View weekly updates and historical trends for 30 Year Mortgage Rate. from United States. Source: Freddie Mac. Track economic data with YCharts analytics.

As of the end of March 2025, the average mortgage interest rate for Australian owner-occupier borrowers was around *** percent. In comparison, the average investor interest rate was approximately *** percent. These rates refer to outstanding housing loans from banks and registered financial corporations. New loans financed in that month had even similar interest rates, at *** percent for owner-occupiers and *** percent for investors, respectively.

Fixed 30-year mortgage rates in the United States averaged 6.40 percent in the week ending November 21 of 2025. This dataset provides the latest reported value for - United States MBA 30-Yr Mortgage Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Mortgage interest rates in Italy decreased substantially between 2013 and 2021 before rising in the following years. As of the first quarter of 2025, the mortgage interest rates amounted to **** percent — lower than the rate in the same period in the previous year. A slowly recovering market Despite not reaching the pre-crisis levels, an increase in the number of transactions in the residential real estate market as well as the volume of mortgages stipulated for house purchase indicate a positive trend for the sector in Italy. Homeownership in Italy reached **** percent in 2021, one of the highest rates in Western Europe. Low interest rates, especially when compared to other European countries, and decreasing house prices led to a renewed interest in the real estate market in Italy. Milan, an attractive destination for investments In recent years, more than in the past, thanks to its role as a capital of business and finance as well as an innovation hub, Milan was able to attract human capital and investments, both domestic and foreign. This ability to grow and innovate was also reflected in the real estate market, which was the most dynamic in the country. Transactions in residential real estate in Milan increased steadily since 2012, except for 2020, and so did prices: some areas of the city are among the most expensive in the country to buy a property.

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. In 2022, the five-year fixed mortgage interest rate for a BTL property in the United Kingdom was **** percent, which was an increase by **** percent compared to the same quarter of 2021. Conversely, the 10-year mortgage rate decreased from **** percent to *** percent. The vast majority of UK landlords had a fixed mortgage, with 5-year fix being the most popular mortgage term.

Average Rates for First Lien (Primary Residence: 6.588%, Investment Property: 7.890%, Second Homes: 7.043%) and Subordinate Lien (Primary Residence: 4.399%, Investment Property: 6.974%, Second Homes: 8.240%).

After a period of record-low mortgage interest rates, the cost of mortgage borrowing in Germany surged in 2022. In 2019, mortgage rates declined notably, falling as low as **** percent in December 2020. This downward trend reversed in 2021, as mortgage rates started to gradually pick up. Five-to-ten-year mortgage loans had the lowest rates in March 2025 at **** percent, while floating rate mortgages up to one year were the most expensive at **** percent. Mortgages with over **-year fixed period – the most popular loan type among homebuyers — had an interest rate of **** percent. Why did mortgage rates in Germany increase? In 2022, the annual inflation rate in Germany experienced a swift rise, prompting the central bank to raise interest rates to counter this surge. The European Central Bank (ECB) is responsible for determining Germany's central bank interest rate. In July 2022, following a prolonged period of stability, the average interest rates in Germany began a steady rise, which persisted consistently thereafter.  This increase is intended to stabilize prices, but it also means higher borrowing costs for those seeking mortgages. Downturn in Germany's home loan borrowing From 2022 onward, the gross residential mortgage lending in Germany fell dramatically. Besides the higher interest rates, the downturn can be explained by the slowed pace of economic growth, which makes individuals and businesses more cautious about big investments such as buying a home. Additionally, the German housing market suffers a chronic undersupply, meaning that homebuyers often struggle to find an affordable home to purchase.

Jumbo 30-Year Fixed Mortgage Rates

Zillow Home Value Forecast and Cash Buyer Data

By Zillow Data [source]

About this dataset

This dataset tracks the average jumbo mortgage rate quoted on Zillow Mortgages for a 30-year, fixed-rate, jumbo mortgage in one-hour increments during business hours. It provides insight into changes in the housing market and helps consumers make wiser decisions with their investments. In addition to tracking monthly mortgage rates, our dataset also covers consumer's home types and housing stock, cash buyer data, Zillow Home Value Forecast (ZHVF), negative equity metrics, affordability forecasts for both mortgages and rents as well as historic data including historical ZHVI and household income. With this unique blend of financial and real estate information, users are empowered to make more informed decisions about their investments. The data is updated weekly with the most recent statistics available so that users always have access to up-to-date information

