In 2023, houses in multiple occupation (HMO) and flats in multi-unit blocks saw the highest property yield in the United Kingdom. In the second quarter of the year, the rental yield of HMOs was *** percent. Business mortgages, or buy-to-let (BTL) mortgages, are a loan sold to property investors, rather than to people who want to purchase a home to live in.

Business mortgages, or buy-to-let (BTL) mortgages, are a loan sold to property investors, rather than to people who want to purchase a home to live in. As of the fourth quarter of 2019, the majority of landlords who took a BTL mortgage loan chose a fixed rate, with more than *** in ***** mortgagers opting for a **** year fixed rate term.

The rental yield for buy-to-let properties varied widely across different property types in the United Kingdom. Business mortgages, or buy-to-let (BTL) mortgages, are a loan sold to property investors, rather than to people who want to purchase a home to live in. Semi-detached houses had the lowest rental yield at **** percent in the second quarter of 2022. Though a higher yield suggests profitability, it is also indicates higher risk.

Price to Rent Ratio in the United States increased to 134.04 in the fourth quarter of 2024 from 133.46 in the third quarter of 2024. This dataset includes a chart with historical data for the United States Price to Rent Ratio.

Business mortgages, or buy-to-let (BTL) mortgages, are a loan sold to property investors, rather than to people who want to purchase a home to live in. As of the fourth quarter of 2019, multi-unit freehold blocks (MUFB) saw the highest average property value at over ***** thousand British pounds.

Real Estate Breakeven Analysis for U.S. Home Types

Buy vs Rent Comparison Across Markets

By Zillow Data [source]

About this dataset

This dataset provides a comprehensive analysis of the current real estate situation in the United States. It includes breakeven analysis charts that compare buying vs renting across major U.S. markets. This dataset contains various metrics such as home types, housing stock, price-to-income ratio, cash buyers, mortgage affordability and rental affordability to name a few. This data has been compiled using Zillow's own data along with TransUnion financing survey data and the Freddie Mac Primary Mortgage Market Survey to provide an accurate understanding of each metro area’s market health and purchasing power for buyers and renters alike. By downloading this information you can compare different regions based on size rank and other factors to get full insights regarding their potential fit for your needs or investments strategies as well as any potential risks associated with each region's housing market health

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How to use the dataset

This dataset is for real estate professionals, owner-occupants, potential buyers and renters who are interested in understanding which U.S. markets offer the most favorable home buying or rental opportunities from a financial perspective over the long term.

The “Real Estate Breakeven Analysis for U.S Home Types” dataset contains data pulled from Zillow's current and forecasted housing market metrics across many different real estate regions in the United States including cities, counties, states, metro areas and combined statistical areas (CSAs). The data includes several measures of affordability such as median price-to-rent ratio (MedPR), median breakeven horizon (MedBE) - which refers to how long it takes to make up purchase costs when compared with renting; cash purchaser share; mortgage rate; mortgage affordability indices; rental affordability rates etc.

In order to analyze and compare buying vs renting decisions across various regions in the US this dataset provides breakeven analysis at various levels of geographies i.e., state names, region types (city/metro area/county) and show how long it will take homeowners to break even on their purchase costs when compared with renting in that region over a longer period of time using discounted cash flow methodology. This information helps people understand what type of transaction is a better fit for them by weighing short term vs long term goals accordingly by evaluating these different factors related to housing metrics carefully before making financial decisions about purchasing or renting properties in desired location(s).

To use this dataset one can use either basic filters like RegionType or RegionName or more detailed filter criteria like CountyName, City name , Metro area name , State Name etc . For example if someone wanted to look at properties available for rent only then they can apply filters based on Province Type =‘Rental’ Also one can further refine searches based on filtering them with defined SampleRate , Median Price – To – Rent Ratio …..etc . This could be useful if seekers would want only specific type of property like Condominium/Coop /Multifamily 5+ Units /Duplex Triplex listing etc …and then apply other parameters like Cash Buyers percent , Mortgage Affordability Rate….etc ..in order narrow down search results while looking at Breakeven scores /horizons in their target locations . One should take advantages of all relevant parameters while searching through data before making any decision related with owning rental properties so that they can make sure best possible investment decision given

Research Ideas

• Visualizing changes in real estate trends across regions by comparing price to rent ratios, mortgage affordability indices and cash buyers over time.
• Market segmentation analysis based on region-level market characteristics such as negative equity data, rental affordability, median house values and population size.
• Predicting housing demand within a particular region based on its breakeven horizon or price to rent ratio

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: BreakEven_2017-03.csv | Column name | Description | |:----------------|:----------------------------------------------------...

