Buy-to-Let vs. Short-Term Lets: Which Offers Better Returns?

As the property market evolves, investors face a growing dilemma when choosing between traditional buy-to-let properties and short-term rental models like those popularised by platforms like Airbnb. Investors have long viewed buy-to-let investments as a stable income stream, but the rise of short-term lets has introduced a more dynamic, and at times riskier, alternative. This article comprehensively analyses both rental strategies, focusing on their financial performance, market trends, risks, and regulatory considerations. By comparing the two approaches, property investors and landlords can make well-informed decisions regarding their rental strategy.

Understanding Buy-to-Let and Short-Term Lets

Buy-to-let and Short-Term Lets represent two distinct approaches to property rental. Let’s explore each model in more detail:

Buy-to-Let

In a traditional buy-to-let investment, landlords lease properties to tenants for extended periods, often under Assured Shorthold Tenancy (AST) agreements. The primary advantage of this model lies in its ability to provide a stable and predictable income, typically in the form of monthly rental payments. However, landlords are still susceptible to tenant turnover and fluctuations in the broader rental market, which could impact rental prices.

Key Characteristics:

  • Stable Income: Regular monthly rental payments.
  • Tenant Turnover: This can result in vacant periods between tenancies.
  • Capital Appreciation: Potential for long-term property value growth.

Short-Term Lets

On the other hand, short-term lets rent out on a nightly or weekly basis, often through platforms like Airbnb. This model can generate higher returns due to the premium pricing for short stays, particularly in tourist destinations or popular city centres. However, the increased rental income comes from more intensive management and higher operational costs, including cleaning, maintenance, and guest communication.

Key Characteristics:

  • Higher Returns: Potential for higher nightly rates.
  • Operational Complexity: Frequent turnover and higher management costs.
  • Market Volatility: Demand can fluctuate seasonally or due to local events.

Profitability and Return on Investment (ROI)

When evaluating profitability, investors should consider key metrics such as rental yield, occupancy rates, and the associated costs for each rental model.

Rental Yields

Regarding rental yields, short-term lets often offer a higher return per night, particularly in high-demand locations. However, this income is not always as stable or predictable as buy-to-let rents. On the other hand, buy-to-let properties typically offer lower yields but provide more consistency, making them attractive to those seeking long-term stability.

Occupancy Rates

Buy-to-let properties generally experience steady occupancy rates, especially in suburban or commuter belt areas where demand remains relatively stable. In contrast, short-term lets tend to see higher occupancy in peak seasons or special events but can suffer from vacancy periods during off-peak months.

Costs and Fees

  • Buy-to-let generally incurs lower management costs. However, landlords may face potential void periods between tenancies and maintenance expenses, especially for older properties.

  • Short-Term Lets: Higher operational costs due to frequent tenant turnover. Costs include cleaning, management fees, and the upkeep of amenities for guests.

Example Cost Breakdown:

Expense Category Buy-to-Let Short-Term Let
Management Fees £0–£150/month £150–£300/month
Maintenance Costs £300/year £600–£1,000/year
Cleaning Costs £0 £40–£60/cleaning

ROI Calculation Example:

  • Buy-to-Let Example: A £250,000 property with a 4.5% yield would generate approximately £11,250 per year in rental income.
  • Short-Term Let Example: The same property, rented as a short-term let in a high-demand area, could generate £30,000+ annually, assuming an average nightly rate of £150 and 80% occupancy.

ROI Example Explained:

Imagine two properties in the exact location—one a buy-to-let and the other a short-term rental. The buy-to-let might offer an annual income of £11,250 with a 4.5% yield, while the short-term let could bring in £30,000. With higher maintenance costs, the net ROI might be closer to 7%. The buy-to-let offers lower returns but with fewer complications.

Market Trends and Demand Shifts

Understanding current market conditions is critical in determining the potential returns of any property investment strategy.

