Home Pricing Index (HPI)
More Effective Valuation Trending and Forecasting
Property valuation trends can vary significantly from neighborhood to neighborhood, yet most HPIs do not provide insight at this level. In response to these weaknesses, DataQuick developed its Neighborhood-Level HPI based on geo spatial data which lets you track trends and forecast at a more granular level. This increased precision significantly improves your ability to understand the relevant market trends impacting a neighborhood as well as property values for specific properties within a neighborhood.
Most HPIs Fall Short
Traditional HPIs fall short in many areas:
- Most are based on the repeat sales method and are unable to discern critical differences at the neighborhood level.
- They assume that a property’s quality hasn’t changed between sales.
- Distinctions are not made between single family residences and condominiums.
- There is often a lag of up to two quarters between when changes occur in the market and when they’re reflected in the HPI.
More Granular Trending and Forecasting
DataQuick’s geospatial approach lets you track trends and forecast at a more granular level by utilizing properties in similar local markets to increase the number of observations available for analysis. Properties within an area are given greater weight for trending for that specific area. Additional data points are pulled from neighborhoods with similar wealth and distressed property measures.
This approach offers several advantages:
- An increase in the density of observations allows for trends and forecasts to be reported down to the zip code and often the zip+1 level.
- Separate HPIs are delivered for single family residences and condos for the same area.
- The index is not constrained by constant quality assumptions over time.
- Because data is aggregated directly from county recorder offices, the HPI is updated monthly.