Graph and download economic data for 30-Year Fixed Rate Conforming Non-Adjusted Mortgage Index (OBMMIC30YFNA) from 2017-01-03 to 2025-07-02 about 30-year, fixed, mortgage, rate, indexes, and USA.

Graph and download economic data for 30-Year Fixed Rate Jumbo Mortgage Index (OBMMIJUMBO30YF) from 2017-01-03 to 2025-07-02 about jumbo, 30-year, fixed, mortgage, rate, indexes, and USA.

30 Year Mortgage Rate in the United States decreased to 6.67 percent in July 3 from 6.77 percent in the previous week. This dataset includes a chart with historical data for the United States 30 Year Mortgage Rate.

Fixed 30-year mortgage rates in the United States averaged 6.79 percent in the week ending June 27 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.

Graph and download economic data for 30-Year Fixed Rate Conforming Mortgage Index: Loan-to-Value Greater Than 80, FICO Score Between 700 and 719 (OBMMIC30YFLVGT80FB700A719) from 2017-01-03 to 2025-07-02 about score, 30-year, fixed, mortgage, rate, indexes, and USA.

Interactive historical chart showing the 30 year fixed rate mortgage average in the United States since 1971.

MBA Mortgage Market Index in the United States increased to 257.50 points in June 27 from 250.80 points in the previous week. This dataset includes a chart with historical data for the United States MBA Mortgage Market Index.

Mortgage rates increased at a record pace in 2022, with the 10-year fixed mortgage rate doubling between March 2022 and December 2022. With inflation increasing, the Bank of England introduced several bank rate hikes, resulting in higher mortgage rates. In May 2025, the average 10-year fixed rate interest rate reached **** percent. As borrowing costs get higher, demand for housing is expected to decrease, leading to declining market sentiment and slower house price growth. How have the mortgage hikes affected the market? After surging in 2021, the number of residential properties sold declined in 2023, reaching just above *** million. Despite the number of transactions falling, this figure was higher than the period before the COVID-19 pandemic. The falling transaction volume also impacted mortgage borrowing. Between the first quarter of 2023 and the first quarter of 2024, the value of new mortgage loans fell year-on-year for five straight quarters in a row. How are higher mortgages affecting homebuyers? Homeowners with a mortgage loan usually lock in a fixed rate deal for two to ten years, meaning that after this period runs out, they need to renegotiate the terms of the loan. Many of the mortgages outstanding were taken out during the period of record-low mortgage rates and have since faced notable increases in their monthly repayment. About **** million homeowners are projected to see their deal expire by the end of 2026. About *** million of these loans are projected to experience a monthly payment increase of up to *** British pounds by 2026.

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

Graph and download economic data for 30-Year Fixed Rate Veterans Affairs Mortgage Index (OBMMIVA30YF) from 2017-01-03 to 2025-07-02 about veterans, 30-year, fixed, mortgage, rate, indexes, and USA.

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

Mortgage Application in the United States increased by 2.70 percent in the week ending June 27 of 2025 over the previous week. This dataset provides - United States MBA Mortgage Applications - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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.

Mortgage Rate in the United Kingdom decreased to 7.09 percent in May from 7.19 percent in April of 2025. This dataset provides - United Kingdom BBA Mortgage Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

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 Soar, Making Homeownership Out of Reach for Many

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

Following the drastic increase directly after the COVID-19 pandemic, the delinquency rate started to gradually decline, falling below *** percent in the second quarter of 2023. In the second half of 2023, the delinquency rate picked up, but remained stable throughout 2024. In the first quarter of 2025, **** percent of mortgage loans were delinquent. That was significantly lower than the **** percent during the onset of the COVID-19 pandemic in 2020 or the peak of *** percent during the subprime mortgage crisis of 2007-2010. What does the mortgage delinquency rate tell us? The mortgage delinquency rate is the share of the total number of mortgaged home loans in the U.S. where payment is overdue by 30 days or more. Many borrowers eventually manage to service their loan, though, as indicated by the markedly lower foreclosure rates. Total home mortgage debt in the U.S. stood at almost ** trillion U.S. dollars in 2024. Not all mortgage loans are made equal ‘Subprime’ loans, being targeted at high-risk borrowers and generally coupled with higher interest rates to compensate for the risk. These loans have far higher delinquency rates than conventional loans. Defaulting on such loans was one of the triggers for the 2007-2010 financial crisis, with subprime delinquency rates reaching almost ** percent around this time. These higher delinquency rates translate into higher foreclosure rates, which peaked at just under ** percent of all subprime mortgages in 2011.

Key information about United States Bank Lending Rate

• United States Bank Lending Rate was reported at 7.500 % pa in Mar 2025.
• This stayed constant from the previous number of 7.500 % pa for Mar 2025.
• US Bank Lending Rate data is updated daily, averaging 4.250 % pa from Aug 1955 to 24 Mar 2025, with 25436 observations.
• The data reached an all-time high of 8.500 % pa in 18 Sep 2024 and a record low of 3.250 % pa in 16 Mar 2022.
• US Bank Lending Rate data remains active status in CEIC and is reported by CEIC Data.
• The data is categorized under World Trend Plus’s Global Economic Monitor – Table: Bank Lending Rate: Daily.

Graph and download economic data for 30-Year Fixed Rate USDA Mortgage Index (OBMMIUSDA30YF) from 2017-01-03 to 2025-07-02 about USDA, 30-year, fixed, mortgage, rate, indexes, and USA.

The U.S. mortgage market has declined notably since 2020 and 2021, mostly due to the effect of higher borrowing costs on refinance mortgages. The value of refinancing mortgage originations, amounted to 190 billion U.S. dollars in the fourth quarter of 2024, down from a peak of 851 billion U.S. dollars in the fourth quarter of 2020. The value of mortgage loans for the purchase of a property recorded milder fluctuations, with a value of 304 billion U.S. dollars in the fourth quarter of 2024. According to the forecast, mortgage lending is expected to slightly increase until the end of 2026. The cost of mortgage borrowing in the U.S. Mortgage interest rates in the U.S. rose dramatically in 2022, peaking in the final quarter of 2024. In 2020, a homebuyer could lock in a 30-year fixed interest rate of under three percent, whereas in 2024, the average rate for the same mortgage type exceeded 6.6 percent. This has led to a decline in homebuyer sentiment, and an increasing share of the population pessimistic about buying a home in the current market. The effect of a slower housing market on property prices and rents According to the S&P/Case Shiller U.S. National Home Price Index, housing prices experienced a slight correction in early 2023, as property transactions declined. Nevertheless, the index continued to grow in the following months. On the other hand, residential rents have increased steadily since 2000.

China Wenzhou Index: Market Entity Financing Interest Rate data was reported at 14.560 % pa in 13 May 2025. This records a decrease from the previous number of 19.360 % pa for 12 May 2025. China Wenzhou Index: Market Entity Financing Interest Rate data is updated daily, averaging 17.870 % pa from Nov 2023 (Median) to 13 May 2025, with 368 observations. The data reached an all-time high of 22.980 % pa in 24 Apr 2024 and a record low of 6.110 % pa in 25 Jan 2024. China Wenzhou Index: Market Entity Financing Interest Rate data remains active status in CEIC and is reported by Wenzhou Private Financ Index. The data is categorized under China Premium Database’s Money Market, Interest Rate, Yield and Exchange Rate – Table CN.MA: Private Lending Rate: Wenzhou.