AgenticInvestor

United States Used Car Prices YoY

United States · Monthly series · EC-US-UCPYY

Latest, October 2026

1.9%

+2.40pp from September 2026

Open interactive chartUnited States Used Car Prices YoY in the app

54.319.7-14.9November 2016October 2027
History through October 2026, the forecast path to October 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for October 2027: 1.9%, with an 80% interval of -4.0% to 8.6%.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
November 20262.6%-0.4%6.0%
December 20262.7%-1.3%7.0%
January 20272.4%-3.9%9.3%
February 20271.9%-4.1%8.8%
March 20271.6%-0.9%4.4%
April 20271.4%-3.6%7.0%
May 20271.5%-5.8%9.4%
June 20271.6%-6.8%10.9%
July 20271.9%-2.4%6.6%
August 20272.1%-3.3%8.4%
September 20272.1%-4.7%10.0%
October 20271.9%-4.0%8.6%

Model: State-space model, 167M (foundation model). Forecast generated 2026-11-15.

AI confidence

Needs refresh

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

Model: State-space model, 167M (foundation model)

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

State-space model, 167M scored lowest on the 6 older tests (0.76) and was chosen. The 6 recent tests played no part in the choice and give its grade (0.85). That grade beats the naive forecast. Scores are MASE: a model's errors divided by the naive forecast's, so 1 is a tie.

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

Every model tested on this series.
ModelClass and computeOlder testsRecent testsRole
State-space model, 167M (foundation model)Foundation model · CPU0.760.85Serving
Agentic Investor TSFM (foundation model)Foundation model · CPU0.780.77Tested
Naive forecast (last value held)Benchmark · CPU1.001.00Benchmark
Hierarchical neural network (neural network)Neural network · CPU1.021.48Tested
Gradient-boosted trees (machine learning)Machine learning · CPU1.231.15Tested
Exponential smoothing (statistical)Statistical · CPU1.291.17Tested

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

It is above 43% of the 119 earlier 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 20261.9%
September 2026-0.5%
August 20260.4%
July 20261.3%
June 20262.1%
May 20263.6%
April 20261.8%
March 20266.2%
February 20264.0%
January 20262.4%
December 20250.4%
November 20250.0%
October 20250.0%
September 20252.0%
August 20251.7%
July 20252.9%
June 20256.3%
May 20254.0%
April 20254.9%
March 2025-0.2%
February 20250.1%
January 20250.8%
December 20240.4%
November 20240.2%

Source

Data: public market data feeds.

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