Landlord Insurance Market Outlook

According to our latest research, the global landlord insurance market size reached USD 38.2 billion in 2024, reflecting robust demand for risk mitigation among property owners. The market is expanding at a strong pace with a CAGR of 7.6% from 2025 to 2033, positioning the industry to attain a forecasted value of USD 73.8 billion by 2033. This growth trajectory is underpinned by the rising number of rental properties, increasing awareness of property-related risks, and the growing need for comprehensive protection solutions for landlords worldwide.

One of the primary growth factors driving the landlord insurance market is the ongoing expansion of the global real estate sector, especially in urban areas. The surge in urbanization has resulted in a significant increase in the number of rental properties, both residential and commercial. As more individuals and entities invest in real estate for rental income, the necessity to safeguard these investments against unforeseen events such as fire, natural disasters, vandalism, and tenant-related damages has become paramount. This heightened risk awareness has led to a greater adoption of landlord insurance policies, especially those offering comprehensive coverage, thus fueling market growth. Additionally, the proliferation of buy-to-let investments and the professionalization of property management have further contributed to the demand for specialized landlord insurance products.

Another significant factor contributing to the growth of the landlord insurance market is the evolution of insurance products and distribution channels. Insurers are responding to changing consumer preferences by offering more tailored and flexible policies, including customizable coverage options that cater to the unique needs of individual landlords and commercial property owners. The rise of digital platforms and online distribution channels has also made it easier for landlords to compare, purchase, and manage insurance policies. This increased accessibility, combined with competitive pricing and enhanced customer service, has made landlord insurance more attractive and convenient for a broader range of property owners. Furthermore, technological advancements such as data analytics and artificial intelligence are enabling insurers to better assess risks and streamline claims processes, thereby improving the overall value proposition for policyholders.

Regulatory developments and the increasing involvement of financial institutions are also shaping the landlord insurance market. In many regions, regulatory bodies are mandating insurance coverage for rental properties, especially for those financed through mortgages or commercial loans. This regulatory push has created a baseline demand for landlord insurance, ensuring a steady influx of new policyholders. Additionally, the integration of landlord insurance offerings into bancassurance and other financial service platforms has expanded the reach of these products, allowing insurers to tap into new customer segments. As the regulatory landscape continues to evolve, it is expected to further support market growth by promoting transparency, standardization, and consumer protection.

From a regional perspective, the landlord insurance market exhibits distinct growth patterns, with North America and Europe leading in terms of market share and product innovation. Both regions benefit from mature real estate markets, high insurance penetration rates, and stringent regulatory frameworks. In contrast, the Asia Pacific region is emerging as a high-growth market, driven by rapid urbanization, increasing foreign investment in real estate, and rising awareness of insurance solutions. Latin America and the Middle East & Africa, while still developing, are witnessing growing interest in landlord insurance as property markets expand and risk management practices become more prevalent. Each region presents unique opportunities and challenges, influenced by local economic conditions, regulatory environments, and cultural attitudes toward insurance.

Coverage Type Analysis

The landlord insurance market is segmented by coverage type into property damage, liability protection, loss of rental income, and others. Among these, property damage coverage remains the most sought-after, accounting for the largest share of the market in 2024. This dominance is attributed to the high incidence of risks such as fire, natural disa

Business mortgages, or buy-to-let (BTL) mortgages, are a loan sold to property investors, rather than to people who want to purchase a home to live in. As of the second quarter of 2022, the loan-to-value (LTV) ratio of rental properties in the United Kingdom was between ** percent and ** percent, depending on the property type. Flats had the highest LTV ratio at ** percent, meaning that the amount of the loan for the purchase of a rental flat amounted to ** percent of the property value. In the same period, flats had the second-lowest average loan size from all property types.

The Residential Mortgage Arrears and Repossessions Statistics detail quarterly developments in the number and value of mortgages in arrears, restructured mortgages, in legal proceedings and repossessed properties. Data are broken down by principal residences (PDH) and buy-to let properties. Data are published on a quarterly basis and are subject to revisions

