53 datasets found
  1. Number of home sales in the U.S. 2014-2024 with forecast until 2026

    • statista.com
    • ai-chatbox.pro
    Updated May 16, 2025
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    Statista (2025). Number of home sales in the U.S. 2014-2024 with forecast until 2026 [Dataset]. https://www.statista.com/statistics/275156/total-home-sales-in-the-united-states-from-2009/
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    Dataset updated
    May 16, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The number of home sales in the United States peaked in 2021 at almost seven million after steadily rising since 2018. Nevertheless, the market contracted in the following year, with transaction volumes falling to 4.8 million. Home sales remained muted in 2024, with a mild increase expected in 2025 and 2026. A major factor driving this trend is the unprecedented increase in mortgage interest rates due to high inflation. How have U.S. home prices developed over time? The average sales price of new homes has also been rising since 2011. Buyer confidence seems to have recovered after the property crash, which has increased demand for homes and also the prices sellers are demanding for homes. At the same time, the affordability of U.S. homes has decreased. Both the number of existing and newly built homes sold has declined since the housing market boom during the coronavirus pandemic. Challenges in housing supply The number of housing units in the U.S. rose steadily between 1975 and 2005 but has remained fairly stable since then. Construction increased notably in the 1990s and early 2000s, with the number of construction starts steadily rising, before plummeting amid the infamous housing market crash. Housing starts slowly started to pick up in 2011, mirroring the economic recovery. In 2022, the supply of newly built homes plummeted again, as supply chain challenges following the COVID-19 pandemic and tariffs on essential construction materials such as steel and lumber led to prices soaring.

  2. U

    Inflation Data

    • dataverse-staging.rdmc.unc.edu
    • dataverse.unc.edu
    Updated Oct 9, 2022
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    Linda Wang; Linda Wang (2022). Inflation Data [Dataset]. http://doi.org/10.15139/S3/QA4MPU
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    Dataset updated
    Oct 9, 2022
    Dataset provided by
    UNC Dataverse
    Authors
    Linda Wang; Linda Wang
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This is not going to be an article or Op-Ed about Michael Jordan. Since 2009 we've been in the longest bull-market in history, that's 11 years and counting. However a few metrics like the stock market P/E, the call to put ratio and of course the Shiller P/E suggest a great crash is coming in-between the levels of 1929 and the dot.com bubble. Mean reversion historically is inevitable and the Fed's printing money experiment could end in disaster for the stock market in late 2021 or 2022. You can read Jeremy Grantham's Last Dance article here. You are likely well aware of Michael Burry's predicament as well. It's easier for you just to skim through two related videos on this topic of a stock market crash. Michael Burry's Warning see this YouTube. Jeremy Grantham's Warning See this YouTube. Typically when there is a major event in the world, there is a crash and then a bear market and a recovery that takes many many months. In March, 2020 that's not what we saw since the Fed did some astonishing things that means a liquidity sloth and the risk of a major inflation event. The pandemic represented the quickest decline of at least 30% in the history of the benchmark S&P 500, but the recovery was not