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United States House Price Index Month-over-Month (MoM)
Price
The current value of the House Price Index Month-over-Month (MoM) in United States is 0.1 %. The House Price Index Month-over-Month (MoM) in United States decreased to 0.1 % on 3/1/2024, after it was 1.2 % on 2/1/2024. From 2/1/1991 to 5/1/2024, the average GDP in United States was 0.36 %. The all-time high was reached on 8/1/2020 with 1.8 %, while the lowest value was recorded on 11/1/2008 with -1.8 %.
House Price Index Month-over-Month (MoM) ·
3 years
5 years
10 years
25 Years
Max
| Home Price Index MoM | |
|---|---|
| 2/1/1991 | 0.4 % |
| 6/1/1991 | 0.1 % |
| 9/1/1991 | 0.2 % |
| 10/1/1991 | 0.3 % |
| 11/1/1991 | 0.5 % |
| 12/1/1991 | 0.5 % |
| 1/1/1992 | 0.4 % |
| 2/1/1992 | 0.7 % |
| 7/1/1992 | 0.3 % |
| 8/1/1992 | 0.5 % |
| 9/1/1992 | 0.4 % |
| 10/1/1992 | 0.3 % |
| 11/1/1992 | 0.2 % |
| 1/1/1993 | 0.1 % |
| 3/1/1993 | 0.3 % |
| 4/1/1993 | 0.6 % |
| 5/1/1993 | 0.2 % |
| 6/1/1993 | 0.4 % |
| 8/1/1993 | 0.4 % |
| 9/1/1993 | 0.4 % |
| 10/1/1993 | 0.2 % |
| 11/1/1993 | 0.3 % |
| 12/1/1993 | 0.5 % |
| 1/1/1994 | 0.2 % |
| 2/1/1994 | 0.2 % |
| 3/1/1994 | 0.3 % |
| 4/1/1994 | 0.3 % |
| 5/1/1994 | 0.3 % |
| 6/1/1994 | 0.2 % |
| 7/1/1994 | 0.1 % |
| 8/1/1994 | 0.3 % |
| 9/1/1994 | 0.1 % |
| 10/1/1994 | 0.3 % |
| 11/1/1994 | 0.2 % |
| 1/1/1995 | 0.3 % |
| 2/1/1995 | 0.5 % |
| 4/1/1995 | 0.2 % |
| 5/1/1995 | 0.1 % |
| 6/1/1995 | 0.3 % |
| 7/1/1995 | 0.5 % |
| 8/1/1995 | 0.3 % |
| 9/1/1995 | 0.2 % |
| 11/1/1995 | 0.2 % |
| 12/1/1995 | 0.4 % |
| 1/1/1996 | 0.4 % |
| 2/1/1996 | 0.1 % |
| 3/1/1996 | 0.4 % |
| 4/1/1996 | 0.2 % |
| 5/1/1996 | 0.2 % |
| 6/1/1996 | 0.1 % |
| 7/1/1996 | 0.3 % |
| 9/1/1996 | 0.2 % |
| 10/1/1996 | 0.1 % |
| 11/1/1996 | 0.3 % |
| 12/1/1996 | 0.3 % |
| 1/1/1997 | 0.1 % |
| 2/1/1997 | 0.2 % |
| 3/1/1997 | 0.4 % |
| 4/1/1997 | 0.2 % |
| 5/1/1997 | 0.4 % |
| 7/1/1997 | 0.3 % |
| 8/1/1997 | 0.4 % |
| 9/1/1997 | 0.1 % |
| 10/1/1997 | 0.5 % |
| 11/1/1997 | 0.3 % |
| 12/1/1997 | 0.3 % |
| 1/1/1998 | 0.4 % |
| 2/1/1998 | 0.7 % |
| 3/1/1998 | 0.3 % |
| 4/1/1998 | 0.4 % |
| 5/1/1998 | 0.4 % |
| 6/1/1998 | 0.6 % |
