Jumbo 30-Year Fixed Mortgage Rates

Zillow Home Value Forecast and Cash Buyer Data

By Zillow Data [source]

About this dataset

This dataset tracks the average jumbo mortgage rate quoted on Zillow Mortgages for a 30-year, fixed-rate, jumbo mortgage in one-hour increments during business hours. It provides insight into changes in the housing market and helps consumers make wiser decisions with their investments. In addition to tracking monthly mortgage rates, our dataset also covers consumer's home types and housing stock, cash buyer data, Zillow Home Value Forecast (ZHVF), negative equity metrics, affordability forecasts for both mortgages and rents as well as historic data including historical ZHVI and household income. With this unique blend of financial and real estate information, users are empowered to make more informed decisions about their investments. The data is updated weekly with the most recent statistics available so that users always have access to up-to-date information

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How to use the dataset

How to Use This Dataset:

• To start exploring this dataset, identify what type of home you are interested in by selecting one of the four categories: “all homes” (Zillow defines all homes as single family, condominiums and coops with a county record); multifamily 5+; duplex/triplex; or condos/coops.
• Understand additional data products that are included such as Zillow Home Value Forecast (ZHVF), Cash Buyers % share, affordability metrics like mortgage affordability or rental affordability and historical ZHVI values along with its median value for particular households or geographies which needs deeper insights into other endogenous variables such detailed information like how many bedrooms a house has etc.

• Choose your geographic region on which you would want to collect more information– regions could include city breakdowns from nationwide level down till specific metropolitan etc . Also use special crosswalks available if needed between federally defined metrics for counties / metro areas combined with Zillow's own ones for greater accuracy when analysing external facors effect on data . To download all datasets at once - click here. .

• Gather more relevant external factors for analysis such as home values forecasts using our published methodology post given url , further to mention TransUnion credit bureau related debt amounts also consider median household incomes vis Bureaus of Labor Cost Indexes ; All these give us greater dimensional insights into market dynamics affecting any particular region finally culminating into deeper research findings when taken together . The reasons behind any fluctions observed can be properly derived as a result .

          Finally make sure that proper attribution is alwys done following mentioned Terms Of Use while downloading since 'All Data Accessed And Downloaded From This Page Is Free For Public Use By Consumers , Media
  

Research Ideas

• Using the Mortgage Rate Data to devise strategies to help persons purchasing jumbo mortgages determine the best time and rates to acquire a loan.
• Analyzing trends in the market by investigating changes in affordability over time by studying rent and mortgage affordability, price-to-income ratios, and historical ZHVIs with cash buyers.
• Comparing different areas of housing markets over diverse geographies using data on all homes, condos/co-ops, multifamily dwellings 5+ units, duplexes/triplexes across various counties or metro areas

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: MortgageRateJumboFixed.csv | Column name | Description | |:---------------------------|:---------------------------------------------------------------------------------------------------------------| | Date | The date of the mortgage rate. (Date) | | TimePeriod | The time period of the ...

Total-Other-Finance-Cost Time Series for Zillow Group Inc. Zillow Group, Inc. operates real estate brands in mobile applications and Websites in the United States. The company offers premier agent and rentals marketplaces, new construction marketplaces, advertising, display advertising, and business technology solutions, as well as dotloop, a real estate transaction management SaaS solution. It also provides mortgage originations and the sale of mortgages, and advertising to mortgage lenders and other mortgage professionals; and title and escrow services. In addition, the company's brand portfolio includes Zillow Premier Agent, Zillow Home Loans, Zillow Rentals, Trulia, StreetEasy, HotPads, and Out East; and a suite of marketing software and technology solutions for the real estate industry, including ShowingTime+, Spruce, and Follow Up Boss. Zillow Group, Inc. was incorporated in 2004 and is headquartered in Seattle, Washington.

Negative Equity Trends in US Housing Markets

Time Series Data Across Regions and Housing Types

By Zillow Data [source]

About this dataset

• This unique dataset explores the trends in negative equity within US housing markets from 2011 to 2017, allowing users to uncover the various factors and determinants that affected the outcome in each market. With data provided on all home types such as single-family homes, condominiums, and co-ops, as well as special metrics such as cash buyers and affordability analyses, you will be able to gain a comprehensive understanding of how these forces have interacted over time. Using this data you can not only learn more about historical behavior but also make predictions for future trends in these impacts.

