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The Weiss Analytics (WA) forecast integrates the unique Weiss house level indexes with local, regional, and national real estate indicators using state of the art machine learning algorithms. This method allows WA to create highly predictive house level price change forecasts.
WA regularly performs large scale out-of-sample tests on its forecasts. The most recent test, completed in March 2019, included approximately 500,000 properties covering the period from 2005 through 2018 in 13 metropolitan areas.
The Weiss one-year forecast predicts how much a property’s value will rise or fall over the following year. Its accuracy can be measured by comparing it to the change in the Weiss index computed a later year.
The median signed error in the most recent test was 0.1%, indicating virtually no bias in the forecasts.
Another way to measure forecast accuracy is how well it predicts the direction of property value changes. Since home prices have inertia, it is relatively easy to predict price changes when appreciation or depreciation continues year-over-year. However, a forecast is more important to mortgage investors in times of high market volatility. For example, it is more important to know that home values are beginning to decrease in a certain neighborhood, than whether the magnitude of an ongoing decline is 5% or 9%.
WA defines three direction ranges of price trends, up, when prices rise more than 2% in a year, down, when home prices fall more than 2% in a year and flat, when the change is between -2% and +2%.
WA compares the forecast direction, up, down or flat, to the following year’s actual direction. The Weiss forecast is highly accurate in predicting the correct direction.
When property values decreased by at least 2% in the following year, the prior years’ forecast predicted a decline of at least 2% 76% of the time and a flat market 20% of the time, leaving an erroneous up prediction only 4% of the time.
This graph shows when property values decline, the Weiss forecast produced in the prior year was either down or flat 96% of the time, with a down prediction 76% of the time.
It is particularly notable that in 2006 when prices were rising but the market faced a sudden down turn in the next year, the WA forecasted predicted down over 70% of the time and up only 4% of the time. This is extremely hard to do given the normal inertia in home prices and is a great demonstration of WA forecasts’ ability to detect market weakness in advance of actual price downturns.
This predictive accuracy for declining values is mirrored when home values increased, in which case the Weiss forecast was in the down range only 1% of the time.
This graph shows that when property values increase, the prior year’s WA forecast was either up or flat 99% of the time, with a up prediction 85% of the time.
As in the case of the downturn, the first year of the upturn in 2012, the associated WA forecasted predicted down in very few cases: Akron OH, Atlanta GA, Boston MA, Cedar Rapids IA, Denver CO, Miami FL, Oklahoma City OK, Omaha NE, Philadelphia PA, Pittsburgh PA, Portland OR, Rochester NY, and San Francisco CA