| 7/1/1998 | 0.3 % |
| 8/1/1998 | 0.4 % |
| 9/1/1998 | 0.6 % |
| 10/1/1998 | 0.4 % |
| 11/1/1998 | 0.7 % |
| 12/1/1998 | 0.5 % |
| 1/1/1999 | 0.6 % |
| 2/1/1999 | 0.4 % |
| 3/1/1999 | 0.4 % |
| 4/1/1999 | 0.5 % |
| 5/1/1999 | 0.6 % |
| 6/1/1999 | 0.5 % |
| 7/1/1999 | 0.6 % |
| 8/1/1999 | 0.6 % |
| 9/1/1999 | 0.3 % |
| 10/1/1999 | 0.6 % |
| 11/1/1999 | 0.4 % |
| 12/1/1999 | 0.5 % |
| 1/1/2000 | 1.2 % |
| 3/1/2000 | 0.8 % |
| 4/1/2000 | 0.7 % |
| 5/1/2000 | 0.4 % |
| 6/1/2000 | 0.7 % |
| 7/1/2000 | 0.5 % |
| 8/1/2000 | 0.4 % |
| 9/1/2000 | 0.6 % |
| 10/1/2000 | 0.6 % |
| 11/1/2000 | 0.6 % |
| 12/1/2000 | 0.6 % |
| 1/1/2001 | 0.6 % |
| 2/1/2001 | 0.7 % |
| 3/1/2001 | 0.5 % |
| 4/1/2001 | 0.6 % |
| 5/1/2001 | 0.4 % |
| 6/1/2001 | 0.5 % |
| 7/1/2001 | 0.6 % |
| 8/1/2001 | 0.5 % |
| 9/1/2001 | 0.5 % |
| 10/1/2001 | 0.6 % |
| 11/1/2001 | 0.3 % |
| 12/1/2001 | 0.6 % |
| 1/1/2002 | 0.6 % |
| 2/1/2002 | 0.6 % |
| 3/1/2002 | 0.6 % |
| 4/1/2002 | 0.5 % |
| 5/1/2002 | 0.7 % |
| 6/1/2002 | 0.6 % |
| 7/1/2002 | 0.6 % |
| 8/1/2002 | 0.6 % |
| 9/1/2002 | 0.6 % |
| 10/1/2002 | 0.7 % |
| 11/1/2002 | 0.6 % |
| 12/1/2002 | 0.7 % |
| 1/1/2003 | 0.6 % |
| 2/1/2003 | 0.6 % |
| 3/1/2003 | 0.3 % |
| 4/1/2003 | 0.6 % |
| 5/1/2003 | 0.5 % |
| 6/1/2003 | 0.5 % |
| 7/1/2003 | 0.7 % |
| 8/1/2003 | 0.7 % |
| 9/1/2003 | 0.8 % |
| 10/1/2003 | 0.6 % |
| 11/1/2003 | 0.8 % |
| 12/1/2003 | 0.8 % |
| 1/1/2004 | 0.6 % |
| 2/1/2004 | 0.8 % |
| 3/1/2004 | 0.7 % |
| 4/1/2004 | 0.8 % |
| 5/1/2004 | 0.9 % |
| 6/1/2004 | 1 % |
| 7/1/2004 | 0.8 % |
| 8/1/2004 | 0.7 % |
| 9/1/2004 | 0.8 % |
| 10/1/2004 | 0.7 % |
| 11/1/2004 | 0.9 % |
| 12/1/2004 | 0.9 % |
| 1/1/2005 | 0.7 % |
| 2/1/2005 | 0.7 % |
| 3/1/2005 | 1 % |
| 4/1/2005 | 0.9 % |
| 5/1/2005 | 0.8 % |
| 6/1/2005 | 0.9 % |
| 7/1/2005 | 1 % |
| 8/1/2005 | 0.7 % |
| 9/1/2005 | 0.9 % |
| 10/1/2005 | 0.6 % |
| 11/1/2005 | 0.6 % |
| 12/1/2005 | 0.6 % |
| 1/1/2006 | 0.6 % |
| 2/1/2006 | 0.2 % |
| 3/1/2006 | 0.4 % |
| 4/1/2006 | 0.2 % |
| 5/1/2006 | 0.3 % |
| 8/1/2006 | 0.3 % |
| 10/1/2006 | 0.1 % |
| 11/1/2006 | 0.3 % |
| 1/1/2007 | 0.3 % |
| 3/1/2007 | 0.4 % |
| 1/1/2009 | 0.8 % |
| 2/1/2009 | 0.1 % |
| 10/1/2009 | 0.2 % |
| 11/1/2009 | 0.3 % |