correlated to anything but Fed intervention. Since the pandemic clearly isn't disappearing and many sectors such as travel, business travel, tourism and supply chain disruptions appear significantly disrupted - the so-called economic recovery isn't so great. And there's this little problem at the heart of global capitalism today, the stock market just keeps going up. Crashes and corrections typically occur frequently in a normal market. But the Fed liquidity and irresponsible printing of money is creating a scenario where normal behavior isn't occurring on the markets. According to data provided by market analytics firm Yardeni Research, the benchmark index has undergone 38 declines of at least 10% since the beginning of 1950. Since March, 2020 we've barely seen a down month. September, 2020 was flat-ish. The S&P 500 has more than doubled since those lows. Look at the angle of the curve: The S&P 500 was 735 at the low in 2009, so in this bull market alone it has gone up 6x in valuation. That's not a normal cycle and it could mean we are due for an epic correction. I have to agree with the analysts who claim that the long, long bull market since 2009 has finally matured into a fully-fledged epic bubble. There is a complacency, buy-the dip frenzy and general meme environment to what BigTech can do in such an environment. The weight of Apple, Amazon, Alphabet, Microsoft, Facebook, Nvidia and Tesla together in the S&P and Nasdaq is approach a ridiculous weighting. When these stocks are seen both as growth, value and companies with unbeatable moats the entire dynamics of the stock market begin to break down. Check out FANG during the pandemic. BigTech is Seen as Bullet-Proof me valuations and a hysterical speculative behavior leads to even higher highs, even as 2020 offered many younger people an on-ramp into investing for the first time. Some analysts at JP Morgan are even saying that until retail investors stop charging into stocks, markets probably don’t have too much to worry about. Hedge funds with payment for order flows can predict exactly how these retail investors are behaving and monetize them. PFOF might even have to be banned by the SEC. The risk-on market theoretically just keeps going up until the Fed raises interest rates, which could be in 2023! For some context, we're more than 1.4 years removed from the bear-market bottom of the coronavirus crash and haven't had even a 5% correction in nine months. This is the most over-priced the market has likely ever been. At the night of the dot-com bubble the S&P 500 was only 1,400. Today it is 4,500, not so many years after. Clearly something is not quite right if you look at history and the P/E ratios. A market pumped with liquidity produces higher earnings with historically low interest rates, it's an environment where dangerous things can occur. In late 1997, as the S&P 500 passed its previous 1929 peak of 21x earnings, that seemed like a lot, but nothing compared to today. For some context, the S&P 500 Shiller P/E closed last week at 38.58, which is nearly a two-decade high. It's also well over double the average Shiller P/E of 16.84, dating back 151 years. So the stock market is likely around 2x over-valued. Try to think rationally about what this means for valuations today and your favorite stock prices, what should they be in historical terms? The S&P 500 is up 31% in the past year. It will likely hit 5,000 before a correction given the amount of added liquidity to the system and the QE the Fed is using that's like a huge abuse of MMT, or Modern Monetary Theory. This has also lent to bubbles in the housing market, crypto and even commodities like Gold with long-term global GDP meeting many headwinds in the years ahead due to a...

