Single Family Home Prices in the United States decreased to 422600 USD in August from 425700 USD in July of 2025. This dataset provides - United States Existing Single Family Home Prices- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Nahb Housing Market Index in the United States remained unchanged at 32 points in September. This dataset provides the latest reported value for - United States Nahb Housing Market Index - 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 Housing Inventory: Median Days on Market in the United States (MEDDAYONMARUS) from Jul 2016 to Aug 2025 about median and USA.

Graph and download economic data for Equity Market Volatility Tracker: Macroeconomic News and Outlook: Real Estate Markets (EMVMACRORE) from Jan 1985 to Aug 2025 about volatility, uncertainty, equity, real estate, and USA.

About Dataset

Source

The source of this dataset is REDFIN Data Center. To download the latest dataset available, please go to: https://www.redfin.com/news/data-center/

They also provide a page with the definitions for each metric used here: https://www.redfin.com/news/data-center-metrics-definitions/

For more informaton on Data and Data Quality, please visit: https://www.redfin.com/about/data-quality-on-redfin Reading the Data

The data is a .tsv format and can be imported using pandas as follows:

df = pd.read_csv("weekly_housing_market_data_most_recent.tsv000", sep='\t')

MOST RECENT DATAPOINT: 2022-07-11

Existing Home Sales in the United States decreased to 4000 Thousand in August from 4010 Thousand in July of 2025. This dataset provides the latest reported value for - United States Existing Home Sales - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus 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.

Dow Jones U.S. Real Estate: A True Reflection of the Market?

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

New Home Sales in the United States increased to 800 Thousand units in August from 664 Thousand units in July of 2025. This dataset provides the latest reported value for - United States New Home Sales - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Housing Starts in the United States decreased to 1307 Thousand units in August from 1429 Thousand units in July of 2025. This dataset provides the latest reported value for - United States Housing Starts - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Housing Index in the United States decreased to 433.80 points in June from 434.60 points in May of 2025. This dataset provides the latest reported value for - United States House Price Index MoM Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Mortgage News Daily is a leading news and analysis provider of U.S. mortgage markets and publish Mortgage News Daily rate index which is published daily.

Graph and download economic data for Housing Inventory: Median Days on Market Month-Over-Month in Newport News City, VA (MEDDAYONMARMM51700) from Jul 2017 to Aug 2025 about Newport News City, VA; Virginia Beach; VA; median; and USA.

CPI Housing Utilities in the United States increased to 349.28 points in August from 348.21 points in July of 2025. This dataset provides - United States Cpi Housing- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Overview with Chart & Report: House Price Index y/y measures average changes in the value of single-family homes in the US in the given month compared to the same period of the previous year. Higher housing prices can strengthen

Introduction

The global AI in real estate market is experiencing remarkable growth, with projections indicating a substantial increase in value. By 2033, the market is anticipated to reach a staggering USD 41.5 billion, reflecting a notable compound annual growth rate (CAGR) of 30.5% during the forecast period from 2024 to 2033. This growth trajectory underscores the transformative impact of artificial intelligence (AI) on the real estate sector, revolutionizing various aspects of operations and decision-making processes.

The integration of Artificial Intelligence (AI) in real estate is transforming how the industry operates, from property management to sales. AI technologies enable more efficient data processing and interpretation, facilitating better decision-making. Key applications include automated valuation models, predictive analytics for market trends, and chatbots for customer service. This innovation leads to improved user experiences and operational efficiencies.

The AI in real estate market is experiencing significant growth. This expansion can be attributed to the increasing demand for smarter and more efficient real estate solutions, which AI provides. Real estate companies are investing in AI to enhance property search engines, implement smart home technologies, and improve transaction processes. These advancements are attracting both investors and companies looking to capitalize on the enhanced capabilities of AI to streamline operations and increase profitability.

Despite challenges such as data privacy concerns and the integration of AI with traditional systems, the momentum for AI adoption in real estate remains strong. AI has the potential to create significant value for the industry, ranging from cost reduction to operational improvement. According to surveys, AI could generate substantial value ranging from $110 billion to $180 billion and beyond, highlighting its transformative potential.

Introduction

The Global Smart Homes Market is poised for substantial growth, projected to reach USD 503.1 billion by 2032 from USD 132.2 billion in 2023, with a robust CAGR of 16.8% during the forecast period. This market expansion is driven by increasing adoption of Internet of Things (IoT) technology, enabling remote control and monitoring of devices for enhanced convenience, energy efficiency, and security.

The Smart Homes market is experiencing significant growth, driven by the increasing demand for energy efficiency, enhanced home security, and the convenience of home automation technologies. As technology advances, consumers are more inclined to adopt smart home systems that offer control over appliances, lighting, heating, and security systems through smartphones and other interfaces. This market's expansion is propelled by the growing integration of Internet of Things (IoT) devices, which enhance the connectivity and functionality of home systems.

One of the key growth factors driving the smart homes market is the increasing adoption of Internet of Things (IoT) devices. The proliferation of IoT devices, such as smart speakers, thermostats, security cameras, and appliances, has made it easier for homeowners to connect and control multiple devices seamlessly. The convenience and energy efficiency offered by smart home solutions have also contributed to their popularity. With the ability to remotely monitor and manage their homes, homeowners can enjoy enhanced comfort, security, and energy savings.

Another factor driving the growth of the smart homes market is the rising demand for home automation systems. Home automation enables the integration and control of various devices, creating a unified and seamless experience for homeowners. The integration of voice assistants and artificial intelligence further enhances the usability and functionality of smart home systems. These advancements have attracted a wider consumer base, including tech-savvy individuals and those seeking to simplify their daily routines.

One major challenge is the interoperability and compatibility of devices from different manufacturers. The lack of industry standards can lead to compatibility issues, limiting the seamless integration of devices within a smart home ecosystem. To overcome this challenge, new entrants should focus on developing open-platform solutions or partnering with established players to ensure compatibility across devices.

Data security and privacy are also critical concerns in the smart homes market. As smart homes collect and transmit sensitive data, such as personal preferences and usage patterns, ensuring robust security measures is vital. New entrants should prioritize cybersecurity and privacy protection to gain the trust of consumers.

Despite the challenges, the smart homes market offers ample opportunities for new entrants. With the increasing demand for smart home solutions, there is room for innovation and differentiation. New entrants can focus on developing affordable and user-friendly solutions, targeting specific customer segments or niche markets. Additionally, partnerships and collaborations with established players, such as device manufacturers, service providers, and platform developers, can help new entrants leverage existing infrastructure and reach a wider customer base.

James Hardie shares plunged 30% following a 29% quarterly profit drop, driven by a severe slowdown in the US housing market as homeowners delay projects and new construction faces affordability constraints.

Graph and download economic data for Housing Inventory: Median Days on Market in Virginia Beach-Norfolk-Newport News, VA-NC (CBSA) (MEDDAYONMAR47260) from Jul 2016 to Aug 2025 about Virginia Beach, VA, NC, median, and USA.

Case Shiller Home Price Index in the United States decreased to 342.90 points in June from 343.04 points in May of 2025. This dataset provides the latest reported value for - United States S&P Case-Shiller Home Price Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Delve into the US prefab homes market for 2025, showcasing robust growth in consumption and production amid shifting import and export trends.