| 4/1/2010 | 0.2 % |
| 10/1/2010 | 0.2 % |
| 4/1/2011 | 0.2 % |
| 6/1/2011 | 0.3 % |
| 7/1/2011 | 0.2 % |
| 9/1/2011 | 0.6 % |
| 11/1/2011 | 0.4 % |
| 12/1/2011 | 0.3 % |
| 2/1/2012 | 0.3 % |
| 3/1/2012 | 0.9 % |
| 4/1/2012 | 0.5 % |
| 5/1/2012 | 0.6 % |
| 6/1/2012 | 0.4 % |
| 7/1/2012 | 0.2 % |
| 8/1/2012 | 0.7 % |
| 9/1/2012 | 0.4 % |
| 10/1/2012 | 0.5 % |
| 11/1/2012 | 0.5 % |
| 12/1/2012 | 0.5 % |
| 1/1/2013 | 0.7 % |
| 2/1/2013 | 0.7 % |
| 3/1/2013 | 1 % |
| 4/1/2013 | 0.5 % |
| 5/1/2013 | 0.8 % |
| 6/1/2013 | 0.6 % |
| 7/1/2013 | 0.6 % |
| 8/1/2013 | 0.3 % |
| 9/1/2013 | 0.5 % |
| 10/1/2013 | 0.3 % |
| 11/1/2013 | 0.1 % |
| 12/1/2013 | 0.6 % |
| 1/1/2014 | 0.4 % |
| 2/1/2014 | 0.4 % |
| 3/1/2014 | 0.3 % |
| 4/1/2014 | 0.3 % |
| 5/1/2014 | 0.2 % |
| 6/1/2014 | 0.5 % |
| 7/1/2014 | 0.4 % |
| 8/1/2014 | 0.4 % |
| 9/1/2014 | 0.1 % |
| 10/1/2014 | 0.6 % |
| 11/1/2014 | 0.5 % |
| 12/1/2014 | 0.6 % |
| 1/1/2015 | 0.1 % |
| 2/1/2015 | 0.8 % |
| 3/1/2015 | 0.3 % |
| 4/1/2015 | 0.4 % |
| 5/1/2015 | 0.6 % |
| 6/1/2015 | 0.4 % |
| 7/1/2015 | 0.5 % |
| 8/1/2015 | 0.2 % |
| 9/1/2015 | 0.5 % |
| 10/1/2015 | 0.6 % |
| 11/1/2015 | 0.5 % |
| 12/1/2015 | 0.5 % |
| 1/1/2016 | 0.4 % |
| 2/1/2016 | 0.1 % |
| 3/1/2016 | 0.8 % |
| 4/1/2016 | 0.5 % |
| 5/1/2016 | 0.4 % |
| 6/1/2016 | 0.6 % |
| 7/1/2016 | 0.5 % |
| 8/1/2016 | 0.5 % |
| 9/1/2016 | 0.6 % |
| 10/1/2016 | 0.5 % |
| 11/1/2016 | 0.4 % |
| 12/1/2016 | 0.7 % |
| 1/1/2017 | 0.1 % |
| 2/1/2017 | 0.5 % |
| 3/1/2017 | 0.6 % |
| 4/1/2017 | 0.8 % |
| 5/1/2017 | 0.5 % |
| 6/1/2017 | 0.4 % |
| 7/1/2017 | 0.5 % |
| 8/1/2017 | 0.7 % |
| 9/1/2017 | 0.4 % |
| 10/1/2017 | 0.4 % |
| 11/1/2017 | 0.7 % |
| 12/1/2017 | 0.4 % |
| 1/1/2018 | 0.8 % |
| 2/1/2018 | 0.7 % |
| 3/1/2018 | 0.4 % |
| 4/1/2018 | 0.3 % |
| 5/1/2018 | 0.5 % |
| 6/1/2018 | 0.4 % |
| 7/1/2018 | 0.4 % |
| 8/1/2018 | 0.5 % |
| 9/1/2018 | 0.2 % |
| 10/1/2018 | 0.4 % |
| 11/1/2018 | 0.6 % |
| 12/1/2018 | 0.3 % |
| 1/1/2019 | 0.6 % |
| 2/1/2019 | 0.2 % |
| 3/1/2019 | 0.3 % |
| 4/1/2019 | 0.5 % |
| 5/1/2019 | 0.4 % |
| 6/1/2019 | 0.3 % |
| 7/1/2019 | 0.4 % |
| 8/1/2019 | 0.4 % |
| 9/1/2019 | 0.6 % |
| 10/1/2019 | 0.5 % |
| 11/1/2019 | 0.6 % |