  3. F

    All-Transactions House Price Index for the United States

    • fred.stlouisfed.org
    json
    Updated May 27, 2025
    + more versions
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    (2025). All-Transactions House Price Index for the United States [Dataset]. https://fred.stlouisfed.org/series/USSTHPI
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    jsonAvailable download formats
    Dataset updated
    May 27, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for All-Transactions House Price Index for the United States (USSTHPI) from Q1 1975 to Q1 2025 about appraisers, HPI, housing, price index, indexes, price, and USA.

  4. A

    Affordable Housing Market Report

    • promarketreports.com
    doc, pdf, ppt
    Updated Feb 11, 2025
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    Pro Market Reports (2025). Affordable Housing Market Report [Dataset]. https://www.promarketreports.com/reports/affordable-housing-market-26535
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    ppt, doc, pdfAvailable download formats
    Dataset updated
    Feb 11, 2025
    Dataset authored and provided by
    Pro Market Reports
    License

    https://www.promarketreports.com/privacy-policyhttps://www.promarketreports.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    Affordable Housing Market Analysis The global affordable housing market is projected to reach $1,983.52 billion by 2033, exhibiting a CAGR of 4.71% from 2025 to 2033. The rising population, urbanization, affordability crisis, and supportive government policies are the primary drivers fueling market growth. The increasing demand for affordable single-family homes, multi-family units, and townhouses, coupled with the adoption of innovative construction methods like prefabrication, 3D printing, and sustainable construction, are key trends shaping the market. The market faces restraints such as escalating land and construction costs, regulatory challenges, and the shortage of skilled labor. Nevertheless, the emergence of crowdfunding platforms and non-profit organizations providing financial assistance, as well as government subsidies and tax incentives, are expected to mitigate these constraints. The market is segmented based on housing type, funding source, construction method, and target demographics. D.R. Horton, Taylor Morrison, PulteGroup, Zillow, Hovnanian Enterprises, and Lennar Corporation are notable companies in the global affordable housing market, with operations in key regions like North America, Europe, and Asia Pacific. Recent developments include: Recent developments in the Affordable Housing Market have highlighted the urgent need for innovative housing solutions as governments and organizations strive to address the growing housing crisis exacerbated by economic challenges and population growth. Various nations are prioritizing policies that encourage public-private partnerships to stimulate investment in affordable housing initiatives. Additionally, the integration of sustainable building practices and smart technologies is gaining traction as stakeholders aim to improve energy efficiency while reducing construction costs. Recent collaborations among international entities and local governments focus on leveraging funding for housing projects, particularly in urban areas where demand is surging. Moreover, rising material costs and labor shortages are prompting stakeholders to explore alternative building materials and methods, including modular construction and 3D printing, to streamline processes. These trends underscore a collective commitment to creating equitable housing opportunities while navigating the complexities of market dynamics, aiming for significant progress by 2032. Overall, this evolving landscape reflects a concerted effort to promote affordability, sustainability, and accessibility in housing worldwide.. Key drivers for this market are: Green building technologies adoption Public-private partnerships expansion Innovative financing solutions development Urban regeneration projects implementation Digital platforms for housing access. Potential restraints include: rising urbanization, government initiatives; increasing housing demand; socioeconomic disparities; affordable financing options.

  5. Residential Real Estate in China - Market Research Report (2015-2030)

    • ibisworld.com
    Updated Apr 1, 2025
    + more versions
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    IBISWorld (2025). Residential Real Estate in China - Market Research Report (2015-2030) [Dataset]. https://www.ibisworld.com/china/market-research-reports/residential-real-estate-industry/
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    Dataset updated
    Apr 1, 2025
    Dataset authored and provided by
    IBISWorld
    License

    https://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/

    Time period covered
    2015 - 2030
    Area covered
    China
    Description

    Revenue for the Residential Real Estate industry in China is expected to decrease at a CAGR of 9.8% over the five years through 2025. This trend includes an expected decrease of 9.6% in the current year.Since August 2020, the People's Bank of China and the China Banking and Insurance Regulatory Commission have proposed three debt indicators for real estate development and management companies through which the company's financial health can be rated. This new policy has exacerbated the company's debt pressure, making it unable to repay old debts by borrowing new debt. Some real estate companies faced a liquidity crisis.In 2022, the city's lockdown and laying-off caused by COVID-19 epidemic led to the pressure of delaying the delivery of houses. The industry's newly constructed and completed areas decreased significantly throughout the year. In addition, the epidemic has impacted sales in the industry, and some sales offices have been forced to close temporarily. In 2022, the residential sales area decreased by 26.8%, and the residential sales decreased by 31.2%.Industry revenue will recover at an annualized 0.7% over the five years through 2030. Over the next five years, the industry's drag on GDP will weaken, and industry growth will stabilize. However, high housing prices have become a major social problem in China. Under the measures on the principle that residential real estate is used for living, not speculation, the financial attributes of real estate will gradually weaken, and housing prices will tend to stabilize.

  6. F

    Median Sales Price of Houses Sold for the United States

    • fred.stlouisfed.org
    json
    Updated Apr 23, 2025
    + more versions
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    (2025). Median Sales Price of Houses Sold for the United States [Dataset]. https://fred.stlouisfed.org/series/MSPUS
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    jsonAvailable download formats
    Dataset updated
    Apr 23, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q1 2025 about sales, median, housing, and USA.

  7. T

    United Kingdom House Price Index

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated May 15, 2025
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    TRADING ECONOMICS (2025). United Kingdom House Price Index [Dataset]. https://tradingeconomics.com/united-kingdom/housing-index
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    json, excel, xml, csvAvailable download formats
    Dataset updated
    May 15, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1983 - May 31, 2025
    Area covered
    United Kingdom
    Description

    Housing Index in the United Kingdom decreased to 511.50 points in May from 513.50 points in April of 2025. This dataset provides - United Kingdom House Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  8. f

    Approximated hazard rate.

