Mexico Gold Reserves

Mexico · Quarterly series · EC-MX-GRES

Latest, Q3 2026

120.0 pts

-0.0% from Q2 2026

Open interactive chartMexico Gold Reserves in the app

125.363.942.54Q1 2000Q3 2027
History through Q3 2026, the forecast path to Q3 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for Q3 2027: 120.0 pts, with an 80% interval of 119.7 pts to 120.3 pts.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
Q4 2026120.1 pts119.8 pts120.3 pts
Q1 2027120.0 pts119.7 pts120.4 pts
Q2 2027120.0 pts119.7 pts120.3 pts
Q3 2027120.0 pts119.7 pts120.3 pts

Model: Agentic Investor TSFM (foundation model). Forecast generated 2026-11-14.

AI confidence

Weak evidence

The serving forecast made larger errors than the no-change baseline in these tests.

Model: Agentic Investor TSFM (foundation model)

Accuracy vs naive
-85%Trails the no-change baseline over 8 tests (8 tests, 3 won)
Direction
58%No clear edge over a coin flip (18 of 31 calls right in 8 tests)
Turning points
6 of 14Anticipated some turns (14 turns in 8 tests, 0 without a turn)
Error vs baseline
85% higherError ratio 1.85; 1.00 is a tie.
Tests won
3 / 8Complete rolling backtests; ties count as no win.
Test period
2018-12-01 to 2026-09-014 observations ahead per test.
80% band coverage
94%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 21% of the 39 earlier readings since Q4 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
Q3 2026120.0 pts
Q2 2026120.0 pts
Q1 2026120.1 pts
Q4 2025120.1 pts
Q3 2025120.1 pts
Q2 2025120.2 pts
Q1 2025120.2 pts
Q4 2024120.3 pts
Q3 2024120.4 pts
Q2 2024120.2 pts
Q1 2024120.4 pts
Q4 2023120.1 pts
Q3 2023120.1 pts
Q2 2023120.2 pts
Q1 2023120.2 pts
Q4 2022120.0 pts
Q3 2022120.0 pts
Q2 2022119.9 pts
Q1 2022119.9 pts
Q4 2021120.0 pts
Q3 2021119.9 pts
Q2 2021120.1 pts
Q1 2021119.9 pts
Q4 2020120.1 pts

Source

Data: public market data feeds.

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