Peru Consumer Spending

Name: Peru Consumer Spending
Creator: Agentic Investor

Peru · Quarterly series · EC-PE-CS

Latest, Q2 2026

106.72B PEN

+8.2% from Q1 2026

Open interactive chartPeru Consumer Spending in the app

History through Q2 2026, the forecast path to Q2 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for Q2 2027: 108.70B PEN, with an 80% interval of 104.91B PEN to 111.84B PEN.

Forecast path. Intervals are shown where available.
Period	Forecast	80% low	80% high
Q3 2026	103.16B PEN	101.24B PEN	104.88B PEN
Q4 2026	102.43B PEN	101.52B PEN	103.25B PEN
Q1 2027	102.08B PEN	99.55B PEN	104.23B PEN
Q2 2027	108.70B PEN	104.91B PEN	111.84B PEN

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: +21%Beats the no-change baseline over 8 tests (8 tests, 7 won)
Direction: 81%No clear edge over a coin flip (26 of 32 calls right in 8 tests)
Turning points: 7 of 9Anticipated most turns (9 turns in 8 tests, 0 without a turn)

Error vs baseline: 21% lowerError ratio 0.79; 1.00 is a tie.
Tests won: 7 / 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.

Band coverage uses all stored test windows, including model-selection windows when present; it does not determine the confidence label.
Evaluated 2026-11-15 against the cached history through 2026-06-01.
This is an evaluation of the serving model; it does not establish a winner across four model classes.

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

That is the highest of the 40 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.
Period	Value
Q2 2026	106.72B PEN
Q1 2026	98.63B PEN
Q4 2025	99.17B PEN
Q3 2025	99.98B PEN
Q2 2025	102.91B PEN
Q1 2025	95.23B PEN
Q4 2024	95.89B PEN
Q3 2024	96.22B PEN
Q2 2024	98.86B PEN
Q1 2024	91.82B PEN
Q4 2023	92.27B PEN
Q3 2023	93.00B PEN
Q2 2023	96.68B PEN
Q1 2023	90.40B PEN
Q4 2022	91.66B PEN
Q3 2022	92.96B PEN
Q2 2022	96.11B PEN
Q1 2022	90.42B PEN
Q4 2021	90.30B PEN
Q3 2021	92.18B PEN
Q2 2021	90.55B PEN
Q1 2021	85.17B PEN
Q4 2020	86.41B PEN
Q3 2020	81.61B PEN

Source

Data: public market data feeds.