    • plos.figshare.com
    xls
    Updated Sep 6, 2024
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    Kwangwon Ahn; Minhyuk Jeong; Jinu Kim; Domenico Tarzia; Ping Zhang (2024). Approximated hazard rate. [Dataset]. http://doi.org/10.1371/journal.pone.0309483.t005
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    xlsAvailable download formats
    Dataset updated
    Sep 6, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Kwangwon Ahn; Minhyuk Jeong; Jinu Kim; Domenico Tarzia; Ping Zhang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Housing markets are often characterized by price bubbles, and governments have instituted policies to stabilize them. Under this circumstance, this study addresses the following questions. (1) Does policy tightening change expectations in housing prices, revealing a regime change? (2) If so, what determines the housing market’s reaction to policy tightening? To answer these questions, we examine the effects of policy tightening that occurred in 2016 on the Chinese housing market where a price boom persisted in the post-2000 period. Using a log-periodic power law model and employing a modified multi-population genetic algorithm for parameter estimation, we find that tightening policy in China did not cause a market crash; instead, shifting the Chinese housing market from faster-than-exponential growth to a soft landing. We attribute this regime shift to low sensitivity in the Chinese housing market to global perturbations. Our findings suggest that government policies can help stabilize housing prices and improve market conditions when implemented expediently. Moreover, policymakers should consider preparedness for the possibility of an economic crisis and other social needs (e.g., housing affordability) for overall social welfare when managing housing price bubbles.

  9. J

    Bubbles and Crises: The Role of House Prices and Credit (replication data)

    • journaldata.zbw.eu
    • jda-test.zbw.eu
    pdf, txt, zip
    Updated Dec 7, 2022
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    André K. Anundsen; Karsten R. Gerdrup; Frank Hansen; Kasper Kragh-Sørensen; André K. Anundsen; Karsten R. Gerdrup; Frank Hansen; Kasper Kragh-Sørensen (2022). Bubbles and Crises: The Role of House Prices and Credit (replication data) [Dataset]. http://doi.org/10.15456/jae.2022326.0700526408
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    zip(4237174), txt(10822), pdf(546815)Available download formats
    Dataset updated
    Dec 7, 2022
    Dataset provided by
    ZBW - Leibniz Informationszentrum Wirtschaft
    Authors
    André K. Anundsen; Karsten R. Gerdrup; Frank Hansen; Kasper Kragh-Sørensen; André K. Anundsen; Karsten R. Gerdrup; Frank Hansen; Kasper Kragh-Sørensen
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This paper utilizes quarterly panel data for 20 OECD countries over the period 1975:Q1-2014:Q2 to explore the importance of house prices and credit in affecting the likelihood of a financial crisis. Estimating a set of multivariate logit models, we find that booms in credit to both households and non-financial enterprises are important to account for when evaluating the stability of the financial system. In addition, we find that global housing market developments have predictive power for domestic financial stability. Finally, econometric measures of bubble-like behavior in housing and credit markets enter with positive and highly significant coefficients. Specifically, we find that the probability of a crisis increases markedly when bubble-like behavior in house prices coincides with high household leverage.

