Lithuania Productivity

Lithuania · Quarterly series · EC-LT-PROD

Latest, Q2 2026

128.3 pts

+1.3% from Q1 2026

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138.291.1143.98Q3 1996Q2 2027
History through Q2 2026, the forecast path to Q2 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for Q2 2027: 130.8 pts, with an 80% interval of 123.4 pts to 138.2 pts.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
Q3 2026128.8 pts126.0 pts131.9 pts
Q4 2026129.6 pts125.4 pts134.0 pts
Q1 2027130.3 pts124.8 pts136.1 pts
Q2 2027130.8 pts123.4 pts138.2 pts

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
+26%Beats the no-change baseline over 8 tests (8 tests, 6 won)
Direction
84%No clear edge over a coin flip (27 of 32 calls right in 8 tests)
Turning points
1 of 9Anticipated some turns (9 turns in 8 tests, 1 without a turn)
Error vs baseline
26% lowerError ratio 0.74; 1.00 is a tie.
Tests won
6 / 8Complete rolling backtests; ties count as no win.
Test period
2018-09-01 to 2026-06-014 observations ahead per test.
80% band coverage
78%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

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.
PeriodValue
Q2 2026128.3 pts
Q1 2026126.7 pts
Q4 2025127.0 pts
Q3 2025124.8 pts
Q2 2025124.2 pts
Q1 2025123.8 pts
Q4 2024122.2 pts
Q3 2024121.2 pts
Q2 2024121.2 pts
Q1 2024121.4 pts
Q4 2023121.6 pts
Q3 2023121.5 pts
Q2 2023121.1 pts
Q1 2023120.3 pts
Q4 2022117.8 pts
Q3 2022120.5 pts
Q2 2022120.1 pts
Q1 2022123.1 pts
Q4 2021125.6 pts
Q3 2021125.7 pts
Q2 2021123.9 pts
Q1 2021125.9 pts
Q4 2020124.9 pts
Q3 2020124.1 pts

Source

Data: public market data feeds.

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