The robust growth of the United States Rent-To-Own Market in the coming years is largely driven by tightened lending standards prevalent among major and subprime lenders. This trend is compelling individuals to seek alternative avenues for accessing essential items such as appliances and computers, fueling the demand for rent-to-own services. The market valued around USD 12.31 Billion in 2023 and it is evident that consumers are increasingly turning to rent-to-own arrangements to fulfill their needs amidst stringent lending conditions. Thus, regulations surrounding rent-to-own in the United States is anticipated help the market grow at a CAGR of around 6.77% from 2024 to 2031.The accelerating pace of growth in the United States Rent-To-Own Market is underscored by Verified Market Research, with substantial expansion witnessed in recent years and further anticipated in the forecasted period spanning from 2024 to 2031. The significant upward trajectory expected in the market is highlighted by the projected value of approximately USD 19.39 Billion by 2031. As flexible solutions for accessing essential goods without the burden of immediate ownership continue to be sought by consumers, the rent-to-own market is poised to flourish, catering to evolving consumer preferences and economic conditions.United States Rent-To-Own Market: Definition/OverviewThe United States Rent-to-Own Market involves tangible goods being leased with the option for eventual purchase. Regular installment payments, resembling renting, include a portion designated for potential ownership, making this option particularly attractive to individuals lacking upfront capital, conventional financing, or a robust credit history required for outright purchases. Flexibility and accessibility are offered by Rent-to-Own agreements, catering to a segment of the population that may otherwise struggle to acquire needed goods or properties.Traditionally, Rent-To-Own agreements were primarily focused on real estate transactions, but the modern rent-to-own industry encompasses a broader spectrum, including furniture, appliances, electronics, and even jewelry. The proliferation of e-commerce platforms is anticipated to significantly bolster market revenues, as enticing deals and convenience are offered to consumers by these platforms. Additionally, substantial potential exists within the Hispanic market as loyal rent-to-own customers. Despite a low unemployment rate, dwindling consumer disposable income has led to hesitancy in committing to new property rentals. Several trends, including the surge in international migration, the emergence of the Kiosk model offering low-risk entrepreneurial opportunities, and a declining US homeownership rate, are poised to influence growth. Rent-to-own contracts, also known as lease purchase provide prospective buyers with the opportunity to lease a home with the option to buy it later, contributing to a pathway to homeownership for individuals who may not qualify for traditional mortgages or lack immediate means to purchase the property outright.

The data in this data set was provided by HM Treasury and details mortgage completions on properties supported by Help to Buy: mortgage guarantee completions, by local authority, England. The data set covers the period 8 October 2013 to 30 June 2014.

The Help to Buy: mortgage guarantee scheme opened on 8 October 2013 and is available across the United Kingdom. Under the scheme the government offers lenders the option to purchase a guarantee on mortgage loans where the borrower has a deposit of between 5% and 20%. The scheme can be used for mortgages on both new build and existing homes, by first time buyers, home movers and those remortgaging. In order to qualify for a loan supported by the Help to Buy: mortgage guarantee, there are a number of eligibility criteria which are set out in the scheme rules.

The guarantee compensates participating mortgage lenders for a portion of net losses suffered in the event of repossession. The guarantee applies down to 80% of the purchase value of the guaranteed property covering 95% of these net losses. The lender therefore retains a 5% risk in the portion of losses covered by the guarantee. This ensures that the lender retains some risk in every mortgage originated. For example, the scheme is not available on buy-to-let mortgages or second homes, and the property value must be £600,000 or less.

Over the life of the scheme the government will make available up to £12 billion of guarantees, which is sufficient to support up to £130 billion of high loan-to-value (LTV) mortgages.

For further information see
Help to Buy: mortgage guarantee scheme Quarterly Statistics.

Landlord Legal Expense Insurance Market Outlook

According to our latest research, the global landlord legal expense insurance market size reached USD 4.28 billion in 2024, reflecting robust adoption across key regions. With a steady rise in demand for comprehensive risk mitigation solutions among property owners, the market is projected to expand at a CAGR of 7.1% from 2025 to 2033. By 2033, the market is forecasted to attain a value of USD 7.98 billion. The primary growth factor driving this trend is the increasing complexity of landlord-tenant relationships, coupled with a heightened awareness of the financial risks associated with rental property management.

The landlord legal expense insurance market is experiencing significant growth due to the evolving regulatory landscape and the rising incidence of tenant disputes globally. As governments introduce stricter rental regulations and tenant protection laws, landlords are increasingly exposed to legal challenges, including eviction proceedings, property damage claims, and rental arrears. This has prompted a surge in demand for specialized insurance products that not only protect landlords from the financial impact of legal proceedings but also provide access to expert legal counsel. The proliferation of rental properties, particularly in urban areas, has further amplified the need for robust legal protection, making legal expense insurance an essential component of property risk management strategies.