  10. J

    Econometric Regime Shifts and the US Subprime Bubble (replication data)

    • journaldata.zbw.eu
    • jda-test.zbw.eu
    csv, txt, xls
    Updated Dec 7, 2022
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    André K. Anundsen; André K. Anundsen (2022). Econometric Regime Shifts and the US Subprime Bubble (replication data) [Dataset]. http://doi.org/10.15456/jae.2022321.0717877140
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    txt(7117), xls(46667), csv(35030), xls(14240), csv(12938)Available download formats
    Dataset updated
    Dec 7, 2022
    Dataset provided by
    ZBW - Leibniz Informationszentrum Wirtschaft
    Authors
    André K. Anundsen; André K. Anundsen
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    Using aggregate quarterly data for the period 1975:Q1-2010:Q4, I find that the US housing market changed from a stable regime with prices determined by fundamentals, to a highly unstable regime at the beginning of the previous decade. My results indicate that these imbalances could have been detected with the aid of real-time econometric modeling. With reference to Stiglitz's general conception of a bubble, I use the econometric results to construct two bubble indicators, which clearly demonstrate the transition to an unstable regime in the early 2000s. The indicators are shown to Granger cause a set of coincident indicators and financial (in)stability measures. Finally, it is shown that the increased subprime exposure during the 2000s can explain the econometric breakdown, i.e.?the housing bubble may be attributed to the increased borrowing to a more risky segment of the market.

  11. F

    Real Residential Property Prices for China

    • fred.stlouisfed.org
    json
    Updated Mar 27, 2025
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    (2025). Real Residential Property Prices for China [Dataset]. https://fred.stlouisfed.org/series/QCNR628BIS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Mar 27, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Description

    Graph and download economic data for Real Residential Property Prices for China (QCNR628BIS) from Q2 2005 to Q4 2024 about China, residential, HPI, housing, real, price index, indexes, and price.

  12. F

    Residential Property Prices for Japan

    • fred.stlouisfed.org
    json
    Updated May 28, 2025
    + more versions
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    (2025). Residential Property Prices for Japan [Dataset]. https://fred.stlouisfed.org/series/QJPN628BIS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    May 28, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Description

    Graph and download economic data for Residential Property Prices for Japan (QJPN628BIS) from Q1 1955 to Q4 2024 about Japan, residential, HPI, housing, price index, indexes, and price.

  13. d

    Replication Data for: How Global is the Affordable Housing Crisis?...

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 22, 2023
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    Coupe, Tom (2023). Replication Data for: How Global is the Affordable Housing Crisis? International Journal of Housing Markets and Analysis [Dataset]. http://doi.org/10.7910/DVN/NVGSV7
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    Dataset updated
    Nov 22, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Coupe, Tom
    Description

    these are the Replication files for: How Global is the Affordable Housing Crisis? accepted by the International Journal of Housing Markets and Analysis

  14. House price change forecast in Spain and Portugal 2023, with a forecast by...

    • statista.com
    Updated Feb 16, 2024
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    Statista (2024). House price change forecast in Spain and Portugal 2023, with a forecast by 2025 [Dataset]. https://www.statista.com/statistics/1165916/residential-real-estate-price-forecast-change-in-spain-and-portugal/
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    Dataset updated
    Feb 16, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Dec 2022
    Area covered
    Spain, Portugal
    Description

    House prices in Spain are forecast to fall in 2024, after increasing by 1.2 percent in 2023. Nevertheless, prices are expected to pick up in 2025, with an increase of one percent. The Portuguese housing market, on the other hand, grew by 5.5 percent in 2023, but was forecast to contract in the next two years.

  15. Forecast house price growth in the UK 2024-2028

    • statista.com
    Updated Jun 11, 2024
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    Statista (2024). Forecast house price growth in the UK 2024-2028 [Dataset]. https://www.statista.com/statistics/376079/uk-house-prices-forecast/
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    Dataset updated
    Jun 11, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 2023
    Area covered
    United Kingdom
    Description

    Just as in many other countries, the housing market in the UK grew substantially during the coronavirus pandemic, fueled by robust demand and low borrowing costs. Nevertheless, high inflation and the increase in mortgage rates has led to house price growth slowing down. According to the forecast, 2024 is expected to see house prices decrease by three percent. Between 2024 and 2028, the average house price growth is projected at 2.7 percent. A contraction after a period of continuous growth In June 2022, the UK's house price index exceeded 150 index points, meaning that since 2015 which was the base year for the index, house prices had increased by 50 percent. In just two years, between 2020 and 2022, the index surged by 30 index points. As the market stood in December 2023, the average price for a home stood at approximately 284,691 British pounds. Rents are expected to continue to grow According to another forecast, the prime residential market is also expected to see rental prices grow in the next years. Growth is forecast to be stronger in 2024 and slow down in the period between 2025 and 2028. The rental market in London is expected to follow a similar trend, with Central London slightly outperforming Greater London.