• In addition to data collected by Zillow through their own internal resources, they have also partnered with TransUnion and other affiliate sources to give an even more precise look into what has been driving these changing dynamics across US housing markets. Such information includes negative equity metrics which allow us to track actual outstanding home-related debt amounts over time - a valuable resource when evaluating potential investments or relocations!

• And of course with any dataset there are a few guiding principles that one should take note of before delving in – this is especially true when it comes down to copyright issues or prohibited uses; though all data can be freely obtained here for public use - clear attribution of such information is legally required at all times (as stated on Zillow’s very own Terms & Conditions page). Furthermore additional resources such as Mortgage Rate Series or Jumbo Mortgages are also available through Zillow; again making sure that appropriate disclaimers are read before utilizing them.

Regardless this little treasure trove of knowledge is waiting at your fingertips – whether you’re trying your luck investing wise or just looking for an area where renting rates are equitable compared real estate values; it provides everything you need understand regional housing market fluctuations over the last half decade!

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How to use the dataset

This dataset provides historical and current trends in negative equity (the amount a mortgage is underwater) across the United States. It contains negative equity data from Zillow, one of the leading real estate data providers. The dataset covers all housing types (including single family, condominiums and co-ops). Additionally, it includes cash buyers share, mortgage affordability index, rental affordability index and other relative measures of affordability for US metro areas. This guide will help you understand how to use this data set for your own analysis.

Overview of Covered Data:

The dataset contains time series data that shows your current trend in negative equity rate as well as some associated metrics across different scales such as region, county, city and MSA level. To access this information you will need to take following columns into consideration while using this data set:

• RegionName: Name of the region (e.g., city/county/MSA)
• SizeRank: Ranking of the region by size
• RegionType: Type of region (e.g., city/county/state)
• StateName: Name of the state
• MSA: Metropolitan Statistical Area FORMAT_4C A4 RINFOX_ RTI Information Exchange File Format [multi value 9] FORMAT_3E A3 FITS Flexible Image Transport System VERSION 4C 3E 1 Language Indicator 0 0 1 1 DONTCOPY 536880031 FILEEXTN 3 Stream Type buffer 'USTD' file version 2 HNEED 8 FILETYPE 'UDIO' creation date 05 FEB 1985 Source FMT0025 APPLICAT TRAINFORM File Organization Spooled Files DF140520 Header Block Length in Words 682 with Header Offset 636 / ULQUACK INTLCHAN * ETBFMT(V7R2),D*RECORD ACCOUNT CRFTIME FT240187 batch process status continuous Availability Continuous Version number V03C02 LOADAT AT04

Research Ideas

• Analyzing which markets have been disproportionately affected by the housing crisis and utilizing this information to inform investment strategies and...

Context

Zillow's Economic Research Team collects, cleans and publishes housing and economic data from a variety of public and proprietary sources. Public property record data filed with local municipalities -- including deeds, property facts, parcel information and transactional histories -- forms the backbone of our data products, and is fleshed out with proprietary data derived from property listings and user behavior on Zillow.

The large majority of Zillow's aggregated housing market and economic data is made available for free download at zillow.com/data.

Content

Variable Availability:

Zillow Home Value Index (ZHVI): A smoothed seasonally adjusted measure of the median estimated home value across a given region and housing type. A dollar denominated alternative to repeat-sales indices. Find a more detailed methodology here: http://www.zillow.com/research/zhvi-methodology-6032/

Zillow Rent Index (ZRI): A smoothed seasonally adjusted measure of the median estimated market rate rent across a given region and housing type. A dollar denominated alternative to repeat-rent indices. Find a more detailed methodology here: http://www.zillow.com/research/zillow-rent-index-methodology-2393/

For-Sale Listing/Inventory Metrics: Zillow provides many variables capturing current and historical for-sale listings availability, generally from 2012 to current. These variables include median list prices and inventory counts, both by various property types. Variables capturing for-sale market competitiveness including share of listings with a price cut, median price cut size, age of inventory, and the days a listing spend on Zillow before the sale is final.