Another pivotal growth factor is the expansion of the rental property market, driven by urbanization, changing demographics, and the increasing preference for rental accommodation over homeownership. As the number of individual and institutional landlords rises, so does the need for insurance solutions tailored to diverse property portfolios. The growth of the buy-to-let sector and the entry of real estate investment trusts (REITs) into the residential rental market have also contributed to market expansion. These entities often require comprehensive coverage to manage large-scale portfolios, including rent guarantee and legal defense, further fueling demand for landlord legal expense insurance.

Technological advancements and the digitization of insurance distribution channels have also played a crucial role in market growth. The emergence of online platforms and insurtech solutions has made it easier for landlords to access, compare, and purchase legal expense insurance policies. This digital shift has expanded market reach, particularly among tech-savvy individual landlords and small-scale property managers, who value convenience and transparency. Additionally, the use of data analytics and artificial intelligence in underwriting and claims management has enhanced the efficiency and appeal of landlord legal expense insurance products, driving higher adoption rates across all segments.

From a regional perspective, Europe and North America continue to dominate the landlord legal expense insurance market, accounting for the majority of global revenues in 2024. This is attributed to mature insurance markets, high rental property penetration, and well-established legal frameworks supporting landlord rights. Meanwhile, the Asia Pacific region is emerging as a lucrative market, fueled by rapid urbanization, increasing foreign investment in real estate, and a growing awareness of legal risk management among property owners. Latin America and the Middle East & Africa, though still nascent, are expected to witness accelerated growth over the forecast period as regulatory reforms and rental market expansion take hold.

Coverage Type Analysis

The coverage type segment within the landlord legal expense insurance market is highly diversified, catering to the multifaceted risks faced by landlords in today’s dynamic property landscape. Eviction coverage remains a cornerstone, providing landlords with financial support and legal representation in cases where tenants breach lease agreements or refuse to vacate the prem

The Property Group is a leading real estate organization that provides expert guidance throughout the home buying and selling process. With a strong presence in Little Rock, Arkansas, the company has established itself as a trusted partner for individuals and families seeking to buy, sell, or rent properties. The Property Group's expert agents are well-versed in local market trends, ensuring that clients receive tailored solutions to their unique needs.

Through their user-friendly website, The Property Group offers a range of resources and tools for homebuyers, including exclusive property listings, neighborhood information, and real-time market reports. Whether buying or selling a home, clients can rely on the company's dedicated professionals to navigate the complex process with ease. With a focus on transparency, efficiency, and personalized attention, The Property Group has earned a reputation as a top choice for those seeking a seamless and stress-free real estate experience.

Price to Rent Ratio in Ireland increased to 113.76 in the second quarter of 2025 from 112.11 in the first quarter of 2025. This dataset includes a chart with historical data for Ireland Price to Rent Ratio.

LiveOverture is a reputable property data solutions provider that offers a wealth of information on property listings, market trends, and real estate data. The company's online presence provides insights into the property market, featuring thousands of listings, property sales data, and market analysis.

By leveraging LiveOverture's online resources, users can gain a deeper understanding of property values, trends, and market conditions, making it an invaluable resource for real estate professionals, investors, and individuals looking to buy, sell, or rent properties.

As per Cognitive Market Research's latest published report,The Europe Landlord Insurance market size will be $27,770.62 Million by 2028.The Europe Landlord Insurance Industry's Compound Annual Growth Rate will be 7.94% from 2023 to 2030. What is Driving Landlord Insurance Industry Growth?

Rising demand of rental properties

It is said that the best investment is a land investment. Population across the globe follows these proverbs and invest their saving in buying homes. The housing process in European countries were observed at its peak which were derived by the large investors. The institutional investors including private equity and pension funds has raise the houses prices in the European countries. The volume of purchases in Europe hit €64bn (£53bn) in 2020, with about €150bn value of housing stock conservatively estimated to be in the hands of such large investors. According to Preqin private database of investors, Berlin, with €40bn worth of housing assets in institutional portfolios is at top followed by London, Amsterdam, Paris and Vienna.

The data from Berlin’s Free University states that the Europe’s housing has become increasingly attractive asset class for investors owing to near-zero interest rates and cheering regulatory outlines. The data from European central bank shows that the real estate funds in the Eurozone reached €1tn in 2021 in which residential assets are consider as progressively central part. The institutional investors’ residential transactions between 2012 and 2021 was increased in Germany, Denmark followed by Netherlands.

