Net-Income Time Series for Claros Mortgage Trust Inc. Claros Mortgage Trust, Inc. operates as a real estate investment trust. It focuses on originating senior and subordinate loans on transitional commercial real estate assets in the United States. The company has elected to be taxed as a real estate investment trust. As a result, it would not be subject to federal and state income tax on that portion of its income that is distributed to shareholders if it distributes at least 90% of its taxable income and complies with certain other requirements to quality as a REIT. Claros Mortgage Trust, Inc. was incorporated in 2015 and is headquartered in New York, New York.

Interest-Income Time Series for Invesco Mortgage Capital Inc. Invesco Mortgage Capital Inc. operates as a real estate investment trust (REIT) that invests, finances, and manages mortgage-backed securities and other mortgage-related assets in the United States. It invests in residential mortgage-backed securities (RMBS) and commercial mortgage-backed securities (CMBS) that are guaranteed by the United States (U.S.) government agency or federally chartered corporation; RMBS and CMBS that are not issued or guaranteed by the U.S. government agency or federally chartered corporation; the U.S. treasury securities; real estate-related financing arrangements; to-be-announced securities forward contracts to purchase RMBS; and commercial mortgage loans. It has elected to be taxed as a REIT and would be subject to federal corporate income taxes if it distributes at least 90% of its taxable income to its stockholders. The company was incorporated in 2008 and is headquartered in Atlanta, Georgia.

SELECTED HOUSING CHARACTERISTICS SELECTED MONTHLY OWNER COSTS AS A PERCENTAGE OF HOUSEHOLD INCOME (SMOCAPI) - DP04 Universe - Housing units with a mortgage and Housing units without a mortgage Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 The information on selected monthly owner costs as a percentage of household income is the computed ratio of selected monthly owner costs to monthly household income. The ratio was computed separately for each unit and rounded to the nearest whole percentage. The data are tabulated only for owner-occupied units.

Variables Year mortgage completed, whether dwelling is wholly occupied by borrower, amount and length of mortgage, gross rate of interest, purchase price, whether an option/low-start mortgage, whether mortgage is for 100% of valuation, whether rate of interest is fixed. Whether dwelling is within authority's area, whether new, date built. Applicant's age and sex, annual income, other income, total income on which mortgage is based, whether first time as on owner-occupier, previous tenure. Mortgage code, period code, price code, applicant's age code, income code, region code. Compilation or synthesis of existing material

This table contains 50 series, with data for years 1970 - 1990 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Revenues and expenses (50 items: Net income;Net income before extraordinary transactions;Net income before income taxes;Total revenue; ...).

1. Data Source

This dataset is a synthetic version inspired by the original Credit Risk dataset on Kaggle and enriched with additional variables based on Financial Risk for Loan Approval data. SMOTENC was used to simulate new data points to enlarge the instances. The dataset is structured for both categorical and continuous features.

2. Metadata

The dataset contains 45,000 records and 14 variables, each described below:

3. Data Usage

The dataset can be used for multiple purposes:

• Exploratory Data Analysis (EDA): Analyze key features, distribution patterns, and relationships to understand credit risk factors.
• Classification: Build predictive models to classify the loan_status variable (approved/not approved) for potential applicants.
• Regression: Develop regression models to predict the credit_score variable based on individual and loan-related attributes.

Mind the data issue from the original data, such as the instance > 100-year-old as age.

This dataset provides a rich basis for understanding financial risk factors and simulating predictive modeling processes for loan approval and credit scoring.