Rental Market Trends in the UK

In recent years, inflation, rising mortgage rates, and post-pandemic recovery have shaped the UK's rental market. While buy-to-let demand remains relatively stable, short-term lets have gained significant traction, particularly in tourist destinations and urban areas with a high influx of visitors.

Growth in Demand for Short-Term Lets

In the short term, in tourist hotspots like London, Edinburgh, or the Lake District, let's see substantial growth, benefiting from the global boom in domestic and international travel. Meanwhile, buy-to-let properties in suburban areas have continued to offer reliable, steady income, especially for landlords targeting long-term tenants in cities like Birmingham, Manchester, and Liverpool.

Legislative and Regulatory Considerations

Both models are affected by local regulations. Short-term lets have faced increasing scrutiny in some urban centres, with councils imposing stricter rules, such as mandatory registration, limits on rental days, or outright bans in certain areas. Conversely, buy-to-let landlords have faced regulatory challenges related to tenancy agreements, landlord licensing, and changes to tax laws, such as the reduction in mortgage interest relief under Section 24.

Risks and Challenges

While both strategies offer the potential for significant returns, they also come with inherent risks.

Buy-to-Let Risks:

  • Tenant Issues: Rent arrears or eviction processes can cause financial strain.
  • Market Fluctuations: Property prices and rental rates may fluctuate based on the broader economic climate.
  • Regulatory Compliance: Adhering to ever-changing landlord regulations, including tax laws, can be complex.

Short-Term Let Risks:

  • Market Fluctuations: Demand can fluctuate dramatically based on seasonality and local events.
  • Stricter Regulations: Local authorities may impose restrictions, reducing the profitability of short-term lets.
  • Higher Operational Demands: The need for constant property maintenance and guest management can increase costs and time investment.

Risk Mitigation Strategies:

To mitigate these risks, landlords can diversify their portfolios, seek insurance, and leverage platforms like PropertyData to track market trends and ensure they remain compliant with evolving regulations.

Legal and Regulatory Considerations

Both investment strategies require landlords to navigate a complex legal landscape.

Buy-to-Let Regulations:

  • Tenancy Laws: Landlords must adhere to tenancy agreements governed by the Housing Act, including legal obligations for repairs, deposits, and tenant rights.
  • Taxation: Changes to tax laws, such as the reduction of mortgage interest relief (Section 24), have impacted buy-to-let landlords.

Short-Term Let Regulations:

  • Local Regulations: Many local councils have introduced strict rules surrounding the operation of Airbnb-style rentals, including licensing requirements and limits on the number of nights a property can be rented out.
  • Planning Laws: Some areas have imposed planning restrictions, making it more challenging to convert properties into short-term lets.

Staying compliant with these regulations is critical to maintaining a profitable investment. PropertyData’s tools can help investors navigate these challenges and stay informed about changes in the law.

Case Studies Comparisons

To offer practical insight, here are two case studies illustrating the potential returns from both strategies:

Case Study 1: Transitioning from Buy-to-Let to Short-Term Lets

A landlord in a city centre converted their buy-to-let property into a short-term rental. Initially generating £14,000 annually with a buy-to-let model, after transitioning to short-term lets, the same property generated £25,000 annually, even after accounting for increased operational costs.

Case Study 2: Buy-to-Let Success

An investor in the commuter belt area chose a buy-to-let model. Despite the area not being a prime tourist destination, long-term tenants provided steady rental income, leading to consistent returns and a healthy capital appreciation over five years.

Conclusion

Both strategies offer distinct advantages and challenges in the debate between buy-to-let and short-term lets. Buy-to-let provides stability and long-term capital growth, while short-term lets offer the potential for higher returns but with greater operational demands and market volatility. Ultimately, your choice should depend on location, market conditions, personal risk tolerance, and investment goals.

For more insights on market trends, property values, and rental yields, investors can leverage PropertyData’s analytical tools to make informed decisions that align with their objectives.

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Where does the raw data come from?

Property listings seen on rightmove.co.uk, zoopla.co.uk and onthemarket.com.

