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Prices

Mantle Estate uses a comprehensive price calculation system for different regional markets. Prices are updated daily and track changes in residential real estate prices in real-time.

Data Sources by Region​

United States (US Markets)​

For US markets, data from Zillow — the largest real estate portal in the United States — is used.

Key Features:

  • Daily price updates
  • Data covers a wide range of property types
  • Integration with real-world real estate market

Europe (European Markets)​

For European markets, combinations of official government indices, real estate market reports, and economic databases are used.

Data Sources:

  • London: Land Registry (official transaction registry) with hedonic quality and location adjustments
  • Paris: INSEE and Notaires de France — Secondary housing price index
  • Berlin: Destatis (Federal Statistical Office) and GREIX (Kiel Institute)
  • Dubai: REIDIN and ValuStrat with hedonic adjustments (DLD – Dubai Land Department)

Methodology:

  • Quarterly or annual data are interpolated to monthly values
  • Prices in local currency are converted to USD using average monthly exchange rates
  • Hedonic methods are used to account for quality/location
  • Prices reflect a blend of apartments/condominiums and houses

Overview: Monthly average residential property prices for European cities were derived from a combination of official government indices, real estate market reports, and economic databases. Prices represent a blend of apartments/condos and houses (where data allows), focusing on urban residential averages. Data for 2025–2026 includes forecasts extrapolated from recent trends (e.g., Q3–Q4 2025).

  • Data Aggregation: Quarterly or annual data from sources was interpolated to monthly values using linear trends
  • Currency Conversion: Local currency prices were converted to USD using average monthly exchange rates (from sources like Reuters or FRED)
  • Adjustments: Where sqm prices were given, average property sizes were applied (e.g., 60–80 m² for apartments) based on city-specific reports. Forecasts account for inflation and market trends
  • Source Selection: Priority was given to official sources (government statistics) and reputable analysts; data was cross-verified for consistency. Hedonic methods or indices were used to account for quality/location
  • Limitations: Averages vary by segment (new vs. existing); luxury outliers are not included. Forecasts assume stable trends without major shocks

APAC (Asia-Pacific Markets)​

For Asia-Pacific markets, combinations of official government indices, real estate market reports, and economic databases are used.

Major Cities and Sources:

Tokyo, Japan​

  • Japan Real Estate Institute (JREI)
  • Ministry of Land, Infrastructure, Transport and Tourism (MLIT)
  • Hedonic quality adjustments

Methodology: Based on JREI surveys and MLIT indices, which use transaction data adjusted for quality (hedonic method). Prices in JPY/sqm converted to full property (avg 70 sqm condo) and USD. 2025 projections from YoY growth (e.g., 8–12% in Tokyo metro). Interpolation from quarterly BIS data.

Singapore​

  • Urban Redevelopment Authority (URA) Private Residential Property Price Index
  • Transaction data with hedonic adjustments
  • Includes HDB flats and condos

Methodology: URA Private Residential Property Price Index, based on transaction caveats (hedonic-adjusted for attributes). Includes HDB flats and condos. SGD to USD conversion; monthly from quarterly data. 2025 forecast uses 0.9% Q3 growth, projecting 4–5% annual.

Hong Kong​

  • Rating and Valuation Department (RVD)
  • Classification by size (A–E)
  • Transaction data (repeat-sales/hedonic)

Methodology: RVD classifies by size (A–E), using transaction data (repeat-sales/hedonic). HKD/sqm to full property (avg 50 sqm), USD conversion. 2025 uses 1.13% YoY rise, with Q2 index interpolation.

Shanghai, China​

  • National Bureau of Statistics (NBS)
  • CREIS index
  • 70-city survey with transaction data

Methodology: NBS and CREIS use 70-city survey (transaction-based, hedonic). RMB/sqm to full (80 sqm avg), USD. 2025 forecast: -2.4% YoY drop, interpolated from monthly.