| 12/1/2019 | 0.8 % |
| 1/1/2020 | 0.6 % |
| 2/1/2020 | 0.7 % |
| 3/1/2020 | 0.2 % |
| 4/1/2020 | 0.2 % |
| 6/1/2020 | 1.1 % |
| 7/1/2020 | 1.4 % |
| 8/1/2020 | 1.8 % |
| 9/1/2020 | 1.6 % |
| 10/1/2020 | 1.5 % |
| 11/1/2020 | 1.2 % |
| 12/1/2020 | 1.3 % |
| 1/1/2021 | 1.1 % |
| 2/1/2021 | 0.9 % |
| 3/1/2021 | 1.4 % |
| 4/1/2021 | 1.6 % |
| 5/1/2021 | 1.6 % |
| 6/1/2021 | 1.8 % |
| 7/1/2021 | 1.6 % |
| 8/1/2021 | 1.2 % |
| 9/1/2021 | 1.1 % |
| 10/1/2021 | 1.3 % |
| 11/1/2021 | 1.4 % |
| 12/1/2021 | 1.5 % |
| 1/1/2022 | 1.4 % |
| 2/1/2022 | 1.6 % |
| 3/1/2022 | 1.2 % |
| 4/1/2022 | 1.4 % |
| 5/1/2022 | 1 % |
| 6/1/2022 | 0.2 % |
| 9/1/2022 | 0.3 % |
| 10/1/2022 | 0.1 % |
| 12/1/2022 | 0.1 % |
| 1/1/2023 | 0.1 % |
| 2/1/2023 | 0.8 % |
| 3/1/2023 | 0.5 % |
| 4/1/2023 | 0.8 % |
| 5/1/2023 | 0.8 % |
| 6/1/2023 | 0.5 % |
| 7/1/2023 | 0.8 % |
| 8/1/2023 | 0.7 % |
| 9/1/2023 | 0.7 % |
| 10/1/2023 | 0.3 % |
| 11/1/2023 | 0.4 % |
| 12/1/2023 | 0.1 % |
| 2/1/2024 | 1.2 % |
| 3/1/2024 | 0.1 % |
House Price Index Month-over-Month (MoM) History
| Date | Value |
|---|---|
| 3/1/2024 | 0.1 % |
| 2/1/2024 | 1.2 % |
| 12/1/2023 | 0.1 % |
| 11/1/2023 | 0.4 % |
| 10/1/2023 | 0.3 % |
| 9/1/2023 | 0.7 % |
| 8/1/2023 | 0.7 % |
| 7/1/2023 | 0.8 % |
| 6/1/2023 | 0.5 % |
| 5/1/2023 | 0.8 % |
Similar Macro Indicators to House Price Index Month-over-Month (MoM)
| Name | Current | Previous | Frequency |
|---|---|---|---|
🇺🇸 15-Year Mortgage Rate | 5.99 % | 6 % | frequency_weekly |
🇺🇸 30-Year Mortgage Rate | 6.86 % | 6.87 % | frequency_weekly |
🇺🇸 Average House Prices | 501,000 USD | 486,500 USD | Monthly |
🇺🇸 Average Mortgage Size | 405,490 USD | 405,400 USD | frequency_weekly |
🇺🇸 Building Permits | 1.425 M | 1.47 M | Monthly |
🇺🇸 Building Permits MoM | -3.1 % | 4.6 % | Monthly |
🇺🇸 Case-Shiller Home Price Index | 333.21 points | 329.95 points | Monthly |
🇺🇸 Case-Shiller Home Price Index MoM | 1.4 % | 1.6 % | Monthly |
🇺🇸 Case-Shiller Home Price Index YoY | 7.2 % | 7.5 % | Monthly |
🇺🇸 Construction Spending | -0.1 % | 0.3 % | Monthly |
🇺🇸 Existing Home Sales | 3.84 M | 3.88 M | Monthly |
🇺🇸 Existing Home Sales MoM | -1 % | -2 % | Monthly |
🇺🇸 Homeownership Rate | 65.6 % | 65.6 % | Quarter |