  16. Crisis 2008-2009 Housing Data

    • kaggle.com
    zip
    Updated Aug 31, 2019
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    Ievgen Iosifov (2019). Crisis 2008-2009 Housing Data [Dataset]. https://www.kaggle.com/eiosifov/crisis-20082009-housing-data
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    zip(1727 bytes)Available download formats
    Dataset updated
    Aug 31, 2019
    Authors
    Ievgen Iosifov
    Description

    Context

    Data augmentation for housing prices

    Content

    US Housing Data for 2008-2009 (pre crisis and crisis year) to predict housing prices more accurate

    Inspiration

    Housing price prediction competition on Kaggle

  17. k

    Skyline Champion (SKY) Riding the Housing Wave: Is This a Dip or a Crash?...

    • kappasignal.com
    Updated Aug 5, 2024
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    KappaSignal (2024). Skyline Champion (SKY) Riding the Housing Wave: Is This a Dip or a Crash? (Forecast) [Dataset]. https://www.kappasignal.com/2024/08/skyline-champion-sky-riding-housing.html
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    Dataset updated
    Aug 5, 2024
    Dataset authored and provided by
    KappaSignal
    License

    https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html

    Description

    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.

    Skyline Champion (SKY) Riding the Housing Wave: Is This a Dip or a Crash?

    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

  18. Replication dataset and calculations for PIIE PB 14-21, Is China's Property...

    • piie.com
    Updated Aug 1, 2014
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    Li-Gang Liu (2014). Replication dataset and calculations for PIIE PB 14-21, Is China's Property Market Heading toward Collapse?, by Li-Gang Liu. (2014). [Dataset]. https://www.piie.com/publications/policy-briefs/chinas-property-market-heading-toward-collapse
    Explore at:
    Dataset updated
    Aug 1, 2014
    Dataset provided by
    Peterson Institute for International Economicshttp://www.piie.com/
    Authors
    Li-Gang Liu
    Area covered
    China
    Description

    This data package includes the underlying data and files to replicate the calculations, charts, and tables presented in Is China's Property Market Heading toward Collapse?, PIIE Policy Brief 14-21. If you use the data, please cite as: Liu, Li-Gang. (2014). Is China's Property Market Heading toward Collapse?. PIIE Policy Brief 14-21. Peterson Institute for International Economics.

  19. f

    Descriptive statistics of housing bubble index.

    • plos.figshare.com
    xls
    Updated Jan 11, 2024
    + more versions
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    Wei Fan; Yun He; Liang Hao; Fan Wu (2024). Descriptive statistics of housing bubble index. [Dataset]. http://doi.org/10.1371/journal.pone.0295311.t003
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    xlsAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Wei Fan; Yun He; Liang Hao; Fan Wu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Moderate rising of house prices are beneficial to the economic development. However, over high house prices worsen the economic distortions and thus hinder the development of the real economy. We use the stochastic frontier models to calculate the fundamental value in the housing in Chinese large and medium cities, and then obtain indexes which could measure the house prices’ deviations from the fundamental value. With the macroeconomic data in the city-level, this paper empirically investigates the effects of the house prices’ deviations on macro-economic variables like consumption, investment and output. The study reveals that the housing bubble exists in most Chinese cities, and first-tier cities fare the worst. House prices over the fundamental value, which could increase the scale of real estate investment, bring adverse impacts on GDP, as it causes declining civilian consumption and discourages real economy’s investment and production. The encouragement and the discouragement on macroeconomy caused by house prices’ deviation from its basic value take turns to play a key role in the process of China’ eco-nomic growth. In the early stage of China’s economic growth, the encouragement effect predominates. As urbanization and industrialization gradually upgrade to a higher level, the discouragement effect takes charge.

