India Gold Reserves

India · Quarterly series · EC-IN-GRES

Latest, Q3 2026

880.5 pts

+0.0% from Q2 2026

Open interactive chartIndia Gold Reserves in the app

959.7658.7357.8Q1 2000Q3 2027
History through Q3 2026, the forecast path to Q3 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for Q3 2027: 895.0 pts, with an 80% interval of 848.2 pts to 959.7 pts.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
Q4 2026882.7 pts872.8 pts892.4 pts
Q1 2027885.5 pts865.8 pts919.9 pts
Q2 2027887.9 pts856.4 pts930.9 pts
Q3 2027895.0 pts848.2 pts959.7 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
+24%Beats the no-change baseline over 8 tests (8 tests, 5 won)
Direction
91%Beats a coin flip (29 of 32 calls right in 8 tests)
Turning points
n/aToo few tests (0 turns, 8 needed) (0 turns in 8 tests, 7 without a turn)
Error vs baseline
24% lowerError ratio 0.76; 1.00 is a tie.
Tests won
5 / 8Complete rolling backtests; ties count as no win.
Test period
2018-12-01 to 2026-09-014 observations ahead per test.
80% band coverage
84%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 95% 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 2026880.5 pts
Q2 2026880.5 pts
Q1 2026880.5 pts
Q4 2025880.3 pts
Q3 2025880.2 pts
Q2 2025880.0 pts
Q1 2025879.6 pts
Q4 2024876.2 pts
Q3 2024853.6 pts
Q2 2024840.8 pts
Q1 2024822.1 pts
Q4 2023803.6 pts
Q3 2023800.8 pts
Q2 2023797.4 pts
Q1 2023794.6 pts
Q4 2022787.4 pts
Q3 2022785.4 pts
Q2 2022767.9 pts
Q1 2022760.4 pts
Q4 2021754.1 pts
Q3 2021743.8 pts
Q2 2021703.7 pts
Q1 2021695.3 pts
Q4 2020676.6 pts

Source

Data: public market data feeds.

More from Agentic Investor

Also stored for India