The Ultimate Guide to Rental Yields in the UK in 2023

The UK property market - and the rental market in particular - has always been an enticing field for domestic and international investors. Interest rates are rising and, property prices are dropping, making property investment even more appealing. However, with the ever-changing dynamics, understanding the significance and implications of rental yields has become increasingly crucial in 2023.

There are several investment strategies to implement in the UK property market but opting for house in multiple occupation (HMO) properties has proved to be a successful, and popular, choice. In this article, we’ll provide a comprehensive guide to rental yields in the UK in 2023 and show you how Property Data can help your investment flourish.

What are Rental Yields?

Rental yield is a fundamental concept in the property investment landscape. At its core, it represents the annual return potential on a property investment, relative to its market value. In essence, the rental yield gives investors a percentage figure that shows the annual rental income the property can generate in relation to its purchase price.

There are a few different ways to calculate rental yields. This includes:

  • Gross Rental Yield: This is the basic form of rental yield calculated by taking the annual rental income, dividing it by the property value, and then multiplying by 100 to get a percentage.
  • Net Rental Yield: A more precise metric, net rental yield takes into account the costs associated with the property, such as maintenance, property management fees, insurance, and other associated expenses. This gives a clearer picture of the actual return an investor can expect after expenses. Net rental yield provides a more accurate representation of the property's profitability.

So investors often prefer to focus on the net yield, although both metrics have their respective merits and applications. Understanding rental yield is important because it offers insights into a property's income potential over the long term. It helps investors compare various properties in different locations, assess the viability of their investment, and devise strategies to optimise returns.

Future Predictions for Rental Yields

The current landscape for rental yield in the UK is being shaped by a spike in demand for properties and a low supply. The UK has seen a month-on-month increase in demand since May 2020, but there are more than a quarter fewer homes available now than pre-pandemic times.

As of 2023, the estimated rental yield is around 4.75%. So anything above this number would qualify as a good rental yield. You can often find slightly higher yields by moving north up the UK to areas like Manchester, Sheffield and Newcastle.

Moving forward, it’s being predicted that rent across the UK will rise by up to 9.5 % over the course of the next five years. London, understandably, will look to experience the most growth of around 12.5 %.

What is an HMO?

House in Multiple Occupation (HMO), is a term familiar to many in the UK property market. An HMO refers to a property where three or more unrelated individuals live, sharing facilities like the bathroom and kitchen. Essentially, it's a living arrangement where several tenants coexist in one property but have separate tenancy agreements.

Why are HMOs Popular among Investors?

HMOs are one of the more popular property investment strategies, and with good reason. There are several reasons why investing in an HMO is appealing, including:

Higher Rental Yields

HMOs often yield higher returns compared to single-let properties. This is because renting out individual rooms typically generates more total income and higher average renting yield than renting the entire property to a single tenant or family. Gross rental yields for HMOs typically falls between 8 to 12 %, whereas single-let properties only reach 5 to 7 %.

Risk Diversification

If one tenant in an HMO vacates, the landlord still receives rent from the other occupants. This reduces the risk of complete loss of rental income, which might occur in a vacant single-let property. So an HMO allows you to diversify your portfolio which lowers the risk of your investment.

Demand

With increasing UK house prices and housing costs, as well as the need for flexible accommodation in university towns and bustling cities, there's a consistent tenant demand for HMOs. This high demand can ensure a solid investment with high capital growth as this is where the greatest demand for HMOs lie.

The Challenges and Risks of HMO Investment

While HMOs can present lucrative opportunities for property investors, they also come with their own set of challenges and potential pitfalls. Understanding these is important for any investor considering delving into the HMO market.