Sydney, Australia​

  • ABS (Australian Bureau of Statistics)
  • CoreLogic hedonic indices
  • Median prices

Methodology: ABS and CoreLogic use hedonic indices from sales data. Median AUD prices to USD; monthly from quarterly. 2025: 4–5% rise projection, with $23k Q3 increase.

Seoul, South Korea​

  • Korea Real Estate Board
  • KB Kookmin Bank
  • Transaction surveys with hedonic adjustments

Methodology: Korea Real Estate Board and KB Kookmin Bank use transaction surveys (hedonic). KRW to USD; monthly from quarterly. 2025: 0.7% YoY, with 5.9% projection adjustment.

APAC Methodology Overview: The monthly average residential property prices in the CSV were derived from a combination of official government indices, real estate market reports, and economic databases. Prices represent a blend of apartments/condos and houses (where data allows), focusing on urban residential averages.

  • Data Aggregation: Quarterly or annual data from sources was interpolated to monthly values using linear trends. For incomplete periods (e.g., pre-2018 blanks in CSV), no data was filled as per available historicals
  • Currency Conversion: Local currency prices were converted to USD using average monthly exchange rates from sources like FRED or Trading Economics
  • Adjustments: Where sqm prices were given, assumed average property sizes (e.g., 60–80 sqm for apartments) based on city-specific reports. 2025 data includes projections from mid-year trends, extrapolated linearly from latest available (e.g., Q3 2025)
  • Sources Selection: Prioritized official (e.g., government stats) and reputable analysts; cross-verified for consistency. Hedonic or index-based methods adjust for quality/location
  • Limitations: Averages vary by segment (new vs. existing); no luxury outliers included. Projections assume stable trends without major shocks

How Price Changes Are Calculated​

Mantle Estate uses next methodology: a real estate price index that updates daily and tracks price changes in real-time across different markets (web sites, reports, online ads).

Unlike traditional indices like Case-Shiller (which uses only repeat sales of single-family homes, monthly, with months of lag), our system includes all types of transactions (including new construction, condos, townhouses, multi-family homes) and strives for maximum timeliness.

1. Data Sources​

Primary Sources:

  • Sales records from county registrars, official registries, historical transaction data

Additional Sources:

  • Timely sources, such as active listings (sales listings), which strongly correlate with final sale prices (correlation coefficient ~0.89). This allows accounting for fresher information, compensating for delays in official sales (from 2 weeks to 6 months)

2. Data Cleaning and Filtering​

Cleaning:

  • Duplicate removal
  • Address standardization
  • Area and other parameter verification

Outlier Filtering:

  • Only transactions in the 35–65th percentiles of price distribution are used
  • This avoids the influence of ultra-expensive or ultra-cheap properties
  • Reduces distortions from market skewness

3. Daily Price Calculation​

Methodology:

  1. Rolling median price per sqm/ft is calculated using a dynamic time window backwards
  2. Window adjusts automatically:
    • Shorter in active markets with high transaction volume
    • Longer in sparse markets (to gather sufficient data)
  3. Timely data (listings) are added to historical sales with exponential weights:
    • More weight to recent observations
    • Historical influence is preserved
  4. Final smoothed price — combination of these components + 7-day smoothing to minimize noise

4. Price Changes​

Price changes are simply the difference in daily median price per sqm/ft from day to day (or over a period).

Benefits:

  • Daily data updates
  • Listing integration allows the index to respond to market shifts much faster than monthly indices
  • No seasonal adjustment (to avoid lags and artificial distortions)

5. Revisions and Quality​

  • Index is tested daily for anomalies (sharp spikes, source issues)
  • Data is revised when necessary
  • Accuracy is verified by correlation with traditional indices (e.g., Case-Shiller for US, where applicable)

Result​

Price changes in Mantle Estate reflect real market trends based on:

  • All available transactions
  • Fresh signals from listings
  • Strong smoothing for stability
  • Daily updates

This allows seeing whether prices are rising in a specific city today, rather than waiting months.