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How to use the dataset

How to Use This Dataset:

• To start exploring this dataset, identify what type of home you are interested in by selecting one of the four categories: “all homes” (Zillow defines all homes as single family, condominiums and coops with a county record); multifamily 5+; duplex/triplex; or condos/coops.
• Understand additional data products that are included such as Zillow Home Value Forecast (ZHVF), Cash Buyers % share, affordability metrics like mortgage affordability or rental affordability and historical ZHVI values along with its median value for particular households or geographies which needs deeper insights into other endogenous variables such detailed information like how many bedrooms a house has etc.

• Choose your geographic region on which you would want to collect more information– regions could include city breakdowns from nationwide level down till specific metropolitan etc . Also use special crosswalks available if needed between federally defined metrics for counties / metro areas combined with Zillow's own ones for greater accuracy when analysing external facors effect on data . To download all datasets at once - click here. .

• Gather more relevant external factors for analysis such as home values forecasts using our published methodology post given url , further to mention TransUnion credit bureau related debt amounts also consider median household incomes vis Bureaus of Labor Cost Indexes ; All these give us greater dimensional insights into market dynamics affecting any particular region finally culminating into deeper research findings when taken together . The reasons behind any fluctions observed can be properly derived as a result .

          Finally make sure that proper attribution is alwys done following mentioned Terms Of Use while downloading since 'All Data Accessed And Downloaded From This Page Is Free For Public Use By Consumers , Media
  

Research Ideas

• Using the Mortgage Rate Data to devise strategies to help persons purchasing jumbo mortgages determine the best time and rates to acquire a loan.
• Analyzing trends in the market by investigating changes in affordability over time by studying rent and mortgage affordability, price-to-income ratios, and historical ZHVIs with cash buyers.
• Comparing different areas of housing markets over diverse geographies using data on all homes, condos/co-ops, multifamily dwellings 5+ units, duplexes/triplexes across various counties or metro areas

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: MortgageRateJumboFixed.csv | Column name | Description | |:---------------------------|:---------------------------------------------------------------------------------------------------------------| | Date | The date of the mortgage rate. (Date) | | TimePeriod | The time period of the ...

Concept: Average interest rate of credit operations with prefixed interest rates by source of funds and type of credit - microenterprise - nonearmarked credit - Rural financing - investment. Home Equity Source: Credit Information System ce54b817-d39a-4715-a6d1-67bdf320314d 27266-average-interest-rate-by-source-of-funds-and-type-of-credit---microenterprise---nonearmarked-

DESCRIPTION

A banking institution requires actionable insights into mortgage-backed securities, geographic business investment, and real estate analysis. The mortgage bank would like to identify potential monthly mortgage expenses for each region based on monthly family income and rental of the real estate. A statistical model needs to be created to predict the potential demand in dollars amount of loan for each of the region in the USA. Also, there is a need to create a dashboard which would refresh periodically post data retrieval from the agencies. The dashboard must demonstrate relationships and trends for the key metrics as follows: number of loans, average rental income, monthly mortgage and owner’s cost, family income vs mortgage cost comparison across different regions. The metrics described here do not limit the dashboard to these few. Dataset Description

Variables

Description Second mortgage Households with a second mortgage statistics Home equity Households with a home equity loan statistics Debt Households with any type of debt statistics Mortgage Costs Statistics regarding mortgage payments, home equity loans, utilities, and property taxes Home Owner Costs Sum of utilities, and property taxes statistics Gross Rent Contract rent plus the estimated average monthly cost of utility features High school Graduation High school graduation statistics Population Demographics Population demographics statistics Age Demographics Age demographic statistics Household Income Total income of people residing in the household Family Income Total income of people related to the householder Project Task: Week 1

Data Import and Preparation:

Import data.

Figure out the primary key and look for the requirement of indexing.

Gauge the fill rate of the variables and devise plans for missing value treatment. Please explain explicitly the reason for the treatment chosen for each variable.