🇺🇸 Housing Index | 424.3 points | 423.3 points | Monthly |
🇺🇸 Housing Price Index YoY | 6.3 % | 6.7 % | Monthly |
🇺🇸 Housing starts | 1.354 M units | 1.361 M units | Monthly |
🇺🇸 Housing Starts MoM | -0.5 % | 7.8 % | Monthly |
🇺🇸 MBA Mortgage Market Index | 212 points | 210.4 points | frequency_weekly |
🇺🇸 MBA Mortgage Refinancing Index | 552.4 points | 552.7 points | frequency_weekly |
🇺🇸 MBA Purchase Index | 133.3 points | 130.8 points | frequency_weekly |
🇺🇸 Mortgage applications | 0.8 % | 0.9 % | frequency_weekly |
🇺🇸 Mortgage Interest Rate | 6.93 % | 6.94 % | frequency_weekly |
🇺🇸 Mortgage Originations | 448.31 B USD | 374.11 B USD | Quarter |
🇺🇸 Multi-family Housing Starts | 278,000 units | 310,000 units | Monthly |
🇺🇸 NAHB Housing Market Index | 42 points | 43 points | Monthly |
🇺🇸 National House Price Index | 322.25 points | 321.205 points | Monthly |
🇺🇸 New Home Sales | 619,000 units | 698,000 units | Monthly |
🇺🇸 New Home Sales MoM | -11.3 % | 2 % | Monthly |
🇺🇸 Pending Home Sales | -6.6 % | -7.4 % | Monthly |
🇺🇸 Pending Home Sales MoM | -2.1 % | -7.7 % | Monthly |
🇺🇸 Price-Rent Ratio | 134.247 | 134.659 | Quarter |
🇺🇸 Residential property prices | 4.67 % | 5.27 % | Quarter |
🇺🇸 Single-family home prices | 404,500 USD | 414,200 USD | Monthly |
🇺🇸 Single-Family Home Starts | 982,000 units | 1.036 M units | Monthly |
🇺🇸 Total Housing stock | 1.39 M | 1.37 M | Monthly |
The FHFA (Federal Housing Finance Agency) House Price Index tracks the month-over-month changes in the average prices of single-family homes with mortgages guaranteed by Fannie Mae and Freddie Mac.
Macro pages for other countries in America
- 🇦🇷Argentina
- 🇦🇼Aruba
- 🇧🇸Bahamas
- 🇧🇧Barbados
- 🇧🇿Belize
- 🇧🇲Bermuda
- 🇧🇴Bolivia
- 🇧🇷Brazil
- 🇨🇦Canada
- 🇰🇾Cayman Islands
- 🇨🇱Chile
- 🇨🇴Colombia
- 🇨🇷Costa Rica
- 🇨🇺Cuba
- 🇩🇴Dominican Republic
- 🇪🇨Ecuador
- 🇸🇻El Salvador
- 🇬🇹Guatemala
- 🇬🇾Guyana
- 🇭🇹Haiti
- 🇭🇳Honduras
- 🇯🇲Jamaica
- 🇲🇽Mexico
- 🇳🇮Nicaragua
- 🇵🇦Panama
- 🇵🇾Paraguay
- 🇵🇪Peru
- 🇵🇷Puerto Rico
- 🇸🇷Suriname
- 🇹🇹Trinidad and Tobago
- 🇺🇾Uruguay
- 🇻🇪Venezuela
- 🇦🇬Antigua and Barbuda
- 🇩🇲Dominica
- 🇬🇩Grenada
What is House Price Index Month-over-Month (MoM)?