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Duplicates from multiple sources are matched and reconciled as far as possible. Listings with obvious errors, where price or number or bedrooms appear out of range, are discarded.

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Averages shown are the interquartile mean, a type of average that is insensitive to outliers while being its own distinct parameter. The 80% range means that 80% of the listed properties fall inside this range.

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Property listings seen on rightmove.co.uk, zoopla.co.uk and onthemarket.com.

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How often is the data updated?

The data is updated in near real-time.

What time period does the data cover?

This is a real-time market snapshot - the data covers currently listed properties. Once properties are removed from the portal, they are soon removed from this tab.

How is the raw data processed?

Duplicates from multiple sources are matched and reconciled as far as possible. Listings with obvious errors, where price or number or bedrooms appear out of range, are discarded.

What are the statistics used?

The average shown is the interquartile mean, a type of average that is insensitive to outliers while being its own distinct parameter. The 80% range means that 80% of the listed properties fall inside this range.

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Property "price paid" data provided by the Land Registry.

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Averages shown are the interquartile mean, a type of average that is insensitive to outliers while being its own distinct parameter. The 80% range means that 80% of the listed properties fall inside this range.

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Property "price paid" data provided by the Land Registry, and Energy Performance Certificate (EPC) data provided by Department for Levelling Up, Housing & Communities.

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We match the Land Registry data to EPC data provided by the Department for Levelling Up, Housing & Communities. Due to the fact that not all properties sold have had an EPC and vagaries of addressing in the UK, we are not able to determine the square footage of all properties, but we can usually get sufficient coverage.

How often is the data updated?

The private paid data is updated once per month when released by the Land Registry, typically towards the end of each calendar month covering up to the end of the previous calendar month. The energy performance certificate database is updated monthly.

What time period does the data cover?

You can customise the time period using the filter at the top of the view. The default time period is up to 9 months back from today's date. The latest data covers the period up to 2024-12-30, although some sales that took place before this date may still be added in the coming months.

How is the raw data processed?

No additional processes are applied to this data.

What are the statistics used?

The average shown is the interquartile mean, a type of average that is insensitive to outliers while being its own distinct parameter. The 80% range means that 80% of the listed properties fall inside this range.

Where does the raw data come from?

Property listings seen on rightmove.co.uk, zoopla.co.uk and onthemarket.com.

How often is the data updated?

The data is updated in near real-time.

What time period does the data cover?

This is a real-time market snapshot - the data covers currently listed properties. Once properties are removed from the portal, they are soon removed from this tab.

How is the raw data processed?

Duplicates from multiple sources are matched and reconciled as far as possible. Listings with obvious errors, where price or number or bedrooms appear out of range, are discarded.

What are the statistics used?

The average shown is the interquartile mean, a type of average that is insensitive to outliers while being its own distinct parameter. The 80% range means that 80% of the listed properties fall inside this range.

Where does the raw data come from?

Room let listings on SpareRoom, the UK's biggest room letting website.

How often is the data updated?

The data is updated in near real-time.

What time period does the data cover?

This is a real-time market snapshot - the data covers currently listed properties. Once properties are removed from SpareRoom, they are soon removed from this tab.

How is the raw data processed?

Listings with obvious errors, where price or number or bedrooms appear out of range, are discarded.

What are the statistics used?

The average shown is the interquartile mean, a type of average that is insensitive to outliers while being its own distinct parameter. The 80% range means that 80% of the listed properties fall inside this range.

Where does the raw data come from?

Property listings seen on rightmove.co.uk, zoopla.co.uk and onthemarket.com.

How often is the data updated?

The data is updated in near real-time.

What time period does the data cover?

This is a real-time market snapshot - the data covers currently listed properties. Once properties are removed from the portal, they are soon removed from this tab.

How is the raw data processed?

Duplicates from multiple sources are matched and reconciled as far as possible. Listings with obvious errors, where price or number or bedrooms appear out of range, are discarded. Yields are calculated by comparing only properties with the same number of bedrooms, e.g. 3-bedroom properties for rent with 3-bedroom properties for sale.

