Paraguay Consumer Spending

Paraguay · Quarterly series · EC-PY-CS

Latest, Q2 2026

63.59T PYG

+1.0% from Q1 2026

Open interactive chartParaguay Consumer Spending in the app

71.35T37.35T3.347TQ3 1996Q2 2027
History through Q2 2026, the forecast path to Q2 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for Q2 2027: 66.62T PYG, with an 80% interval of 61.54T PYG to 71.35T PYG.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
Q3 202664.24T PYG63.24T PYG65.27T PYG
Q4 202668.08T PYG66.10T PYG70.29T PYG
Q1 202765.87T PYG62.73T PYG68.97T PYG
Q2 202766.62T PYG61.54T PYG71.35T PYG

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
+51%Beats the no-change baseline over 8 tests (8 tests, 8 won)
Direction
97%Beats a coin flip (31 of 32 calls right in 8 tests)
Turning points
14 of 15Anticipated most turns (15 turns in 8 tests, 0 without a turn)
Error vs baseline
51% lowerError ratio 0.49; 1.00 is a tie.
Tests won
8 / 8Complete rolling backtests; ties count as no win.
Test period
2018-09-01 to 2026-06-014 observations ahead per test.
80% band coverage
84%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 97% of the 39 earlier readings since Q3 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
Q2 202663.59T PYG
Q1 202662.99T PYG
Q4 202564.46T PYG
Q3 202560.97T PYG
Q2 202560.69T PYG
Q1 202558.35T PYG
Q4 202461.06T PYG
Q3 202455.42T PYG
Q2 202455.03T PYG
Q1 202453.63T PYG
Q4 202356.24T PYG
Q3 202351.32T PYG
Q2 202350.36T PYG
Q1 202349.57T PYG
Q4 202252.85T PYG
Q3 202248.51T PYG
Q2 202246.10T PYG
Q1 202244.28T PYG
Q4 202146.69T PYG
Q3 202142.67T PYG
Q2 202141.12T PYG
Q1 202139.37T PYG
Q4 202041.43T PYG
Q3 202037.46T PYG

Source

Data: public market data feeds.

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