S&P/Case-Shiller United States Home Price Index (HPI) Composite-20 n.s.a. m/m

Country:
United States
USD, US dollar
Sector:
Housing
Low 0.0% 0.0%
0.2%
Last release Importance Actual Forecast
Previous
0.2%
0.0%
Next release Actual Forecast
Previous
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S&P/Case-Shiller Home Price Index Composite-20 n.s.a. m/m reflects a change in repeat-sales house prices in 20 major metro areas in the reported month compared to the previous one. Seasonal fluctuations are not considered in the calculations.

The calculation involves the method of weighted repeated sales offered by Karl Case, Robert Shiller and Allan Weiss. Data for calculation are collected from local recording offices. Each metropolitan area is given a weigh used for the aggregate index calculation. The available data usually include the date, sale price and type of property. An object needs to have an earlier arms-length sales transaction in order to be included in the composite index calculation.

The following types of homes are excluded from calculation:

  • New homes, because it is not possible to measure a change in its price before a repeated sale
  • Condominiums and cooperatives, multi-unit houses and other objects, which cannot be determined as "single-family dwelling"
  • Non arm-length transactions (e.g. transfers between family members)
  • Transactions where the property type designation is changed (e.g., properties originally recorded as single-family homes are subsequently recorded as condominiums)
  • Homes that have been repeatedly sold two or more times during six months

Different factors are usually formed in the market for different types of property, which determine demand, supply and prices. Therefore, for the correct evaluation of the market situation, the index includes segmentation by type of residential dwellings. The detailed version of this composite indicator includes three separate indices: prices for dwellings with low, medium and high cost. Changes in prices for expensive homes has a greater impact on the composite index result. This is one of the differences between the index and FHFA house price index, in which no segmentation is applied and an average price for all types of houses is calculated.

Also, S&P/CS calculation uses a smaller sample and does not take into account data from 13 states. The indicator is used for measuring activity in the real estate market in the largest US metro areas. Index growth can have a positive effect on dollar quotes.

Last values:

actual data

forecast

The chart of the entire available history of the "S&P/Case-Shiller United States Home Price Index (HPI) Composite-20 n.s.a. m/m" macroeconomic indicator. The dashed line shows the forecast values ​​of the economic indicator for the specified dates.

A significant deviation of a real value from a forecast one may cause a short-term strengthening or weakening of a national currency in the Forex market. The threshold values ​​of the indicators signaling the approach of the critical state of the national (local) economy occupy a special place.

Date (GMT)
Reference
Actual
Forecast
Previous
Aug 2019
0.0%
0.0%
0.2%
Jul 2019
0.1%
-0.1%
0.4%
Jun 2019
0.3%
0.3%
0.6%
May 2019
0.6%
0.5%
0.8%
Apr 2019
0.8%
0.6%
0.7%
Mar 2019
0.7%
0.5%
0.2%
Feb 2019
0.2%
0.5%
-0.2%
Jan 2019
-0.2%
0.4%
-0.2%
Dec 2018
-0.2%
0.3%
-0.1%
Nov 2018
-0.1%
0.2%
0.0%
Oct 2018
0.0%
0.2%
0.0%
Sep 2018
0.0%
0.2%
0.0%
Aug 2018
0.0%
0.3%
0.3%
Jul 2018
0.3%
0.3%
0.6%
Jun 2018
0.5%
0.8%
0.8%
May 2018
0.7%
0.5%
0.9%
Apr 2018
0.8%
0.9%
1.0%
Mar 2018
1.0%
0.8%
0.7%
Feb 2018
0.7%
0.6%
0.3%
Jan 2018
0.3%
0.5%
0.2%
Dec 2017
0.2%
0.3%
0.2%
Nov 2017
0.2%
0.3%
0.2%
Oct 2017
0.2%
0.2%
0.4%
Sep 2017
0.4%
0.3%
0.4%
Aug 2017
0.4%
0.4%
0.7%
Jul 2017
0.7%
0.6%
0.7%
Jun 2017
0.7%
0.7%
0.9%
May 2017
0.8%
1.0%
Apr 2017
0.9%
1.0%
Mar 2017
1.0%
0.4%
Feb 2017
0.4%
0.2%
Jan 2017
0.2%
0.3%
Dec 2016
0.3%
0.2%
Nov 2016
0.2%
0.1%
Oct 2016
0.1%
0.1%
Sep 2016
0.1%
0.4%
Aug 2016
0.4%
0.6%
Jul 2016
0.6%
0.8%
Jun 2016
0.8%
0.9%
May 2016
0.9%
1.1%
Apr 2016
1.1%
1.0%
Mar 2016
0.9%
0.2%
Feb 2016
0.2%
0.0%
Jan 2016
0.0%
0.0%
Dec 2015
0.0%
0.1%
Nov 2015
0.1%
0.1%
Oct 2015
0.1%
0.2%
Sep 2015
0.2%
0.3%
Aug 2015
0.4%
0.6%
Jul 2015
0.6%
0.9%

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