AgenticInvestor

Paraguay Core Inflation Rate YoY

Paraguay · Monthly series · EC-PY-CIR

Latest, October 2026

0.9%

-0.07pp from September 2026

Open interactive chartParaguay Core Inflation Rate YoY in the app

8.33.981-0.3371November 2016October 2027
History through October 2026, the forecast path to October 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for October 2027: 2.2%, with an 80% interval of -0.3% to 5.7%.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
November 20260.9%0.5%1.4%
December 20261.0%0.0%2.1%
January 20271.1%0.1%2.3%
February 20271.2%0.5%2.0%
March 20271.3%0.8%1.9%
April 20271.5%0.3%2.9%
May 20271.7%-0.1%3.9%
June 20271.8%-0.3%4.5%
July 20271.9%0.2%4.0%
August 20272.0%0.0%4.7%
September 20272.1%-0.1%5.1%
October 20272.2%-0.3%5.7%

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

AI confidence

Supported evidence

The point forecast beat the no-change baseline overall and in a majority of the evaluated tests.

Model: Agentic Investor TSFM (foundation model)

Accuracy vs naive
+17%Beats the no-change baseline over 12 tests (12 tests, 8 won)
Direction
63%No clear edge over a coin flip (90 of 142 calls right in 12 tests)
Turning points
16 of 43Anticipated some turns (43 turns in 12 tests, 0 without a turn)
Error vs baseline
17% lowerError ratio 0.83; 1.00 is a tie.
Tests won
8 / 12Complete rolling backtests; ties count as no win.
Test period
2014-11-01 to 2026-10-0112 observations ahead per test.
80% band coverage
79%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 1% 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 20260.9%
September 20260.9%
August 20260.8%
July 20261.2%
June 20261.1%
May 20261.2%
April 20261.7%
March 20262.5%
February 20263.0%
January 20263.3%
December 20253.6%
November 20254.1%
October 20254.7%
September 20255.2%
August 20255.6%
July 20255.6%
June 20255.8%
May 20255.6%
April 20255.5%
March 20255.2%
February 20255.0%
January 20255.0%
December 20245.3%
November 20244.9%

Source

Data: public market data feeds.

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