The House Price Index Month-over-Month (HPI MoM) is a critical macroeconomic indicator that offers insights into the housing market's performance over a given month. At Eulerpool, we take pride in delivering accurate, timely, and comprehensive macroeconomic data, and the HPI MoM is an integral part of our offerings. The HPI MoM is a statistical measure that tracks the changes in the prices of residential properties. This index is crucial for economists, policymakers, real estate analysts, and investors as it provides a snapshot of the housing market's health, signaling trends and potential changes in economic conditions. Understanding the HPI MoM can help in forecasting future market movements, making informed decisions, and formulating strategies for various economic activities. The House Price Index is typically calculated by collecting data on residential property transactions. These transactions comprise a varied array of residential properties, including single-family homes, townhouses, and condominiums. The data collected is then used to create a weighted average that reflects changes in house prices. The month-over-month comparison provides a short-term view of the market by comparing the prices from one month to the next. One of the primary benefits of the HPI MoM is its ability to capture the dynamic nature of the housing market. Housing markets are often influenced by many factors, including interest rates, employment levels, and economic cycles. By examining month-over-month changes, stakeholders can quickly identify short-term trends and potential turning points in the market. For instance, if the HPI MoM shows a consistent increase over several months, it may indicate a robust housing market with increasing demand and rising prices. Conversely, a decline in the HPI MoM could suggest a cooling market, potentially due to higher interest rates, reduced buyer confidence, or an oversupply of properties. These insights can be invaluable for various stakeholders, each of whom relies on the HPI MoM for different reasons. Policymakers use the HPI MoM to gauge the effectiveness of monetary and fiscal policies. For example, central banks may use this data to adjust interest rates or implement other measures to control inflation and stabilize the economy. By analyzing the HPI MoM, policymakers can determine whether their initiatives are having the desired effect on the housing market and, by extension, the broader economy. Real estate professionals, including agents, brokers, and developers, also rely heavily on the HPI MoM. This data helps them understand current market conditions, set appropriate pricing strategies, and advise their clients more effectively. For instance, if the HPI MoM indicates rising prices, real estate agents might advise sellers to list their properties promptly to capitalize on the favorable market. Conversely, developers might adjust their project timelines to align with periods of expected growth. Investors, particularly those involved in real estate, consider the HPI MoM to be a critical tool in their decision-making process. This data can help investors identify opportunities for capital appreciation or gauge the risk of potential investments. For example, an investor might look for markets where the HPI MoM shows a steady increase, indicating strong demand and the potential for property values to rise further. Conversely, investors might avoid markets where the HPI MoM is declining, signaling potential risks. Economists and researchers utilize the HPI MoM to study housing market trends and economic cycles. By analyzing this data, they can identify patterns and correlations with other economic indicators, such as employment levels, consumer confidence, and GDP growth. These insights can contribute to broader macroeconomic forecasts and models, enhancing our understanding of the complex interactions between different sectors of the economy. At Eulerpool, we strive to provide not only the raw data but also the context and analysis needed to interpret the HPI MoM. Our platform offers a user-friendly interface, detailed visualizations, and expert commentary to help our users make sense of the data. We understand that the housing market is a critical component of the economy, and our comprehensive coverage of the HPI MoM reflects our commitment to helping our users stay informed and make data-driven decisions. To ensure the accuracy and reliability of our HPI MoM data, we employ rigorous data collection and validation processes. We source our data from reputable providers, including government agencies, industry associations, and private sector organizations. Our team of analysts meticulously reviews the data to ensure it accurately reflects market conditions and trends. We also continuously monitor changes in the housing market, updating our HPI MoM data as new information becomes available. Understanding the HPI MoM also requires considering regional variations. Housing markets can differ significantly from one region to another, influenced by factors such as local economic conditions, population growth, and regulatory environments. At Eulerpool, we provide detailed regional breakdowns of the HPI MoM, allowing users to drill down into specific areas and gain a deeper understanding of local market dynamics. This regional data can be particularly valuable for stakeholders with interests in specific geographic areas, such as local policymakers, real estate professionals, and investors. In addition to regional analysis, we also offer historical data on the HPI MoM, enabling users to examine long-term trends and patterns. By analyzing historical data, users can identify cycles, compare current conditions with past periods, and gain a broader perspective on the housing market's evolution. This historical context can be invaluable for making informed decisions and developing robust strategies. Ultimately, the House Price Index Month-over-Month is more than just a statistic; it is a vital tool for understanding the housing market and its implications for the broader economy. At Eulerpool, we are committed to providing our users with the highest quality HPI MoM data, along with the insights and analysis needed to make sense of this complex and dynamic market. Whether you are a policymaker, real estate professional, investor, or researcher, our comprehensive coverage of the HPI MoM can help you stay informed and achieve your goals. In conclusion, the HPI MoM is an essential macroeconomic indicator that provides valuable insights into the housing market's monthly performance. By tracking changes in residential property prices, this index helps stakeholders identify trends, make informed decisions, and develop effective strategies. At Eulerpool, we are dedicated to delivering accurate, reliable, and comprehensive HPI MoM data, empowering our users with the knowledge they need to navigate the housing market and contribute to a better understanding of the broader economy.