Home Sales Metrics: Zillow provides data on sold homes including median sale price by various housing types, sale counts (methodology here: http://www.zillow.com/research/home-sales-methodology-7733/), and a normalized view of sale volume referred to as turnover. The prevalence of foreclosures is also provided as ratio of the housing stock and the share of all sales in which the home was previously foreclosed upon.

For-Rent Listing Metrics: Zillow provides median rents prices and median rent price per square foot by property type and bedroom count.

Housing type definitions:

All Homes: Zillow defines all homes as single-family, condominium and co-operative homes with a county record. Unless specified, all series cover this segment of the housing stock.

Condo/Co-op: Condominium and co-operative homes.

Multifamily 5+ units: Units in buildings with 5 or more housing units, that are not a condominiums or co-ops.

Duplex/Triplex: Housing units in buildings with 2 or 3 housing units.

Tiers: By metro, we determine price tier cutoffs that divide the all homes housing stock into thirds using the full distribution of estimated home values. We then estimate real estate metrics within the property sets, Bottom, Middle, and Top, defined by these cutoffs. When reported at the national level, all Bottom Tier homes defined at the metro level are pooled together to form the national bottom tier. The same holds for Middle and Top Tier homes.

Regional Availability:

Zillow metrics are reported for common US geographies including Nation, State, Metro (2013 Census Defined CBSAs), County, City, ZIP code, and Neighborhood.

We provide a crosswalk between colloquial Zillow region names and federally defined region names and linking variables such as County FIPS codes and CBSA codes. Cities and Neighborhoods do not match standard jurisdictional boundaries. Zillow city boundaries reflect mailing address conventions and so are often visually similar to collections of ZIP codes. Zillow neighborhood boundaries can be found here.

Suppression Rules: To ensure reliability of reported values the Zillow Economic Research team applies suppression rules triggered by low sample sizes and excessive volatility. These rules are customized to the metric and region type and explain most missingness found in the provided datasets.

Additional Data Products

The following data products and more are available for free download exclusively at [Zillow.com/Data][1]:

• Zillow Home Value Forecast
• Zillow Rent Forecast
• Negative Equity (the share of mortgaged properties worth less than mortgage balance)
• Zillow Home Price Expectations Survey
• Zillow Housing Aspirations Report
• Zillow Rising Sea Levels Research
• Cash Buyers Time Series
• Buy vs. Rent Breakeven Horizon
• Mortgage Affordability, Rental Affordability, Price-to-Income Ratio
• Conventional 30-year Fixed Mortgage Rate, Weekly Time Series
• Jumbo 30-year Fixed Mortgage Rates, Weekly Time Series

Acknowledgements

The mission of the Zillow Economic Research Team is to be the most open, authoritative source for timely and accurate housing data and unbiased insight. We...

Rental Affordability Analysis Based on Median Income

Trends in Tier-Based Affordability Across the U.S

By Zillow Data [source]

About this dataset

This dataset contains rental affordability data for different regions in the US, giving valuable insights into regional rental markets. Renters can use this information to identify where their budget will go the farthest. The cities are organized by rent tier in order to analyze affordability trends within and between different housing stock types. Within each region, the data includes median household income, Zillow Rent Index (ZRI), and percent of income spent on rent.

The Zillow Home Value Forecast (ZHVF) is used to calculate future combined mortgage pay/rent payments in each region using current median home prices, actual outstanding debt amounts and 30-year fixed mortgage interest rates reported through partnership with TransUnion credit bureau. Zillow also provides a breakdown of cash vs financing purchases for buyers looking for an investment or cash option solution.

This dataset provides an effective tool for consumers who want to better understand how their budget fits into diverse rental markets across the US; from condominiums and co-ops, multifamily residences with five or more units, duplexes and triplexes - every renter can determine how their housing budget should be adjusted as they consider multiple living possibilities throughout the country based on real-time price data!

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How to use the dataset

Introduction

Getting Started

• First, you'll need to download the TieredAffordability_Rental.csv dataset from this Kaggle page onto your computer or device.

• After downloading the data set onto your device, open it with any CSV viewing software of your choice (ex: Excel). It will include columns for RegionName**RegionName** , homes type/housing stock (All Homes or Condo/Co-op) SizeRank , Rent tier tier , Date date , median household income income , Zillow Rent Index zri and PercentIncomeSpentOnRent percentage (what portion of monthly median house-hold goes toward monthly mortgage payment) .