  20. Estate Agents in Germany - Market Research Report (2015-2030)

    • ibisworld.com
    Updated Aug 15, 2024
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    IBISWorld (2024). Estate Agents in Germany - Market Research Report (2015-2030) [Dataset]. https://www.ibisworld.com/germany/industry/estate-agents/949/
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    Dataset updated
    Aug 15, 2024
    Dataset authored and provided by
    IBISWorld
    License

    https://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/

    Time period covered
    2014 - 2029
    Area covered
    Germany
    Description

    The property brokerage sector was hardly affected by the coronavirus crisis and the war in Ukraine. Demand for residential property in urban areas is very high, while demand for office and retail space collapsed in 2020. The slump in demand for commercial space was largely absorbed by industry players, as many companies sold their commercial properties and rented them themselves in order to increase their liquidity in the short term. These sale-and-lease-back transactions often required advice from industry players. Due to the weak development on the commercial property market, turnover is expected to fall by 0.9% to 12.8 billion euros in the current year. On average, a decline in turnover of 3.3% per year has been observed over the past five years. The increased regulation of the property market, such as the rent freeze, has also contributed to this. Politicians have also responded to the sometimes low level of qualification of estate agents by making further training certificates a legal requirement.Despite rising property prices, estate agents are still benefiting from a high willingness to invest in property as a capital investment in the current year. One reason for this is the high level of rents. However, the high level of interest rates reduces the incentives to invest in a home if the client is reliant on borrowed capital. The short supply of properties is driving up property prices in many German cities and is a major factor in the high level of brokerage fees that estate agents receive for successful brokerage. In addition, residential property is considered an attractive capital investment, especially for wealthy private individuals and investors, which is considered crisis-proof in times of volatile securities markets and persistent inflation.Over the next five years up to and including 2029, IBISWorld expects industry turnover to increase by an average of 0.2% per year to an estimated 12.9 billion euros. While the number of commercial property sales will fall due to the negative impact of working from home and online retail, industry players will benefit from recovering demand on the residential property market. Demand for residential property will once again benefit from the reputation of residential property as a crisis-proof investment, even if the high level of interest rates will continue to dampen demand somewhat. In order to remain competitive in a highly fragmented market with low barriers to market entry, companies must increasingly focus on high-quality service offerings.

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Statista (2025). Number of home sales in the U.S. 2014-2024 with forecast until 2026 [Dataset]. https://www.statista.com/statistics/275156/total-home-sales-in-the-united-states-from-2009/
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Number of home sales in the U.S. 2014-2024 with forecast until 2026

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Dataset updated
May 16, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

The number of home sales in the United States peaked in 2021 at almost seven million after steadily rising since 2018. Nevertheless, the market contracted in the following year, with transaction volumes falling to 4.8 million. Home sales remained muted in 2024, with a mild increase expected in 2025 and 2026. A major factor driving this trend is the unprecedented increase in mortgage interest rates due to high inflation. How have U.S. home prices developed over time? The average sales price of new homes has also been rising since 2011. Buyer confidence seems to have recovered after the property crash, which has increased demand for homes and also the prices sellers are demanding for homes. At the same time, the affordability of U.S. homes has decreased. Both the number of existing and newly built homes sold has declined since the housing market boom during the coronavirus pandemic. Challenges in housing supply The number of housing units in the U.S. rose steadily between 1975 and 2005 but has remained fairly stable since then. Construction increased notably in the 1990s and early 2000s, with the number of construction starts steadily rising, before plummeting amid the infamous housing market crash. Housing starts slowly started to pick up in 2011, mirroring the economic recovery. In 2022, the supply of newly built homes plummeted again, as supply chain challenges following the COVID-19 pandemic and tariffs on essential construction materials such as steel and lumber led to prices soaring.

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