and assessed bases sometimes differ from market values.

Financing inputs

Enter your down payment as a percentage. For non-EU buyers, many markets require more equity than domestic buyers. In Sweden, for example, the legal minimum down payment is 15% (85% maximum loan-to-value), and foreign buyers should expect mortgage rates 0.1% to 0.9% above the resident rate, which placed the range at approximately 2.9% to 4.0% in early 2026 (Homestra, February 2026). Model the rate you've actually been quoted, not the headline rate, and include any arrangement or mortgage broker fees in the closing costs bucket.

Annual property taxes and non-resident tax treatment

Separate one-time transaction taxes from recurring annual charges. Spain's IBI (annual property tax), France's taxe foncière, and Italy's IMU for second homes are all recurring obligations that meaningfully reduce net cashflow. Enter them as a fixed annual euro amount per property.

For rental income, tax treatment for non-residents varies widely. Sweden applies the SINK regime: a flat withholding rate of 22.5% (proposed for 2026, reduced from the prior 25%) on rental income for non-residents, with income below 40,000 SEK annually exempt from this tax (Homestra, February 2026). In Spain, non-resident rental income is typically taxed at 19% for EU/EEA residents and 24% for others. Build a "rental income tax rate" row into your model and apply it to gross rental income before calculating net cashflow.

Rental income: occupancy and nightly rates

Occupancy rate is the input with the most leverage on your output. A 5% change in occupancy on a coastal property often flips the model from positive to negative cashflow. Enter your assumed occupancy rate as a percentage of available nights (typically 365 or 300 if you plan personal use). For each market:

• Use comparable active listings on Airbnb and VRBO to estimate nightly rates in your target location and property type.
• Pull occupancy data from tools like AirDNA or Transparent (both provide regional European data) to validate whether your assumed rate is realistic.
• Include a per-turnover cleaning fee row; at 15-30 euros per night, it adds up across 80-120 annual bookings.

Add a seasonality column if your market has significant winter/summer variance (coastal France, Greek islands, Swedish lake properties). A simple high/low season split, with separate occupancy and nightly rate assumptions, is more accurate than a single blended rate.

Operating costs

A standard maintenance reserve for European second homes is 1-2% of property value per year. Add insurance as a fixed annual figure. If you plan to use a property management company (common for non-resident owners), model 15-25% of gross rental income as the management fee.

Sensitivity inputs

Create a separate "scenarios" tab with three columns: base case, low occupancy (-20%), and adverse FX (-10%). This is where your model earns its keep.

Worked example: comparing a Swedish fritidshus vs. a Greek island property

The following is a simplified illustration using representative assumptions. Run your own figures using your actual quotes.

Property A: Fritidshus (vacation cabin), rural Sweden

• Purchase price: 2,500,000 SEK (approx. EUR 220,000 at 11.35 SEK/EUR)
• Closing costs: 1.5% stamp duty (lagfart) + 825 SEK registration fee + approx. 1.5% other fees = ~3% total
• Down payment: 25% (conservative for a foreign buyer)
• Interest rate: 3.6% over 25 years
• Annual property tax (fastighetsskatt): approximately 0.75% of assessed value
• Occupancy assumption: 55% (short summer season, approx. 70 nights)
• Average nightly rate: 1,400 SEK (~EUR 123)
• Rental income tax: 22.5% (SINK, above the 40,000 SEK threshold)

Property B: Stone cottage, Greek island (Cyclades)

• Purchase price: EUR 220,000
• Closing costs: ~3.5% (3% transfer tax + notary/registry)
• Down payment: 30%
• Interest rate: 4.5% over 20 years (Greek bank, non-resident)
• Annual property tax (ENFIA): approx. EUR 600-900 depending on assessed value
• Occupancy assumption: 72% (approx. 130 nights, strong summer demand)
• Average nightly rate: EUR 140
• Rental income tax: 15% (Greek scale for rental income up to EUR 12,000)

Step 1: Enter values and calculate annual gross rental income

• Property A: 70 nights x 123 EUR = EUR 8,610 gross
• Property B: 130 nights x 140 EUR = EUR 18,200 gross

The Greek property generates roughly 2.1x more gross rental income despite the same purchase price.

Step 2: Subtract rental income tax and operating costs

• Property A (after SINK at 22.5% on taxable amount, maintenance, insurance, cleaning): net rental income approx. EUR 5,200
• Property B (after 15% tax, maintenance, management at 20%, cleaning): net rental income approx. EUR 10,800

Step 3: Subtract annual mortgage service

Both properties carry similar down payments (EUR 55,000 and EUR 66,000 respectively). Annual mortgage service on Property A runs approximately EUR 8,900; Property B approximately EUR 8,100 given the shorter Swedish kronor/euro FX buffer.

Step 4: Calculate net cashflow and cash-on-cash ROI

• Property A: EUR 5,200 - EUR 8,900 = EUR -3,700 net cashflow (negative; owner contribution required)
• Property B: EUR 10,800 - EUR 8,100 = EUR +2,700 net cashflow (positive)

On paper, Greece wins on cashflow. But run the sensitivity: drop Greek occupancy to 52% (adverse scenario) and apply a -10% EUR/GBP or EUR/USD FX assumption for a dollar-based buyer, and cashflow compresses to roughly EUR +400, well within rounding error of breakeven.