• To begin analyzing rental prices across different regions using this dataset, look first at column four: SizeRank; which ranks each region based on size - smallest regions listed first and largest at last - so that you can compare a similar range of Regions when looking at affordability by home sizes larger than one unit multiplex dwellings.*Duples/Triplex*. Once there is an understanding of how all homes compare overall now it is time to consider home types Multifamily 5+ units according to rent tiers tier .

• Next, choose one or more region(s) for comparison based on their rank in SizeRank column –so that all information gathered about them reflects what portionof households fall into certain categories ; eg; All Homes / Small Home /Large Home / MultiPlex Dwelling and what tier does each size rank falls into eg.: Affordable/Slightly Expensive/ Moderately Expensive etc.. This will enable further abstraction from other elements like date vs inflation rate per month or periodical intervals set herein by Rate segmentation i e dates givenin ‘Date’Columns – making the task easier and more direct while analyzing renatalAffordibility Analysis Based On Median Income zri 00 zwi & PCISOR 00 PCIRO

Research Ideas

• Use the PercentIncomeSpentOnRent column to compare rental affordability between regions within a particular tier and determine optimal rent tiers for relocating families.
• Analyze how market conditions are affecting rental affordability over time by using the income, zri, and PercentageIncomeSpentOnRent columns.
• Identify trends in housing prices for different tiers over the years by comparing SizeRank data with Zillow Home Value Forecast (ZHVF) numbers across different regions in order to identify locations that may be headed up or down in terms of home values (and therefore rent levels)

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: TieredAffordability_Rental.csv | Column name | Description | |:-----------------------------|:-------------------------------------------------------------| | RegionName | The name of the region. (String) ...

The market for Mortgage Calculator Tools is projected to reach a value of USD XXX million by 2033, exhibiting a CAGR of XX% during the forecast period (2025-2033). Key market drivers include the rising demand for homeownership, increasing mortgage rates, and the need for financial planning tools. The growing popularity of online mortgage calculators and the increasing adoption of mobile devices further contribute to market growth. Major market players include Zillow, USMortgage, Truila, Ramsey, Veterans United, FHA, Karl's Mortgage Calculator, Mortgage Pal, Calculator.net, Rocket Mortgage, Mortgage Calculator, Pine Grove Software, CalculatorSoup, Bankrate, SmartAsset, NerdWallet, MoneyHelper, CalculateStuff, Bank of America, and Forbes Advisor. The market issegmented by application (residential, commercial, industrial) and by type (online, mobile, desktop). North America holds a significant market share due to the high penetration of mortgage services in the region, followed by Europe and Asia Pacific.

Negative Equity in U.S. Housing Market

Measuring Home Values, Debt, and Credit Risk

By Zillow Data [source]

About this dataset

This dataset, Negative Equity in the US Housing Market, provides an in-depth look into the negative equity occurring across the United States during this single quarter. Included are metrics such as total amount of negative equity in millions of dollars, total number of homes in negative equity, percentage of homes with mortgages that are in negative equity and more. These data points provide helpful insights into both regional and national trends regarding the prevalence and rate of home mortgage delinquency stemming from a diminishment of value from peak levels.

Home types available for analysis include 'all homes', condos/co-ops, multifamily units containing five or more housing units as well as duplexes/triplexes. Additionally, Cash buyers rates for particular areas can also be determined by referencing this collection. Further metrics such as mortgage affordability rates and impacts on overall indebtedness are readily calculated using information related to Zillow's Home Value Index (ZHVI) forecast methodology and TransUnion data respectively.

Other variables featured within this dataset include characteristics like region type (i.e city, county ..etc), size rank based on population values , percentage change in ZHVI since peak levels as well as loan-to-value ratio greater than 200 across all regions constituted herein (NE). Moreover Zillow's own Secondary Mortgage Market Survey data is utilized to acquire average mortgage quote rates while correlative Census Bureau NCHS median household income figures represent typical assessable proportions between wages and debt obligations . So whether you're looking to assess effects along metro lines or detailed buffering through zip codes , this database should prove sufficient for insightful explorations! Nonetheless users must strictly adhere to all conditions encompassed within Terms Of Use commitments put forth by our lead provider before accessing any resources included herewith

