An average can hide how often a premium was near zero or unusually high. We divided every available observation from October 19, 2025 through October 18, 2026 into four simple ranges. The ranges describe this site's normalized values; they are not risk ratings or trading thresholds.
Gold distribution
| Series | n | Below 0% | 0-5% | 5-15% | 15%+ |
|---|---|---|---|---|---|
| SGE | 237 | 118 (49.8%) | 118 (49.8%) | 1 (0.4%) | 0 |
| MCX | 254 | 0 | 9 (3.5%) | 198 (78.0%) | 47 (18.5%) |
| LBMA-related | 11 | 6 (54.5%) | 5 (45.5%) | 0 | 0 |
Gold SGE was almost evenly split between a discount and a premium below 5%, with only one observation above 5%. Gold MCX occupied a different numerical range: 245 of 254 observations were at least 5%, and 47 were 15% or higher. This difference may reflect contracts, timestamps, vendor conversion and local market structure as well as price conditions.
Silver distribution
| Series | n | Below 0% | 0-5% | 5-15% | 15%+ |
|---|---|---|---|---|---|
| SGE | 240 | 4 (1.7%) | 41 (17.1%) | 159 (66.2%) | 36 (15.0%) |
| MCX | 255 | 0 | 15 (5.9%) | 130 (51.0%) | 110 (43.1%) |
| LBMA-related | 13 | 5 (38.5%) | 8 (61.5%) | 0 | 0 |
Silver had more observations in the upper ranges than gold. Silver MCX was at least 15% on 110 of 255 recorded dates, while silver SGE was in that range on 36 of 240 dates. These frequencies describe the stored comparison, not the profit available to a buyer or seller.
Median levels add context
The one-year medians were 0.01% for gold SGE, 7.68% for gold MCX, 11.28% for silver SGE and 10.09% for silver MCX. The median and frequency table together are more informative than a single latest observation, but they still do not make differently specified markets directly interchangeable.
Why LBMA-related percentages should be treated separately
There were only 11 gold and 13 silver LBMA-related observations. Percentages calculated from such small samples can move sharply when one row is added. They are shown for transparency, not as a reliable estimate of a full year's London distribution.
Method and interpretation
We counted finite premium values in the public history response and used mutually exclusive ranges: below 0%, 0% to below 5%, 5% to below 15%, and 15% or more. Missing dates were excluded. The cutoffs are descriptive conveniences, not evidence that a value becomes normal, abnormal or tradable at a boundary.
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