Feel free to leave comments on the discussion. I'd appreciate your upvote if you find my dataset useful! 😀

Abstract copyright UK Data Service and data collection copyright owner.The Survey of Mortgage Lenders (SML) was launched on 1st April 1992 to succeed the 5% Sample Survey of Building Society Mortgage Completions (BSM) (See GN:33191). The aims were to improve the survey in three principal ways: a) to broaden the range of institutions surveyed to incorporate other mortgage lenders in addition to building societies and Abbey National. With the entry of the high street banks and then the centralised lenders into the mortgage market, information provided by the building societies no longer represented the whole market in the way it did when the BSM was set up in the 1960s. b) to extend its coverage to include further advances, remortgages and top-up loans in addition to first mortgages. c) to increase the level of detail on the questionnaire especially with respect to the characteristics of the mortgage loan. An important consideration for users of the data is that the SML figures allow continuity with the BSM survey results to be maintained for a reasonable period. Main Topics: Financial institution code, date mortgage completed, whether dwelling is wholly or partly occupied by borrower. Mortgage amount, type of advance, whether solely for purchase of property, period of mortgage, gross rate of interest, whether the interest charged is fixed or variable rate, whether interest payments are discounted or deferred, repayment method, source of mortgage business, purchase price and whether discounted in any way, location of dwelling, whether new, age of dwelling, type of dwelling, number of habitable rooms, number, sex and age of borrowers, basic income of main borrower, other income and total income on which mortgage is based, whether applicant previously owner occupier, previous tenure. The institutions are divided into four strata according to the size of their assets. All the largest were asked to complete questionnaires on a sample of 5 per cent of their new mortgage advances. Mortgages are included if their reference numbers end in specified digits chosen so that every twentieth mortgage is selected. Institutions in the next stratum are arranged in order of size of assets and alternate institutions chosen each of which are asked to complete questionnaires on 10 per cent of their mortgages. In the next stratum 20 per cent of the mortgages of every fourth institution are obtained. The smallest institutions are completely excluded.

Taiwan Housing Price to Income Ratio data was reported at 9.160 Times in Dec 2017. This records a decrease from the previous number of 9.220 Times for Sep 2017. Taiwan Housing Price to Income Ratio data is updated quarterly, averaging 6.735 Times from Mar 2002 (Median) to Dec 2017, with 64 observations. The data reached an all-time high of 9.460 Times in Jun 2017 and a record low of 4.150 Times in Sep 2002. Taiwan Housing Price to Income Ratio data remains active status in CEIC and is reported by Construction and Planning Agency, Ministry of the Interior. The data is categorized under Global Database’s Taiwan – Table TW.EB017: Housing Price and Housing Loan Payment to Income Ratio.

This dataset includes one dataset which was custom ordered from Statistics Canada.The table includes information on housing suitability and shelter-cost-to-income ratio by number of bedrooms, housing tenure, age of primary household maintainer, household type, and income quartile ranges for census subdivisions in British Columbia. The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom order from Statistics Canada includes the following dimensions and variables: Geography: Non-reserve CSDs in British Columbia - 299 geographies The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released. Housing Tenure Including Presence of Mortgage (5) 1. Total – Private non-band non-farm off-reserve households with an income greater than zero by housing tenure 2. Households who own 3. With a mortgage1 4. Without a mortgage 5. Households who rent Notes: 1) Presence of mortgage - Refers to whether the owner households reported mortgage or loan payments for their dwelling. 2015 Before-tax Household Income Quartile Ranges (5) 1. Total – Private households by quartile ranges1, 2, 3 2. Count of households under or at quartile 1 3. Count of households between quartile 1 and quartile 2 (median) (including at quartile 2) 4. Count of households between quartile 2 (median) and quartile 3 (including at quartile 3) 5. Count of households over quartile 3 Notes: 1) A private household will be assigned to a quartile range depending on its CSD-level location and depending on its tenure (owned and rented). Quartile ranges for owned households in a specific CSD are delimited by the 2015 before-tax income quartiles of owned households with an income greater than zero and residing in non-farm off-reserve dwellings in that CSD. Quartile ranges for rented households in a specific CSD are delimited by the 2015 before-tax income quartiles of rented households with an income greater than zero and residing in non-farm off-reserve dwellings in that CSD. 2) For the income quartiles dollar values (the delimiters) please refer to Table 1. 3) Quartiles 1 to 3 are suppressed if the number of actual records used in the calculation (not rounded or weighted) is less than 16. For cases in which the renters’ quartiles or the owners’ quartiles (figures from Table 1) of a CSD are suppressed the CSD is assigned to a quartile range depending on the provincial renters’ or owners’ quartile figures. Number of Bedrooms (Unit Size) (6) 1. Total – Private households by number of bedrooms1 2. 0 bedrooms (Bachelor/Studio) 3. 1 bedroom 4. 2 bedrooms 5. 3 bedrooms 6. 4 bedrooms Note: 1) Dwellings with 5 bedrooms or more included in the total count only. Housing Suitability (6) 1. Total - Housing suitability 2. Suitable 3. Not suitable 4. One bedroom shortfall 5. Two bedroom shortfall 6. Three or more bedroom shortfall Note: 1) 'Housing suitability' refers to whether a private household is living in suitable accommodations according to the National Occupancy Standard (NOS); that is, whether the dwelling has enough bedrooms for the size and composition of the household. A household is deemed to be living in suitable accommodations if its dwelling has enough bedrooms, as calculated using the NOS. 'Housing suitability' assesses the required number of bedrooms for a household based on the age, sex, and relationships among household members. An alternative variable, 'persons per room,' considers all rooms in a private dwelling and the number of household members. Housing suitability and the National Occupancy Standard (NOS) on which it is based were developed by Canada Mortgage and Housing Corporation (CMHC) through consultations with provincial housing agencies. Shelter-cost-to-income-ratio (4) 1. Total – Private non-band non-farm off-reserve households with an income greater than zero 2. Spending less than 30% of households total income on shelter costs 3. Spending 30% or more of households total income on shelter costs 4. Spending 50% or more of households total income on shelter costs Note: 'Shelter-cost-to-income ratio' refers to the proportion of average total income of household which is spent on shelter costs. Household Statistics (8) 1....