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Research Ideas

• Analyzing regional and state trends in negative equity: Analyze geographic differences in the percentage of mortgages “underwater”, total amount of negative equity, number of homes at least 90 days late, and other key indicators to provide insight into the factors influencing negative equity across regions, states and cities.
• Tracking the recovery rate over time: Track short-term changes in numbers related to negative equity (e.g., region or area ZHVI Change from Peak) to monitor recovery rates over time as well as how different policy interventions are affecting homeownership levels in affected areas.
• Exploring best practices for promoting housing affordability: Compare affordability metrics (e.g., mortgage payments, price-to-income ratios) across different geographic locations over time to identify best practices for empowering homeowners and promoting stability within the housing market while reducing local inequality impacts related to availability of affordable housing options and access to credit markets like mortgages/loans etc

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: NESummary_2017Q1_Public.csv | Column name | Description | |:------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------| | RegionType | The type of region (e.g., city, county, metro etc.) (String) | | City | Name of the city (String) | | County | Name of the county (String) | | State | Name of the state (String) | | Metro ...

Real Estate Breakeven Analysis for U.S. Home Types

Buy vs Rent Comparison Across Markets

By Zillow Data [source]

About this dataset

This dataset provides a comprehensive analysis of the current real estate situation in the United States. It includes breakeven analysis charts that compare buying vs renting across major U.S. markets. This dataset contains various metrics such as home types, housing stock, price-to-income ratio, cash buyers, mortgage affordability and rental affordability to name a few. This data has been compiled using Zillow's own data along with TransUnion financing survey data and the Freddie Mac Primary Mortgage Market Survey to provide an accurate understanding of each metro area’s market health and purchasing power for buyers and renters alike. By downloading this information you can compare different regions based on size rank and other factors to get full insights regarding their potential fit for your needs or investments strategies as well as any potential risks associated with each region's housing market health

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How to use the dataset

This dataset is for real estate professionals, owner-occupants, potential buyers and renters who are interested in understanding which U.S. markets offer the most favorable home buying or rental opportunities from a financial perspective over the long term.

The “Real Estate Breakeven Analysis for U.S Home Types” dataset contains data pulled from Zillow's current and forecasted housing market metrics across many different real estate regions in the United States including cities, counties, states, metro areas and combined statistical areas (CSAs). The data includes several measures of affordability such as median price-to-rent ratio (MedPR), median breakeven horizon (MedBE) - which refers to how long it takes to make up purchase costs when compared with renting; cash purchaser share; mortgage rate; mortgage affordability indices; rental affordability rates etc.

In order to analyze and compare buying vs renting decisions across various regions in the US this dataset provides breakeven analysis at various levels of geographies i.e., state names, region types (city/metro area/county) and show how long it will take homeowners to break even on their purchase costs when compared with renting in that region over a longer period of time using discounted cash flow methodology. This information helps people understand what type of transaction is a better fit for them by weighing short term vs long term goals accordingly by evaluating these different factors related to housing metrics carefully before making financial decisions about purchasing or renting properties in desired location(s).

To use this dataset one can use either basic filters like RegionType or RegionName or more detailed filter criteria like CountyName, City name , Metro area name , State Name etc . For example if someone wanted to look at properties available for rent only then they can apply filters based on Province Type =‘Rental’ Also one can further refine searches based on filtering them with defined SampleRate , Median Price – To – Rent Ratio …..etc . This could be useful if seekers would want only specific type of property like Condominium/Coop /Multifamily 5+ Units /Duplex Triplex listing etc …and then apply other parameters like Cash Buyers percent , Mortgage Affordability Rate….etc ..in order narrow down search results while looking at Breakeven scores /horizons in their target locations . One should take advantages of all relevant parameters while searching through data before making any decision related with owning rental properties so that they can make sure best possible investment decision given

Research Ideas

• Visualizing changes in real estate trends across regions by comparing price to rent ratios, mortgage affordability indices and cash buyers over time.
• Market segmentation analysis based on region-level market characteristics such as negative equity data, rental affordability, median house values and population size.
• Predicting housing demand within a particular region based on its breakeven horizon or price to rent ratio

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: BreakEven_2017-03.csv | Column name | Description | |:----------------|:----------------------------------------------------...