Exploratory Data Analysis (EDA):

Perform debt analysis. You may take the following steps:

Explore the top 2,500 locations where the percentage of households with a second mortgage is the highest and percent ownership is above 10 percent. Visualize using geo-map. You may keep the upper limit for the percent of households with a second mortgage to 50 percent

Use the following bad debt equation:

Bad Debt = P (Second Mortgage ∩ Home Equity Loan) Bad Debt = second_mortgage + home_equity - home_equity_second_mortgage Create pie charts to show overall debt and bad debt

Create Box and whisker plot and analyze the distribution for 2nd mortgage, home equity, good debt, and bad debt for different cities

Create a collated income distribution chart for family income, house hold income, and remaining income

Perform EDA and come out with insights into population density and age. You may have to derive new fields (make sure to weight averages for accurate measurements):

Use pop and ALand variables to create a new field called population density

Use male_age_median, female_age_median, male_pop, and female_pop to create a new field called median age

Visualize the findings using appropriate chart type

Create bins for population into a new variable by selecting appropriate class interval so that the number of categories don’t exceed 5 for the ease of analysis.

Analyze the married, separated, and divorced population for these population brackets

Visualize using appropriate chart type

Please detail your observations for rent as a percentage of income at an overall level, and for different states.

Perform correlation analysis for all the relevant variables by creating a heatmap. Describe your findings.

Project Task: Week 2

Data Pre-processing:

The economic multivariate data has a significant number of measured variables. The goal is to find where the measured variables depend on a number of smaller unobserved common factors or latent variables.

Each variable is assumed to be dependent upon a linear combination of the common factors, and the coefficients are known as loadings. Each measured variable also includes a component due to independent random variability, known as “specific variance” because it is specific to one variable. Obtain the common factors and then plot the loadings. Use factor analysis to find latent variables in our dataset and gain insight into the linear relationships in the data.

  Following are the list of latent variables:

Highschool graduation rates

Median population age

Second mortgage statistics

Percent own

Bad debt expense

Data Modeling :

Build a linear Regression model to predict the total monthly expenditure for home mortgages loan.

  Please refer deplotment_RE.xlsx. Column hc_mortgage_mean is predicted variable. This is the mean monthly mortgage and owner costs of specified geographical location.

  Note: Exclude loans from prediction model which have NaN (Not a Numb...

It can be seen that the mortgage interest rate in Poland increased overall during the period under observation, reaching a value of *** percent as of the fourth quarter of 2024. Demand for mortgage loans in Poland      Despite the tightening of credit policy by banks, the demand for mortgage loans is not decreasing. The residential market has also seen increases both in sales and in the construction of new premises. The increase in salaries combined with the decrease in the mortgage loan cost results in Poles having no problems buying apartments despite high prices. Higher wages also affect their creditworthiness, which is essential when applying for a mortgage. The value of housing loans amounted to a record ***** billion zloty in 2019. Despite a decrease in 2017, the value of debt in 2019 increased by *** percent compared to the previous year. The increase in wealth has also been reflected in the average value of mortgages. In 2021, Bank Millennium granted the largest number of mortgages to Poles, although Bank ****** was the leader in terms of value.   Demand for housing in Poland      Despite a growing number of flats, the prices are not falling, but on the contrary, they are continually rising. An increase in prices was recorded in every major city. The annual rise in prices in many cities went up between ** and ** percent. The most significant price increase on the primary market was recorded in ******, while on the secondary market, Wroclaw prevailed. Nevertheless, Poles pay the most for a flat in the Polish capital Warsaw. In December 2024, the price per square meter of an apartment on the secondary market exceeded **** thousand zloty, while the price per square meter on the primary market was close to **** thousand zloty. However, the coronavirus (COVID-19) outbreak in Poland in March 2020 affected the investment plans in the real estate market. Both individual customers and developers recorded a significant decline in the number of construction projects commenced during this period.

This dataset provides values for INTEREST RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Mortgage Rate in Australia decreased to 5.51 percent in September from 5.52 percent in August of 2025. This dataset includes a chart with historical data for Australia Mortgage Rate.