Significant occupancy of residential and commercial properties by institutional investors led to the undersupply of housing across the continent and results in the increasing rental rates. Owing to the chronic undersupply of housing in several European countries, the population of the tenants increases which simultaneously increases the demand of rental properties in Europe. Moreover, the capability of population to purchase house is also decreasing with the increasing annual house prices. The data shows a surge in rents by 16.0 % and house prices by 38.7 % from 2010 to third quarter of 2021 in Europe. The rent and houses price in Europe has increased by 1.2 % and 9.2 % respectively from third quarter of 2021 to third quarter of 2020.

Landlord insurance is applicable to rental properties only. Hence, with the increasing demand of rental properties in Europe is driving the growth of landlord insurance market.

Increase in natural disasters is propelling market growth

Restraint of the Europe Landlord Insurance Market

Inadequate information related to landlord insurance policies.(Access Detailed Analysis in the Full Report Version)

Opportunities of the Europe Landlord Insurance Market

Introduction of new technologies in insurance industry.(Access Detailed Analysis in the Full Report Version)

What is Landlord Insurance?

Landlord Insurance is a sort of homeowner's insurance that protects homeowners against financial losses associated with rental properties. This insurance includes coverage for fire and other dangers, as well as theft and intentional damage.

Several European nations are quickly implementing landlord insurance for their buildings. Property and liability protection are two forms of coverage that are commonly included in insurance policies. Both insurance policies are designed to protect both the landlord and the renters from financial losses.

Damage to property, income replacement, liability insurance, and add-on coverage are all covered by landlord insurance. It assists clients in protecting themselves from financial losses caused by natural catastrophes, injuries, accidents, and other liability concerns.

It also provides payment for lost rent, repairs, and property replacement that are covered by landlord insurance.

Landlord liability insurance, landlord buildings insurance, landlord contents insurance, loss of rent insurance, tenant default insurance, accidental damage insurance, alternative accommodation insurance, unoccupied property insurance, and legal expenses insurance are among the various types of landlord insurance.

In Europe, several online and offline landlord insurance businesses offer solutions for both residential and commercial properties. This landlord insurance migh...

Housing Prices By Location

Why Location DOES Matter in Housing Prices

By [source]

About this dataset

The Hyderabad House Data dataset contains information on various aspects of housing in Hyderabad, India, including price, locality, furnishings, and number of bedrooms and bathrooms. This data was collected from one of the housing rental portals in Hyderabad using web scraping methods, and provides valuable insights into the city's real estate market.

The dataset includes a variety of features that will be helpful for those looking to rent or buy a property in Hyderabad. In addition to general information about the property such as price, locality, and number of bedrooms and bathrooms, the dataset also includes detailed information about furniture, tennants, and area. This data can be used to help understand the city's real estate market and make informed decisions about renting or buying a property in Hyderabad

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Guide to Using the Hyderabad House Dataset

This dataset can be used to study various aspects of housing in Hyderabad, India, including price, locality, furnishings, and number of bedrooms and bathrooms. The data was collected from one of the housing rental portals in Hyderabad using web scraping methods.

To get started, you may want to take a look at the columns in the dataset:

• Bedrooms: This column indicates the number of bedrooms in a given house.
• Bathrooms: This column indicates the number of bathrooms in a given house.
• Furnishing: This column indicates whether or not the house is furnished.
• Tennants: This column indicates whether or not tenants are allowed in the house.
• Area: This column indicates the size of the house in square feet.
• Price: This column indicates the price of rent for a given house per month.

• Locality: This column indicates the locality/location of a given house.

  With this information in mind, you can now begin to explore some questions that you may be interested in answering with this dataset!

Research Ideas

• This dataset can be used to study the relationship between housing prices and various other factors such as locality, furnishings, number of bedrooms and bathrooms, etc.

• This dataset can be used to predict future housing prices in Hyderabad based on historical data.

• This dataset can be used to study the trends in the Hyderabad real estate market

Acknowledgements

If you use this dataset in your research, please credit the original authors.

Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: Hyderabad_House_Data.csv | Column name | Description | |:---------------|:--------------| | **** | | | Bedrooms | | | Bathrooms | | | Furnishing | | | Tennants | | | Area | | | Price | | | Locality | |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit .

Premiere Property Group is a real estate company that specializes in residential and commercial properties. The company's website provides information on a wide range of properties, including vacant land, single-family homes, and multi-unit dwellings. With a strong focus on customer satisfaction, Premiere Property Group's team of experienced agents and brokers work closely with clients to understand their unique needs and preferences.

Premiere Property Group's website offers a wealth of information for those looking to buy, sell, or rent properties. The company's extensive property listings are regularly updated to reflect the latest market trends and developments. By partnering with Premiere Property Group, clients can gain insights into the local real estate market, receive expert advice, and navigate the buying and selling process with confidence.