Peru GDP From Construction
Peru · Quarterly series · EC-PE-GDPC
Latest, Q2 2026
9.66B PEN
+6.4% from Q1 2026
Forecast
Forecast for Q2 2027: 9.71B PEN, with an 80% interval of 8.34B PEN to 11.05B PEN.
| Period | Forecast | 80% low | 80% high |
|---|---|---|---|
| Q3 2026 | 10.53B PEN | 10.25B PEN | 10.83B PEN |
| Q4 2026 | 12.18B PEN | 10.75B PEN | 13.54B PEN |
| Q1 2027 | 9.15B PEN | 7.83B PEN | 10.47B PEN |
| Q2 2027 | 9.71B PEN | 8.34B PEN | 11.05B PEN |
AI confidence
Supported evidenceThe 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
- +41%Beats the no-change baseline over 8 tests (8 tests, 8 won)
- Direction
- 88%Beats a coin flip (28 of 32 calls right in 8 tests)
- Turning points
- 15 of 15Anticipated most turns (15 turns in 8 tests, 0 without a turn)
- Error vs baseline
- 41% lowerError ratio 0.59; 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.
- 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.
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 74% of the 39 earlier readings since Q3 2016.
Recent history (24 observations)
| Period | Value |
|---|---|
| Q2 2026 | 9.66B PEN |
| Q1 2026 | 9.08B PEN |
| Q4 2025 | 12.03B PEN |
| Q3 2025 | 9.93B PEN |
| Q2 2025 | 8.85B PEN |
| Q1 2025 | 8.02B PEN |
| Q4 2024 | 10.73B PEN |
| Q3 2024 | 9.44B PEN |
| Q2 2024 | 8.48B PEN |
| Q1 2024 | 7.55B PEN |
| Q4 2023 | 11.15B PEN |
| Q3 2023 | 9.00B PEN |
| Q2 2023 | 8.21B PEN |
| Q1 2023 | 7.21B PEN |
| Q4 2022 | 11.68B PEN |
| Q3 2022 | 9.92B PEN |
| Q2 2022 | 8.85B PEN |
| Q1 2022 | 8.15B PEN |
| Q4 2021 | 11.11B PEN |
| Q3 2021 | 9.57B PEN |
| Q2 2021 | 8.56B PEN |
| Q1 2021 | 8.18B PEN |
| Q4 2020 | 11.71B PEN |
| Q3 2020 | 7.73B PEN |
Source
Data: public market data feeds.
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