Discover the booming Latin American home mortgage finance market. This comprehensive analysis reveals key growth drivers, restraints, and market segmentation, including data on fixed-rate vs. adjustable-rate mortgages and regional breakdowns across Brazil, Chile, Peru, Colombia, and more. Projected to reach $XX million by 2033, learn about the top players and investment opportunities in this dynamic sector. Recent developments include: In August 2022, Two new mortgage fintech start-ups emerged in Latin America: Toperty launched in Colombia and Saturn5 is about to launch in Mexico. Toperty offers to purchase a customer's new house outright and provides a payment schedule that allows the customer to purchase the house while renting it from the business. Saturn5 wants to give its clients the skills and resources they need to buy a house on their own., In August 2022, During a conference call on August 5, Brazilian lender Banco Bradesco SA startled analysts by reporting an increase in default rates in the second quarter of 2022. The average 90-day nonperforming loan ratio for Bradesco, the second-largest private bank in Latin America, increased by 30 basis points. Delinquency in the overall portfolio increased to 3.5% from 2.5% and 3.2%, respectively, in the first quarter.. Notable trends are: Increase in Economic Growth and GDP per capita.

View monthly updates and historical trends for Belgium Long Term Interest Rate. Source: European Central Bank. Track economic data with YCharts analytics.

Mortgage lenders are dealing with the RBA's shift to a tighter monetary policy, as it fights heavy inflation. Since May 2022, the RBA has raised the benchmark cash rate, which flows to interest rates on home loans. This represents a complete reversal of the prevailing approach to monetary policy taken in recent years. Over the course of the pandemic, subdued interest rates, in conjunction with government incentives and relaxed interest rate buffers, encouraged strong mortgage uptake. With the RBA's policy reversal, authorised deposit-taking institutions will need to balance their interest rate spreads to ensure steady profit. A stronger cash rate means more interest income from existing home loans, but also steeper funding costs. Moreover, increasing loan rates mean that prospective homeowners are being cut out of the market, which will slow demand for new home loans. Overall, industry revenue is expected to rise at an annualised 0.4% over the past five years, including an estimated 2.2% jump in 2023-24, to reach $103.4 billion. APRA's regulatory controls were updated in January 2023, with new capital adequacy ratios coming into effect. The major banks have had to tighten up their capital buffers to protect against financial instability. Although the ‘big four’ banks control most home loans, other lenders have emerged to foster competition for new loanees. Technological advances have made online-only mortgage lending viable. However, lenders that don't take deposits are more reliant on wholesale funding markets, which will be stretched under a higher cash rate. Looking ahead, technology spending isn't slowing down, as consumers continue to expect secure and user-friendly online financial services. This investment is even more pressing, given the ongoing threat of cyber-attacks. Industry revenue is projected to inch upwards at an annualised 0.8% over the five years through 2028-29, to $107.7 billion.

Key information about New Zealand Long Term Interest Rate

• New Zealand Government Bond Yield: 10 Years was reported at 4.36 % pa in Nov 2025, compared with 4.06 % pa in the previous month.
• New Zealand Long Term Interest Rate data is updated monthly, available from Jan 1985 to Nov 2025.
• The data reached an all-time high of 18.90 % pa in Mar 1986 and a record low of 0.51 % pa in Sep 2020.
• Long Term Interest Rate is reported by reported by Reserve Bank of New Zealand.

CEIC calculates monthly Long Term Interest Rate from daily 10 year Government Bond Yield. The Reserve Bank of New Zealand provides 10 year Treasury Bond Yield. Long Term Interest Rate prior to March 1985 is sourced directly from Reserve Bank of New Zealand.. The ten-year benchmark for New Zealand Government bonds with a fixed interest coupon paid semi-annually in arrears. The bonds are redeemable at par on maturity.


Related information about New Zealand Long Term Interest Rate

• In the latest reports, New Zealand Short Term Interest Rate: Month End: New Zealand: Bank Accepted Bills: 90 Days was reported at 2.45 % pa in Nov 2025.
• The cash rate (Policy Rate: Month End: New Zealand: Official Cash Rate) was set at 2.25 % pa in Nov 2025.
• New Zealand Exchange Rate against USD averaged 1.73 (USD/NZD) in Oct 2025.

