AgenticInvestor

Indonesia Food Inflation YoY

Indonesia · Monthly series · EC-ID-FI

Latest, October 2026

4.8%

+0.45pp from September 2026

Open interactive chartIndonesia Food Inflation YoY in the app

9.7184.614-0.49November 2016October 2027
History through October 2026, the forecast path to October 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for October 2027: 4.8%, with an 80% interval of 2.4% to 8.0%.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
November 20265.5%3.6%7.5%
December 20265.6%3.9%7.5%
January 20275.7%3.4%8.4%
February 20275.5%3.3%8.2%
March 20275.5%3.2%8.4%
April 20275.6%2.5%9.3%
May 20274.7%3.2%6.5%
June 20274.8%1.8%8.6%
July 20275.2%1.8%9.7%
August 20274.9%2.9%7.5%
September 20274.7%3.1%7.0%
October 20274.8%2.4%8.0%

Model: Agentic Investor TSFM (foundation model). Forecast generated 2026-11-15.

AI confidence

Mixed evidence

The tests show no consistent, material advantage over the no-change baseline.

Model: Agentic Investor TSFM (foundation model)

Accuracy vs naive
+17%Beats the no-change baseline over 12 tests (12 tests, 6 won)
Direction
68%No clear edge over a coin flip (98 of 144 calls right in 12 tests)
Turning points
28 of 58Anticipated some turns (58 turns in 12 tests, 0 without a turn)
Error vs baseline
17% lowerError ratio 0.83; 1.00 is a tie.
Tests won
6 / 12Complete rolling backtests; ties count as no win.
Test period
2014-11-01 to 2026-10-0112 observations ahead per test.
80% band coverage
81%Observed outcomes inside the band across all stored test windows.
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.

Replay past tests

Model comparison

Comparison pendingA new ticker first receives its serving model's forecast and evaluation. An eligible nightly batch can compare both candidates, subject to call budgets and retry limits.

Reading

It is above 68% 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 20264.8%
September 20264.4%
August 20263.9%
July 20263.0%
June 20264.7%
May 20264.9%
April 20263.1%
March 20263.3%
February 20263.5%
January 20261.5%
December 20254.6%
November 20254.2%
October 20255.0%
September 20255.0%
August 20254.0%
July 20253.8%
June 20252.0%
May 20251.0%
April 20252.2%
March 20252.1%
February 20252.2%
January 20253.7%
December 20241.9%
November 20241.7%

Source

Data: public market data feeds.

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