Fixed 30-year mortgage rates in the United States averaged 6.77 percent in the week ending July 4 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.

The 10-year treasury constant maturity rate in the U.S. is forecast to increase by *** percentage points by 2027, while the 30-year fixed mortgage rate is expected to fall by *** percentage points. From *** percent in 2024, the average 30-year mortgage rate is projected to reach *** percent in 2027.

30 Year Mortgage Rate in the United States increased to 6.72 percent in July 10 from 6.67 percent in the previous week. This dataset includes a chart with historical data for the United States 30 Year Mortgage Rate.

Graph and download economic data for 15-Year Fixed Rate Mortgage Average in the United States (MORTGAGE15US) from 1991-08-30 to 2025-07-10 about 15-year, fixed, mortgage, interest rate, interest, rate, and USA.

Canada Conventional Mortgage: 5 Years: Weekly data was reported at 6.490 % pa in 07 May 2025. This stayed constant from the previous number of 6.490 % pa for 30 Apr 2025. Canada Conventional Mortgage: 5 Years: Weekly data is updated weekly, averaging 5.700 % pa from Jan 2000 (Median) to 07 May 2025, with 1323 observations. The data reached an all-time high of 8.750 % pa in 31 May 2000 and a record low of 4.640 % pa in 12 Jul 2017. Canada Conventional Mortgage: 5 Years: Weekly data remains active status in CEIC and is reported by Bank of Canada. The data is categorized under Global Database’s Canada – Table CA.M005: Conventional Mortgage Rate. [COVID-19-IMPACT]

Mortgage Loan Service Market Outlook

The global mortgage loan service market size was valued at approximately $10.5 trillion in 2023 and is projected to reach around $18.2 trillion by 2032, growing at a CAGR of 6.1% during the forecast period. The growth of this market is driven by the increasing urbanization, rising disposable incomes, and favorable government policies aimed at promoting homeownership across various regions. Additionally, the proliferation of digital banking and fintech solutions has made mortgage services more accessible, further contributing to the market's expansion.

One of the primary growth factors for the mortgage loan service market is the significant rise in housing demand globally. As urban populations swell and economic conditions improve, more individuals and families are seeking to purchase homes, driving the need for mortgage loans. This trend is particularly evident in emerging markets, where urbanization is occurring at an unprecedented rate. Governments are also playing a crucial role by implementing policies and grants to make housing more affordable, thereby boosting mortgage adoption.

Technological advancements are another significant factor propelling the mortgage loan service market. The integration of AI, big data analytics, and blockchain technology has revolutionized the way mortgage services are delivered. These technologies streamline application processes, enhance risk assessment, and improve customer service, making it easier and faster for consumers to secure loans. Fintech companies, in particular, are leveraging these technologies to offer more competitive rates and personalized loan products, thereby attracting a broader customer base.

Furthermore, the increasing participation of non-banking financial institutions (NBFIs) and credit unions has diversified the mortgage loan service market. These entities often provide more flexible and innovative loan products compared to traditional banks, meeting the needs of a more varied clientele. NBFIs and credit unions also tend to have more lenient approval processes, making them an attractive option for individuals with non-traditional income sources or lower credit scores. This diversification is contributing significantly to the market's growth.

Mortgage Loans Software is playing an increasingly pivotal role in the evolution of the mortgage loan service market. As the industry embraces digital transformation, software solutions are being developed to streamline the entire mortgage process, from application to approval. These software platforms facilitate better data management, enhance customer experience, and improve operational efficiency for service providers. By automating routine tasks and providing real-time analytics, Mortgage Loans Software helps lenders make more informed decisions, reduce processing times, and minimize errors. This technological advancement is not only beneficial for lenders but also empowers borrowers by offering them greater transparency and control over their mortgage journey.

Regionally, North America continues to dominate the mortgage loan service market due to its well-established financial infrastructure and high homeownership rates. However, the Asia Pacific region is expected to register the fastest growth during the forecast period, driven by rapid urbanization, rising incomes, and government initiatives aimed at affordable housing. Countries like China and India are particularly noteworthy due to their large and growing middle-class populations.

