Swaziland Balance Of Trade

Swaziland · Quarterly series · EC-SZ-BOT

Latest, Q1 2026

1.16B SZL

-40.1% from Q4 2025

Open interactive chartSwaziland Balance Of Trade in the app

3.041B983.3M-1.075BQ1 2005Q1 2027
History through Q1 2026, the forecast path to Q1 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for Q1 2027: 1.07B SZL, with an 80% interval of -269.62M SZL to 2.42B SZL.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
Q2 2026498.58M SZL-842.16M SZL2.18B SZL
Q3 20261.48B SZL-224.79M SZL3.04B SZL
Q4 20261.56B SZL1.02B SZL2.05B SZL
Q1 20271.07B SZL-269.62M SZL2.42B SZL

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
+31%Beats the no-change baseline over 8 tests (8 tests, 8 won)
Direction
72%No clear edge over a coin flip (23 of 32 calls right in 8 tests)
Turning points
12 of 17Anticipated most turns (17 turns in 8 tests, 0 without a turn)
Error vs baseline
31% lowerError ratio 0.69; 1.00 is a tie.
Tests won
8 / 8Complete rolling backtests; ties count as no win.
Test period
2018-06-01 to 2026-03-014 observations ahead per test.
80% band coverage
81%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 64% of the 39 earlier readings since Q2 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
Q1 20261.16B SZL
Q4 20251.93B SZL
Q3 20251.23B SZL
Q2 2025112.70M SZL
Q1 20251.65B SZL
Q4 20241.18B SZL
Q3 20242.18B SZL
Q2 2024-69.00M SZL
Q1 20241.35B SZL
Q4 2023656.50M SZL
Q3 20231.81B SZL
Q2 2023570.30M SZL
Q1 2023-285.50M SZL
Q4 2022900.50M SZL
Q3 2022917.20M SZL
Q2 2022-538.60M SZL
Q1 2022-362.30M SZL
Q4 20211.18B SZL
Q3 20211.20B SZL
Q2 2021-457.60M SZL
Q1 2021-226.00M SZL
Q4 20201.10B SZL
Q3 20201.78B SZL
Q2 2020195.20M SZL

Source

Data: public market data feeds.

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