Operating-Income Time Series for Blackstone Mortgage Trust Inc. Blackstone Mortgage Trust, Inc., a real estate finance company, originates senior loans collateralized by commercial properties in North America, Europe, and Australia. The company originates and acquires senior, floating rate mortgage loans that are secured by a first-priority mortgage on commercial real estate assets. It operates as a real estate investment trust for federal income tax purposes. The company was formerly known as Capital Trust, Inc. and changed its name to Blackstone Mortgage Trust, Inc. in May 2013. Blackstone Mortgage Trust, Inc. was incorporated in 1998 and is headquartered in New York, New York.

SIA101 - Poverty and Deprivation Rates Before and After Rent and Mortgage Interest. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Poverty and Deprivation Rates Before and After Rent and Mortgage Interest...

SIA105 - Poverty and Deprivation Rates Before and After Rent and Mortgage Interest. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Poverty and Deprivation Rates Before and After Rent and Mortgage Interest...

Mortgage Status By Household Income Report based on US Census and American Community Survey Data.

Net-Income Time Series for Zillow Group Inc Class C. 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.

SIA107 - Poverty and Deprivation Rates Before and After Rent and Mortgage Interest. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Poverty and Deprivation Rates Before and After Rent and Mortgage Interest...

SIA108 - Poverty and Deprivation Rates Before and After Rent and Mortgage Interest. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Poverty and Deprivation Rates Before and After Rent and Mortgage Interest...

Expenditure on rent by renters and mortgages by mortgage holders, by region and age from the Living Costs and Food Survey for the financial year ending 2022. Data is presented as a proportion of total expenditure and a proportion of disposable income.

Shelter-cost-to-income ratio by tenure including presence of mortgage payments and subsidized housing for Canada, provinces and territories, census divisions and census subdivisions. Includes residence on or off reserve, and household type including census family structure.

Shelter cost by tenure including presence of mortgage payments and subsidized housing for Canada, provinces and territories, census metropolitan areas and census agglomerations. Includes shelter-cost-to-income ratio, household total income groups and household type including census family structure, off reserve.

Average weekly household expenditure on goods and services in the UK. Data are shown by region, age, income (including equivalised) group (deciles and quintiles), economic status, socio-economic class, housing tenure, output area classification, urban and rural areas (Great Britain only), place of purchase and household composition.