Sweden, conversely, becomes more defensible if the buyer has a strong personal-use case (offsetting the negative cashflow with lifestyle value) and a long capital appreciation horizon. The model doesn't tell you which property to buy. It tells you exactly what you're betting on.

How to interpret results and run sensitivity analysis

Cash-on-cash ROI vs. total ROI

Cash-on-cash ROI measures net annual cashflow divided by your actual cash invested (down payment plus closing costs). It tells you how efficiently your deposited equity is working. Total ROI adds capital appreciation to the numerator, which is speculative unless backed by regional price trend data (Eurostat's Housing Price Statistics database and the OECD House Price Tracker are useful reference points for directional trends, even if they don't predict future values).

For second homes, cash-on-cash ROI is the more conservative and more useful metric. If it's negative, you need to be honest about whether the lifestyle benefit justifies the annual shortfall.

Break-even occupancy

This is the single most useful output in the model. Divide total annual fixed costs (mortgage service + taxes + insurance + management) by net revenue per night (nightly rate minus cleaning fee, minus tax). The result is the number of nights needed to break even. Express it as a percentage of your available rental window.

If break-even occupancy is 45% and the market delivers 70%, you have meaningful downside buffer. If break-even is 68% and the market delivers 72%, your model is fragile. One slow season, a burst pipe in February, or a competitor listing at 15% lower nightly rates can tip you into loss.

Decision rule

If cashflow stays positive or within tolerable deficit across both the base case and the low-occupancy scenario, proceed to deeper due diligence: legal review, structural inspection, title search. If cashflow only works in the optimistic scenario, treat it as a lifestyle purchase with investment characteristics, not an investment with lifestyle characteristics.

Localizing your inputs: a practical checklist

Tax localization

• Verify purchase/transfer taxes against the relevant country's tax authority website or a local notary, not just expat forums. Sweden's lagfart rate is straightforward at 1.5%; Spain's ITP depends on the region (Andalusia differs from Valencia).
• Distinguish between the headline tax rate and the assessed value base. Some countries apply transfer tax to the declared purchase price; others use an official catastral value that may differ significantly.
• For non-resident rental income tax, confirm whether your home country has a double taxation treaty with the property country that reduces withholding obligations.

Occupancy and nightly rate localization

• Pull at least 10 comparable active listings from the primary short-term rental platform for your target area. Use median nightly rate, not mean (outliers distort the average).
• Check seasonal calendars: a Swedish lakeside property may rent for 15 weeks; a Portugese Algarve villa may command 22+ weeks. The rental window matters as much as the nightly rate.
• AirDNA's regional European data is a credible source for occupancy benchmarks by market and property type. For France specifically, Green-Acres listing volumes can indicate demand concentration by region.

Currency localization

• If your income is in USD or GBP and the property country uses EUR or SEK, build two FX rows: a spot rate and a conservative rate (typically spot minus 8-12%).
• Run your cashflow output through both. If the conservative FX scenario pushes cashflow negative, quantify the annual exposure in your home currency so it's visible, not hidden.
• Avoid presenting FX risk as binary (hedged vs. unhedged). Most second-home buyers aren't hedging; acknowledge the exposure and size it.

The due diligence reminder

The spreadsheet output is only as reliable as the inputs. Nightly rate assumptions sourced from a single weekend of browsing Airbnb, or transfer tax figures copied from a five-year-old blog post, will produce confident-looking numbers built on weak foundations. Use the model to structure the right questions, then verify every material input with a qualified local professional (lawyer, notary, tax advisor) before committing.

Platforms like Homestra support this process by providing detailed country-specific guidance alongside listings, so buyers can cross-reference transaction cost expectations against real listings in the same interface. That combination of listing data and country-level context is where most single-country portals and generic data tools fall short for cross-European second home comparison.

Where to source data for European property markets

For regional house price benchmarks, Eurostat's Housing Price Statistics and the OECD House Price Tracker both provide indexed data by country. Neither replaces a local market appraisal, but both are useful for assessing whether a market has been appreciating or softening over the prior 2-5 years, which affects your total ROI assumptions.

For listing-level comps across France, Spain, Portugal, Italy, and Greece, the major country-specific portals (Idealista, Kyero, Green-Acres, Immobiliare.it) each cover their respective markets well. The practical challenge for cross-country buyers is that using five separate platforms makes consistent comparison time-consuming. Cross-country platforms that aggregate across borders reduce that friction.

For tax and cost benchmarks by country, the Global Property Guide publishes rental yield and transaction cost estimates by market. Numbeo provides cost-of-living context that's relevant for estimating realistic utility and maintenance costs in a given city or region. Both are useful as orientation tools; neither replaces country-specific legal advice.

The OECD and Eurostat data are free and authoritative for macro trends. For transaction-level detail on taxes, especially in Spain, Portugal, France, Italy, Greece, Croatia, and Austria, the respective countries' tax authority websites and notarial federation sites publish current rates. Cross-reference any third-party summary against the official source before entering a figure into your model.

Once your spreadsheet is populated with real inputs from two or more markets, you'll have a decision tool that most buyers never build. You'll see which property's cashflow is sensitive to occupancy shifts, which one carries meaningful FX risk, and which one has a realistic path to break-even on rental income alone. That framing, rather than a comparison of listing prices alone, is what separates a confident cross-European second home purchase from an expensive guess.