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 30-Year Fixed Rate FHA Mortgage Index (OBMMIFHA30YF) from 2017-01-03 to 2025-08-27 about FHA, 30-year, mortgage, fixed, rate, indexes, and USA.

The table below showcases the 10th, 25th, 50th, 75th, and 90th percentiles of mortgage rates for each zip code in Mountain Home Village, California. It's important to understand that mortgage rates can vary greatly and can change yearly.

The table below showcases the 10th, 25th, 50th, 75th, and 90th percentiles of mortgage rates for each zip code in College City, California. It's important to understand that mortgage rates can vary greatly and can change yearly.

The table below showcases the 10th, 25th, 50th, 75th, and 90th percentiles of mortgage rates for each zip code in Etterburg, California. It's important to understand that mortgage rates can vary greatly and can change yearly.

The table below showcases the 10th, 25th, 50th, 75th, and 90th percentiles of mortgage rates for each zip code in Willow Springs, California. It's important to understand that mortgage rates can vary greatly and can change yearly.

Car loan interest rates in the United States decreased since mid-2024. Thus, the period of rapidly rising interest rates, when they increased from 3.85 percent in December 2021 to 7.92 percent in June 2024, has come to an end. The Federal Reserve interest rate is one of the main causes of the interest rates of loans rising or falling. If inflation stays under control, the Federal Reserve will start cutting the interest rates, which would have the effect of the cost of car loans falling too. How many cars have financing in the United States? Car financing exists because not everyone who wants or needs a car can purchase it outright. A financial institution will then lend the money to the customer for purchasing the car, which must then be repaid with interest. Most new vehicles in the United States in 2024 were purchased using car loans. It is not as common to use car loans for purchasing used vehicles as for new ones, although over a third of used vehicles were purchased using loans. The car industry in the United States The car financing business is huge in the United States, due to the high sales of both new and used vehicles in the country. A lot of the United States is very car-centric, which means that, outside large cities, it can often be difficult to do their daily commutes through other transportation methods. In fact, only a small percentage of U.S. workers used public transport to go to work. That is one of the factors that has helped establish the importance of the automotive sector in North America. Nevertheless, there are still countries in Asia-Pacific, Africa, the Middle East, and Europe with higher car-ownership rates than the United States.

The table below showcases the 10th, 25th, 50th, 75th, and 90th percentiles of mortgage rates for each zip code in Iowa Hill, California. It's important to understand that mortgage rates can vary greatly and can change yearly.

The table below showcases the 10th, 25th, 50th, 75th, and 90th percentiles of mortgage rates for each zip code in Madison, California. It's important to understand that mortgage rates can vary greatly and can change yearly.

The foreclosure rate in the United States has experienced significant fluctuations over the past two decades, reaching its peak in 2010 at **** percent following the financial crisis. Since then, the rate has steadily declined, with a notable drop to **** percent in 2021 due to government interventions during the COVID-19 pandemic. In 2024, the rate stood slightly higher at **** percent but remained well below historical averages, indicating a relatively stable housing market. Impact of economic conditions on foreclosures The foreclosure rate is closely tied to broader economic trends and housing market conditions. During the aftermath of the 2008 financial crisis, the share of non-performing mortgage loans climbed significantly, with loans 90 to 180 days past due reaching *** percent. Since then, the share of seriously delinquent loans has dropped notably, demonstrating a substantial improvement in mortgage performance. Among other things, the improved mortgage performance has to do with changes in the mortgage approval process. Homebuyers are subject to much stricter lending standards, such as higher credit score requirements. These changes ensure that borrowers can meet their payment obligations and are at a lower risk of defaulting and losing their home. Challenges for potential homebuyers Despite the low foreclosure rates, potential homebuyers face significant challenges in the current market. Homebuyer sentiment worsened substantially in 2021 and remained low across all age groups through 2024, with the 45 to 64 age group expressing the most negative outlook. Factors contributing to this sentiment include high housing costs and various financial obligations. For instance, in 2023, ** percent of non-homeowners reported that student loan expenses hindered their ability to save for a down payment.

The table below showcases the 10th, 25th, 50th, 75th, and 90th percentiles of mortgage rates for each zip code in Los Angeles, California. It's important to understand that mortgage rates can vary greatly and can change yearly.

Dataset Overview

This dataset provides historical housing price indices for the United States, covering a span of 20 years from January 2000 onwards. The data includes housing price trends at the national level, as well as for major metropolitan areas such as San Francisco, Los Angeles, New York, and more. It is ideal for understanding how housing prices have evolved over time and exploring regional differences in the housing market.

Why This Dataset?