What is the yield calculation used?

The calculation used is (average_weekly_asking_rent * 52 / average_asking_price), expressed as a percentage. It is a top-line gross yield, meaning no expenses are considered.

What are the statistics used?

The average shown is the interquartile mean, a type of average that is insensitive to outliers while being its own distinct parameter. The 80% range means that 80% of the listed properties fall inside this range.

Where does the raw data come from?

Property listings seen on rightmove.co.uk, zoopla.co.uk and onthemarket.com.

How often is the data updated?

The data is updated in near real-time.

What time period does the data cover?

This is a real-time market snapshot - the data covers currently listed properties. Once properties are removed from Zoopla, Rightmove or Spareroom, they are soon removed from this tab.

How is the raw data processed?

Duplicates from multiple sources are matched and reconciled as far as possible. Yields are calculated by comparing only properties with the same number of bedrooms, e.g. 3-bedroom properties for rent with 3-bedroom properties for sale. For the SpareRoom data, hypothetical properties consisting of two to six average double rooms with shared bathrooms are used to derived average rent. For all sources, listings with obvious errors, where price or number or bedrooms appear out of range, are discarded.

What is the yield calculation used?

The calculation used is (average_weekly_asking_rent * 52 / average_asking_price), expressed as a percentage. It is a top-line gross yield, meaning no expenses are considered.

What are the statistics used?

The average shown is the interquartile mean, a type of average that is insensitive to outliers while being its own distinct parameter. The 80% range means that 80% of the listed properties fall inside this range.

Where does the raw data come from?

Property "price paid" data provided by the Land Registry.

How often is the data updated?

Once per month when released by the Land Registry, typically towards the end of each calendar month covering up to the end of the previous calendar month.

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The data covers transactions in the last six years

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No additional processes are applied to this data.

What are the statistics used?

The average shown is the interquartile mean, a type of average that is insensitive to outliers while being its own distinct parameter. The 80% range means that 80% of the listed properties fall inside this range.

Where does the raw data come from?

Property listings seen on rightmove.co.uk, zoopla.co.uk and onthemarket.com.

How often is the data updated?

The listings data is updated in near real-time. The Land Registry data is updated once per month when released, typically towards the end of each calendar month covering up to the end of the previous calendar month.

What time period does the data cover?

The price paid data shown goes back to January 2015. The listings data is a real-time market snapshot - the data covers currently listed properties. Once properties are removed from the portal, they are soon removed from this tab.

How is the raw data processed?

Duplicates from multiple sources are matched and reconciled as far as possible. Listings with obvious errors, where price or number or bedrooms appear out of range, are discarded.

What are the calculations used?

Average sales per month are for the last 3 finalised months. Turnover is average sales per month divided by total for sale. Inventory is 100 divided by turnover.

Where does the raw data come from?

Property listings seen on rightmove.co.uk, zoopla.co.uk and onthemarket.com.

How often is the data updated?

The listings data is updated in near real-time. The Land Registry data is updated once per month when released, typically towards the end of each calendar month covering up to the end of the previous calendar month.

What time period does the data cover?

This is a real-time market snapshot - the data covers currently listed properties. Once properties are removed from the portal, they are soon removed from this tab.

How is the raw data processed?

Duplicates from multiple sources are matched and reconciled as far as possible. Listings with obvious errors, where price or number or bedrooms appear out of range, are discarded.

Where does the raw data come from?

We receive data on the extent and corporate ownership of all land titles in England & Wales from the Land Registry.

How often is the data updated?

The data is updated once per month when released, typically in the first few days of each calendar month.

What time period does the data cover?

This is an ownership snapshot - the data represents ownership as recorded by the Land Registry at the last monthly export.

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No additional processes are applied to this data.

Where does the raw data come from?

We source different expert forecasts Savills, Knight Frank, OBR

How often is the data updated?

The data is updated annually when new forecasts are released, typically towards the beginning of the year.

How is the raw data processed?

We calculate a consensus forecast using a simple mean average.