A deep(er) dive in comex silver delivery notices

[AGgregator]

Using the present month's contract SIQ26 (Silver-August) as an example, I became curious as to what the ratio of House Stopped Contracts to Customer Stopped has occurred in Nick Laird's dataset. The presumption was that the House Accounts either wanted the Metal or if Exchanged for Physical or fiat the gain in $value. This month is extremely lop-sided towards House Stopped Contracts by ratio, less so, in total ounces.
Or looked at a different way




So, if one goes back a couple years, the pattern shows a House Stop bias. (No big surprise) The comparison is the number of ounces of House Stops less Customer Stops and since the contracts net to zero, the same difference in Customer Issues less House Issues. In the above graphic, the 944 contract House Stop bias and same in Customer Issues.
In a candle format, 1st Notice Day is the bottom of the white candles and the top of the black candles. As the month progresses, the ratio changes, but in general the House Stop ratio usually is above zero and usually increases.


There doesn't seem to be any direct correlation to price/volume, and here's the dataset going back to 2011

 

[pmbug]

Very interesting. Nice work!

Your candle charts threw me for a bit - you have the X axis showing most current dates on the left instead of the right. It looks to me like the data has become more chaotic (increased magnitudes and variance between black/white) in 2025-2026 versus 2023-2024.

 

[AGgregator]

Flipped the columns to go Left to Right so most current data is to the right.

So, in general to recap, Customer Accounts tend to Issue more than Stop, and House accounts tend to Stop more than Issue. To the extent that Customer Issues exceed Customer Stops, that number will now initialize above zero on 1st Notice Day: Customer Issues > Customer Stops. Customer Stops reduce the number

To the extent House Stops exceed House Issues, that number will now be negative on 1st Notice Day: House Issues < House Stops. House Issues increase the number.

For every Issue there is a Stop and if the distribution of Customer Issues equaled House Issues the overall number would be zero. The numbers are cumulative throughout the contract and represent the rate of change until Last Notice Day.

A candle where the House-Stop ratio grows throughout the contract is black(red), more relative Customer Issues and House Stops

A candle where the House-Stop ratio shrinks throughout the contract is white(green), increasing Customer Stops and House Issues.

***In crunching the data, and recently the black candles would be much more negative and the ratio more lop-sided because much of the Customer Stop-activity has occurred thru JPM's customer accounts, while at the same time JPM's House account has been all but quiet. ***

Also, flipping the data has caused the charts above to also flip from a white-candle positive bias to a black-candle negative bias due to the underlying setup, based on the order of subtraction, so it's kinda a mirror image... and, of course, I was looking for a (some) correlation to price movement.