The U.S. housing market has experienced significant shifts over the last two decades, influenced by economic booms, recessions, and post-pandemic recovery. This dataset allows data enthusiasts, economists, and real estate professionals to analyze long-term trends, make forecasts, and derive insights into regional housing markets.

What’s Included?

Time Period: January 2000 to the latest available data (specific end date depends on the dataset). Frequency: Monthly data. Regions Covered: 20+ U.S. cities, states, and aggregates.

Columns Description

Each column represents the housing price index for a specific region or aggregate, starting with a date column:

Date: Represents the date of the housing price index measurement, recorded with a monthly frequency. U.S. National: The national-level housing price index for the United States. 20-City Composite: The aggregate housing price index for the top 20 metropolitan areas in the U.S. CA-San Francisco: The housing price index for San Francisco, California. CA-Los Angeles: The housing price index for Los Angeles, California. WA-Seattle: The housing price index for Seattle, Washington. NY-New York: The housing price index for New York City, New York. Additional Columns: The dataset includes more columns with housing price indices for various U.S. cities, which can be viewed in the full dataset preview.

Potential Use Cases

Time-Series Analysis: Investigate long-term trends and patterns in housing prices. Forecasting: Build predictive models to forecast future housing prices using historical data. Regional Comparisons: Analyze how housing prices have grown in different cities over time. Economic Insights: Correlate housing prices with economic factors like interest rates, GDP, and inflation.

Who Can Use This Dataset?

This dataset is perfect for:

Data scientists and machine learning practitioners looking to build forecasting models. Economists and policymakers analyzing housing market dynamics. Real estate investors and analysts studying regional trends in housing prices.

Example Questions to Explore

Which cities have experienced the highest housing price growth over the last 20 years? How do housing price trends in coastal cities (e.g., Los Angeles, Miami) compare to midwestern cities (e.g., Chicago, Detroit)? Can we predict future housing prices using time-series models like ARIMA or Prophet?

The table below showcases the 10th, 25th, 50th, 75th, and 90th percentiles of mortgage rates for each zip code in Apple Valley, California. It's important to understand that mortgage rates can vary greatly and can change yearly.

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.

CEV Eaton Vance California Municipal Income Trust Shares of Beneficial Interest

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

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.

Southern California Edison: A Steady Path to Floating Rates? (SCE-J)

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

The table below showcases the 10th, 25th, 50th, 75th, and 90th percentiles of mortgage rates for each zip code in Ca Hot Springs, California. It's important to understand that mortgage rates can vary greatly and can change yearly.

Property-Plant-and-Equipment-Gross Time Series for Zions Bancorporation. Zions Bancorporation, National Association provides various banking products and related services primarily in the states of Arizona, California, Colorado, Idaho, Nevada, New Mexico, Oregon, Texas, Utah, Washington, and Wyoming. The company operates through Zions Bank, California Bank & Trust, Amegy Bank, National Bank of Arizona, Nevada State Bank, Vectra Bank Colorado, and The Commerce Bank of Washington segments. It offers commercial and small business banking services to small- and medium-sized businesses, such as commercial, industrial, and owner-occupied lending and leasing; municipal and public finance services; depository account and cash management services; commercial and small business cards; merchant processing services; corporate trust services; and correspondent banking and international lending services. The company also provides capital markets and investment banking services, including loan syndications, foreign exchange services, interest rate derivatives, fixed income securities underwriting, advisory and capital raising, commercial mortgage-backed security conduit lending, and power and project financing; and commercial real estate lending services consisting of term and construction/land development financing for commercial and residential purposes. In addition, it offers retail banking services comprising residential mortgages, home equity lines of credit, personal lines of credit, installment consumer loans, depository account services, consumer cards, and personal trust services; and wealth management services consisting of investment management, fiduciary and estate, and advanced business succession and estate planning services. The company was formerly known as ZB, National Association and changed its name to Zions Bancorporation, National Association in September 2018. Zions Bancorporation, National Association was founded in 1873 and is headquartered in Salt Lake City, Utah.

The table below showcases the 10th, 25th, 50th, 75th, and 90th percentiles of mortgage rates for each zip code in Corte Madera, California. It's important to understand that mortgage rates can vary greatly and can change yearly.

The table below showcases the 10th, 25th, 50th, 75th, and 90th percentiles of mortgage rates for each zip code in Elk Creek, California. It's important to understand that mortgage rates can vary greatly and can change yearly.

The table below showcases the 10th, 25th, 50th, 75th, and 90th percentiles of mortgage rates for each zip code in Willow Creek, California. It's important to understand that mortgage rates can vary greatly and can change yearly.