AgenticInvestor

United States NAHB Housing Market Index

United States · Monthly series · EC-US-HMI

Latest, October 2026

29.0 pts

-9.4% from September 2026

Open interactive chartUnited States NAHB Housing Market Index in the app

9050.0610.12November 2016October 2027
History through October 2026, the forecast path to October 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for October 2027: 29.0 pts, with an 80% interval of 16.4 pts to 41.6 pts.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
November 202629.0 pts21.2 pts36.8 pts
December 202629.0 pts15.9 pts42.1 pts
January 202729.0 pts19.9 pts38.1 pts
February 202729.0 pts21.7 pts36.3 pts
March 202729.0 pts21.0 pts37.0 pts
April 202729.0 pts18.2 pts39.8 pts
May 202729.0 pts14.5 pts43.5 pts
June 202729.0 pts15.9 pts42.1 pts
July 202729.0 pts18.8 pts39.2 pts
August 202729.0 pts10.1 pts47.9 pts
September 202729.0 pts16.4 pts41.6 pts
October 202729.0 pts16.4 pts41.6 pts

Model: Exponential smoothing (statistical). Forecast generated 2026-11-14.

AI confidence

Needs refresh

The data refresh is due. Confidence will be reassessed against the refreshed history.

Model: Exponential smoothing (statistical)

Accuracy vs naive
n/aNot evaluated
Direction
n/aNot evaluated
Turning points
n/aNot evaluated
How this assessment is made

AI confidence describes historical evidence for this forecast, not a probability of being correct. Each backtest fits on data available before its test window. The baseline carries the last value forward. Supported evidence requires at least six complete, non-overlapping tests, an error ratio below 0.90 (rounded to two decimals), and wins in a majority of tests. Ratios from 0.90 to below 1.10 are on par; 1.10 or above is weak evidence. Inconsistent wins produce mixed evidence. For a selected model, only the recent tests excluded from model selection determine this label. These are historical simulations using the available data, not a live trading track record; revisions and foundation-model pretraining can limit how closely they reproduce a past decision. Past performance can change.

Model comparison

Previous comparisonThe stored comparison uses earlier data or a previous model roster. An eligible nightly batch can compare both candidates, subject to call budgets and retry limits.

Models tested

Exponential smoothing scored lowest on the 6 older tests (1.00) and was chosen. The 6 recent tests played no part in the choice and give its grade (1.00). The search for a model that beats the naive forecast on both sets of tests goes on. Scores are MASE: a model's errors divided by the naive forecast's, so 1 is a tie.

4 model classes completed the tests: Statistical, Foundation model, Neural network, Machine learning. Previous model roster.

Every model tested on this series.
ModelClass and computeOlder testsRecent testsRole
Exponential smoothing (statistical)Statistical · CPU1.001.00Serving
Naive forecast (last value held)Benchmark · CPU1.001.00Benchmark
Agentic Investor TSFM (foundation model)Foundation model · CPU1.041.02Tested
State-space model, 167M (foundation model)Foundation model · CPU1.081.03Tested
Hierarchical neural network (neural network)Neural network · CPU1.152.86Tested
Gradient-boosted trees (machine learning)Machine learning · CPU1.271.31Tested

Uses ci-proto, released by Continuous Intelligence. Continuous Intelligence does not endorse or approve this product or service. (ci-proto is shown as State-space model, 167M.)

Reading

That is the lowest of the 120 readings since November 2016.

Written from the figures by a fixed template; no AI model is involved.

Recent history (24 observations)
The 24 most recent observations, newest first.
PeriodValue
October 202629.0 pts
September 202632.0 pts
August 202635.0 pts
July 202634.0 pts
June 202636.0 pts
May 202637.0 pts
April 202634.0 pts
March 202638.0 pts
February 202637.0 pts
January 202637.0 pts
December 202539.0 pts
November 202538.0 pts
October 202537.0 pts
September 202532.0 pts
August 202532.0 pts
July 202533.0 pts
June 202532.0 pts
May 202534.0 pts
April 202540.0 pts
March 202539.0 pts
February 202542.0 pts
January 202547.0 pts
December 202446.0 pts
November 202446.0 pts

Source

Data: public market data feeds.

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