In October 2024, the interest rate for mortgages with an initial rate fixation of five and up to ten years was 3.23 percent. This mortgage rate saw a general increase since the beginning of 2022 until the end of 2023, however started to decline in 2024. Falling mortgage rates might be a reason for the value of new mortgage lending rose in 2024. As borrowing costs increase, taking out a mortgage becomes less affordable for home buyers, also leading to the mortgage market slowing down. What about housing prices in Belgium? On average, a house cost approximately 319,000 euros in Belgium in 2022. Big price differences are observed, however, among the three regions of the country. A house in the French-speaking region of Wallonia is much more expensive on average than a house in the Brussels-Capital Region (the city of Brussels with its surrounding villages). Belgium’s real estate market grows steadily Property transactions in Belgium are affected by the country’s fiscal system. When purchasing a house in Belgium, consumers pay the asking price plus ten (in Flanders) or 12 percent (in Wallonia and the Brussels-Capital Region) in registration rights. This makes buying a house in Belgium a long-term investment and something consumers do not do right away.

The benchmark interest rate in Mexico was last recorded at 7.25 percent. This dataset provides - Mexico Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The German Internet Panel (GIP) is a long-term study at the University of Mannheim. The GIP examines individual attitudes and preferences that are relevant in political and economic decision-making processes. To this end, more than 3,500 people throughout Germany have been regularly surveyed online every two months since 2012 on a wide range of topics. The GIP is based on a random sample of the general population in Germany between the ages of 16 and 75. The study started in 2012 and was supplemented by new participants in 2014 and 2018. The panel participants were recruited offline. The GIP questionnaires cover a variety of topics that deal with current events.
Sustainability in the financial sector: perception of financial products with a focus on sustainability (sustainable equity funds, sustainable savings accounts or current accounts, sustainable life or pension insurance, green loans that finance energy-saving investments and property renovations, none of the above); assessment of personal knowledge of financial matters; Financial knowledge on the topics of interest rates on savings accounts, interest rates and inflation, investment risk, debt development after borrowing; assessment of knowledge of sustainable financial investments; knowledge of the term ESG in connection with sustainable investments; financial knowledge on the topics of CO2 emission reduction, sustainability rating and label standards for funds, sustainability and risks of funds; consideration of sustainability aspects in household financial decisions; types of sustainable investments or household expenditures (green electricity, electric car, sustainable fund, sustainable savings account or checking account, sustainable life or pension insurance, credit financing via green credit, other, none of the above); home ownership; investment in various measures to improve the energy efficiency of the property over the last ten years (installation of a photovoltaic or solar thermal system, installation of a heat pump, conversion of heat generation, replacement of windows, doors, or gates, renewal of radiators or heat distribution, insulation of basement ceilings, attics, pipes, exterior walls, or similar, heat insulation for the summer, other, none of the above); use of government subsidies for these measures (government subsidy loans (e.g., KfW loans, tax advantages, government allowances, none of the above); obtaining a sustainable loan that did not come from KfW to finance one of the above investments; investment expectations: long-term assessment of average returns, fees, and average risk of sustainable equity funds compared to conventional equity funds; assessment of average savings interest rates on sustainable savings deposits compared to conventional savings accounts or checking accounts; assessment of credit terms for loans to finance sustainable investments compared to conventional loans; assessment of the long-term financial savings of investments in energy efficiency in real estate compared to the necessary investment sum; assessment of the long-term returns of sustainable life or pension insurance policies compared to conventional products; self-assessment of risk tolerance in financial decisions; investment preferences (I only invest in an equity fund if I can be sure that it invests exclusively in climate-friendly companies); opinion on financial markets and sustainable investment opportunities: sustainable financial investments are just a marketing strategy used by financial institutions to attract investors; sustainable financial investments are invested exclusively in sustainable business models; I feel good when I invest in sustainable financial investments, even if their effect on the environment cannot be assessed; investing in sustainable financial assets has a positive impact on the environment; I don´t know what social benefits investing in sustainable financial assets has; I prefer to live a sustainable lifestyle rather than consider sustainability in my financial decisions; I regularly discuss sustainable financial assets with my friends, colleagues, and/or relatives; general trust in banks and financial institutions in Germany; climate change is a serious problem that needs to be solved; a clean planet is more important to me than increasing my own wealth; higher fees for a bank account are worthwhile if the bank grants more loans for sustainable investments; I would only invest in sustainable investments if they offer the same or higher returns than conventional investments; I behave in a climate-conscious manner in order to stop global warming; confidence in financial institutions that invested money will actually be invested in a sustainable manner; Institutions or decision-makers that should primarily drive climate transformation in the future (German Bundestag, European Commission or European Parliament, private companies, financial sector, central banks, research, private households, other, none of the...