Type Analysis

The mortgage loan service market is segmented by type into fixed-rate mortgages, adjustable-rate mortgages, interest-only mortgages, reverse mortgages, and others. Fixed-rate mortgages are the most popular type, offering borrowers the stability of a constant interest rate over the life of the loan. This makes them particularly attractive in times of low-interest rates, as borrowers can lock in favorable terms for the long term. The predictability of monthly payments also makes fixed-rate mortgages a preferred choice for many homeowners.

Adjustable-rate mortgages (ARMs) offer lower initial interest rates compared to fixed-rate mortgages, making them an attractive option for borrowers who anticipate an increase in their income or plan to sell their property before the rate adjusts. However, the fluctuating interest rates can pose a risk, especially in volatile economic conditions. Despite this, the flexibility

15 Year Mortgage Rate in the United States increased to 5.86 percent in July 10 from 5.80 percent in the previous week. This dataset includes a chart with historical data for the United States 15 Year Mortgage Rate.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

What are 30 year mortgage rates?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

In the United States, interest rates for all mortgage types started to increase in 2021. This was due to the Federal Reserve introducing a series of hikes in the federal funds rate to contain the rising inflation. In the fourth quarter of 2024, the 30-year fixed rate rose slightly, to **** percent. Despite the increase, the rate remained below the peak of **** percent in the same quarter a year ago. Why have U.S. home sales decreased? Cheaper mortgages normally encourage consumers to buy homes, while higher borrowing costs have the opposite effect. As interest rates increased in 2022, the number of existing homes sold plummeted. Soaring house prices over the past 10 years have further affected housing affordability. Between 2013 and 2023, the median price of an existing single-family home risen by about ** percent. On the other hand, the median weekly earnings have risen much slower. Comparing mortgage terms and rates Between 2008 and 2023, the average rate on a 15-year fixed-rate mortgage in the United States stood between **** and **** percent. Over the same period, a 30-year mortgage term averaged a fixed-rate of between **** and **** percent. Rates on 15-year loan terms are lower to encourage a quicker repayment, which helps to improve a homeowner’s equity.

Graph and download economic data for 5/1-Year Adjustable Rate Mortgage Average in the United States (DISCONTINUED) (MORTGAGE5US) from 2005-01-06 to 2022-11-10 about adjusted, mortgage, interest rate, interest, 5-year, rate, and USA.

Mortgage interest rates worldwide varied greatly in 2024, from less than **** percent in many European countries, to as high as ** percent in Turkey. The average mortgage rate in a country depends on the central bank's base lending rate and macroeconomic indicators such as inflation and forecast economic growth. Since 2022, inflationary pressures have led to rapid increase in mortgage interest rates. Which are the leading mortgage markets? An easy way to estimate the importance of the mortgage sector in each country is by comparing household debt depth, or the ratio of the debt held by households compared to the county's GDP. In 2023, Switzerland, Australia, and Canada had some of the highest household debt to GDP ratios worldwide. While this indicator shows the size of the sector relative to the country’s economy, the value of mortgages outstanding allows to compare the market size in different countries. In Europe, for instance, the United Kingdom, Germany, and France were the largest mortgage markets by outstanding mortgage lending. Mortgage lending trends in the U.S. In the United States, new mortgage lending soared in 2021. This was largely due to the growth of new refinance loans that allow homeowners to renegotiate their mortgage terms and replace their existing loan with a more favorable one. Following the rise in interest rates, the mortgage market cooled, and refinance loans declined.

After a period of gradual decline, the average annual rate on a 30-year fixed-rate mortgage in the United States rose to **** percent in 2023, up from the record-low **** percent in 2021. In 2024, interest rates declined slightly. The rate for 15-year fixed mortgages and five-year ARM mortgages followed a similar trend. This was a result of the Federal Reserve increasing the bank rate - a measure introduced to tackle the rising inflation. U.S. home prices going through the roof Mortgage rates have a strong impact on the market – the lower the rate, the lower the loan repayment. The rate on a 30-year fixed-rate mortgage decreasing after the Great Recession has stimulated the market and boosted home sales. Another problem consumers face is the fact that house prices are rising at an unaffordable level. The median sales price of a new home sold surged in 2021, while the median weekly earnings of a full-time employee maintained a more moderate increase. What are the differences between 15-year and 30-year mortgages? Two of the most popular loan terms available to homebuyers are the 15-year fixed-rate mortgage and the 30-year fixed-rate mortgage. The 30-year option appeals to more consumers because the repayment is spread out over 30 years, meaning the monthly payments are lower. Consumers choosing the 15-year option will have to pay higher monthly payments but benefit from lower interest rates.

