More than a week ago, I posted this cryptic tweet. Although it was about gold, the same can be applied to any other physical commodity. But it is especially true for metals like copper or silver.
Supply vs. demand for silver
The point is that industrial use cases for metals involve pretty complex processes which are inherently hard to understand and predict.
I vividly remember the attitude towards silver at the beginning of the previous decade, after the GFC. Comprehensive research papers from renowned institutions were calling for an explosion in demand for silver coming from hi-tech applications like batteries, nanotech, and electrification in general.
Yet, none of it really materialized. Sure, demand for silver has been drifting higher over the years. But it was very gradual. All these smart sounding forecasts were wrong, as no explosion in demand really happened.
Besides not understanding the complex demand use cases, the analysts forgot that technology is a double-edged sword. While some applications led to an increase in demand for silver, other technological breakthroughs resulted in higher efficiency, requiring much less precious metal than originally estimated.
The supply side, on the other hand, looks much simpler. New metal can come predominantly from mining. And while mining for silver is not a trivial endeavor, it is much easier to understand and estimate than some high-tech demand use cases. Moreover, demand can change pretty quickly, but supply does not. Building a new mine takes at least 5 years.
So when I get to my original tweet, I find trading strategies built around some supply scenario much more successful than hypotheses centered on changes in demand.
Silver mining costs
But how is that related to silver mining costs? Well, the absolutely best opportunities emerge when the price of silver drops so low that it starts to affect supply. Estimating the mining costs of the primary silver miners can prove immensely valuable.
We prefer to watch the so-called all-in sustaining costs (AISC) that include not only the expenses directly associated with the mining operation, but also indirect costs such as exploration, capital expenditures to maintain current production levels, and reclamation expenses. As its name implies, the AISC determines the price level at which the mining operation is sustainable in the long term.
Back to May 2022
Let’s get back to May last year. Silver was trading close to $22, #silversqueeze was trending on Twitter, and everybody and his dog were absolutely certain silver is going above $30 in summer.
Well, everybody except us. We used the power of the SpreadCharts app to correctly estimate more downside in the medium term. And more importantly, we did a quick analysis of the primary silver miners’ all-in sustaining costs to estimate the downside to be between $15 and $20.
Here is the proof, as we are unlocking the old video analysis for everyone to see.
Current silver mining costs
Today, we’re releasing a follow-up analysis. But it will not be a simple and crude estimate like last year. This time, I manually aggregated all the data for the most prominent primary silver miners and did proper statistical analysis, revealing more exact price levels.
These price levels will act as pain points for the miners and most likely offer strong long-term support for the price of silver.
Aggregating the historical data was a very time-consuming process. Writing it down manually was actually the easiest part. The problem is that AISC is not a GAAP compliant metric. Every company can report slightly different data. Sometimes the companies even change the way they calculate AISC and issue some revised data. I had to study accounting details thoroughly in the historical quarterly reports for each company and decide what data I can include in the statistics. In some cases, I had to work with the data on an individual mine basis.
But here’s the good news: you don’t have to undergo this multi-week, boring endeavor. Users of the premium version of SpreadCharts can watch the processed data in our latest video analysis. We have also analyzed the trends in the data and explained them to you in simple terms. Enjoy!