Let’s go over a few of the biggest challenges and risks of HMO investment:

  • Regulatory Compliance: HMOs are heavily regulated in the UK, with licensing requirements that vary by local council. The Management of Houses in Multiple Occupation (England) Regulations 2006, for instance, details obligations for landlords regarding fire safety, water supply, drainage, and waste disposal. Non-compliance can lead to hefty fines.
  • Higher Management Demands: Managing an HMO is often more time-consuming and demanding than other rental properties. From ensuring shared spaces are maintained to managing potential conflicts between tenants, HMOs require a more hands-on approach.
  • Turnover and Vacancies: While HMOs can diversify risk due to multiple tenants, they can also see a higher turnover rate. This can increase wear and tear on the property and result in more frequent periods of vacancies for individual rooms.
  • Increased Maintenance Costs: Due to shared facilities and more occupants, wear and tear in HMOs is typically higher than in single-let properties. This can translate to more frequent repairs and replacements, leading to higher maintenance costs.
  • Mortgage and Insurance Complexities: Not all mortgage lenders offer products for HMOs, and those that do might have stricter criteria. Similarly, insuring an HMO can be more complex and potentially more expensive than standard landlord insurance.
  • Tenant Cohesion: A harmonious tenant mix is essential in HMOs. Disputes or disagreements between tenants can lead to a stressful environment, potentially resulting in early lease terminations or disputes for the landlord to mediate.
  • Economic Factors: While HMOs can offer a buffer against economic downturns due to multiple rent sources, they can also be sensitive to changes in the local economy. For instance, if an HMO is based in a university town and there's a significant drop in student numbers, it can impact rental demand.

By understanding the risks, you’re in a much better position to make a prudent investment that will pay off. So keep these in mind and you should be able to reap the benefits of HMO investment.

How to Use PropertyData.co.uk to Maximise Rental Yields

Property Data offers a variety of useful tools for property investors in the UK. It provides invaluable data-driven insights that can significantly aid in identifying and analysing potential HMO properties. This ranges from learning about nearby transport links to focusing on specific UK cities and postcodes. Here's a step-by-step guide on how to harness its capabilities effectively:

Research tools

Property Data provides you with a wide range of research tools to help you find and assess potential investment areas. You can:

  • Identify Areas:Use the 'Rental Yield' hotspot table to spot areas offering the highest rental yields for long let or HMO.
  • Filter for Precision:Use Postcode Data to filter postcode districts by specific parameters like property type or price range. Find areas best suited to your investment goals.
  • Occupancy Characteristic Statistics

    • Demographics: Get insights into the population makeup of an area by looking Local Data. This data can help determine if the locality is conducive for HMOs. For instance, areas with a high student population may be ideal.
    • Tenancy Types: Review the most common types of tenancies in an area. High numbers of shared tenancies might indicate a demand for HMOs.

    On Market Sourcing

    Find the right on or off-market properties using the sourcing tools. You can:

    • View Listings: Browse through properties currently on the market that fit the HMO criteria. Look for larger properties that can be converted or existing HMOs.
    • Direct Contact: Some listings might provide direct contact to agents or sellers, facilitating quicker transactions.

    Evaluate Opportunities

    There are several due diligence tools you can use to help you perform due diligence around your potential investment. This includes:

    • Property Valuation: Use the platform's tools to get an estimated market value of your potential HMO property.
    • Comparable: Compare the property with similar ones in the area. This helps in understanding if you're getting a fair deal and potential room for negotiation.

    Find Your Next HMO Investment and Reap the Benefits

    The current landscape of the UK property market is one that is hungry for more properties. This demand for properties has created an excellent window of opportunity for investors. However, it takes a good understanding of rental yields to know what a good deal looks like

    Thankfully, there are plenty of tools and resources available at Property Data that are designed to make finding the right investment easier. From property valuation tools to finding new locations and assessing demographics, you can harness these tools to find the right location to invest in and find properties that will maximise your HMO yields.

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    Transparent data promise

    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?

    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.

    Where does the raw data come from?

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

    How do you know the square footage of properties?

    We use proprietary technology to read the square footage of properties from agent floorplans. Although we cannot determine the square footage for all properties, we can usually get sufficient coverage. Agents are sometimes known to inflate square footage, and this should be borne in mind as a weakness of this data.

    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?

    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.

    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 2024-03-01, 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?

    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.

    Where does the raw data come from?

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

    How do you know the square footage of properties?

    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 2024-03-01, 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.

    Zoopla Zed-index

    What time period does the data cover?

    The data covers transactions in the last six years

    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 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.

    How is the raw data processed?

    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.