More than ************* mortgage loans are projected to be affected by the increasing mortgage interest rates in Canada by 2025. About *********** of these mortgages are projected to be up for renewal in 2024. These loans were taken out at a time when interest rates were much lower, meaning that homeowners will be affected by a notable increase in their monthly payments.

Mortgage rates in the Netherlands increased sharply in 2022 and 2023, after declining gradually between 2008 and 2021. In December 2022, the average interest rate for new mortgage loans stood at **** percent, and by the end of 2023, it had risen to **** percent. The 10-year interest rate was the lowest, at **** percent; the floating and less than one-year interest rates amounted to **** and **** percent, respectively. In early 2024, mortgage rates decreased notably. Are mortgage rates in the Netherlands different from those in other European countries? When comparing this ranking to data that covers multiple European countries, the Netherlands’ mortgage rate was similar to the rates found in Spain, the United Kingdom, and Sweden. It was, however, a lot lower than the rates in Eastern Europe. Hungary and Romania, for example, had some of the highest mortgage rates. For more information on the European mortgage market and how much the countries differ from each other, please visit this dedicated research page. How big is the mortgage market in the Netherlands? The Netherlands has overall seen an increase in the number of mortgage loans sold and is regarded as one of the countries with the highest mortgage debt in Europe. The reason behind this is that Dutch homeowners were able to for many years to deduct interest paid from pre-tax income (a system known in the Netherlands as hypotheekrenteaftrek). Total mortgage debt of Dutch households has been increasing year-on-year since 2013.

United States Mortgage Fixed Rate: Mth Avg: 15 Year data was reported at 4.250 % pa in Oct 2018. This records an increase from the previous number of 4.080 % pa for Sep 2018. United States Mortgage Fixed Rate: Mth Avg: 15 Year data is updated monthly, averaging 5.680 % pa from Sep 1991 (Median) to Oct 2018, with 326 observations. The data reached an all-time high of 8.800 % pa in Jan 1995 and a record low of 2.660 % pa in Apr 2013. United States Mortgage Fixed Rate: Mth Avg: 15 Year data remains active status in CEIC and is reported by Federal Home Loan Mortgage Corporation, Freddie Mac. The data is categorized under Global Database’s United States – Table US.M012: Mortgage Interest Rate.

WAS: Contract Rate: 5-Year ARM: 1-Wk Change data was reported at 0.050 Point in 23 Nov 2018. This records an increase from the previous number of -0.210 Point for 16 Nov 2018. WAS: Contract Rate: 5-Year ARM: 1-Wk Change data is updated weekly, averaging -0.010 Point from Jan 2011 (Median) to 23 Nov 2018, with 410 observations. The data reached an all-time high of 0.270 Point in 11 Dec 2015 and a record low of -0.250 Point in 09 Jan 2015. WAS: Contract Rate: 5-Year ARM: 1-Wk Change data remains active status in CEIC and is reported by Mortgage Bankers Association. The data is categorized under Global Database’s United States – Table US.M013: Weekly Applications Survey: Mortgage Interest Rate.

Graph and download economic data for 30-Year Fixed Rate Veterans Affairs Mortgage Index (OBMMIVA30YF) from 2017-01-03 to 2025-07-10 about veterans, 30-year, fixed, mortgage, rate, indexes, and USA.

Graph and download economic data for 30-Year Fixed Rate FHA Mortgage Index (OBMMIFHA30YF) from 2017-01-03 to 2025-07-10 about FHA, 30-year, fixed, mortgage, rate, indexes, and USA.

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.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Mortgage Rates: Hot Economic Conjecture Puts the Squeeze on Homebuyers

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data