Constructing a Commodity Balance Sheet

Welcome to your second lesson in the "Commodity Fundamentals and Industrial-Metal Cycles" module. In our previous session, we traced the physical journey of copper from a raw ore to a refined metal, giving you a qualitative map of the supply chain. Now, we will transition from that qualitative description to a quantitative one.

Your goal for this lesson is to learn how to construct a commodity balance. This is a fundamental tool for any commodity analyst or trader. It's essentially an accounting sheet that tracks the total supply and total use of a commodity within a specific market (like a country or the entire globe) over a period. By systematically accounting for all the inflows and outflows, we can determine whether the market is in a surplus (supply exceeds demand) or a deficit (demand exceeds supply). This balance, or imbalance, is a primary driver of commodity prices.

The Logic of a Commodity Balance

At its heart, a commodity balance is based on a simple principle of conservation: material cannot be created or destroyed, only moved or transformed. In this context, it means that all the material available in a market must be accounted for.

Your background in physics and electronics provides a useful analogy. Think of Kirchhoff's current law, which states that the sum of currents entering a junction must equal the sum of currents leaving it. A commodity balance sheet applies the same logic to physical material. The "junction" is the market, the "currents in" are supply sources, and the "currents out" are uses. Any difference is absorbed by a change in storage, or inventory.

To understand this conceptual framework, please read the first part of the following resource from SG Group.

As the reading explains, the balance sheet is an identity. The two sides must always close. The price action you see on a chart is, in large part, the market's reaction to whether the resulting inventory level is judged to be scarce or abundant.

The Balancing Equation

We can formalize this logic with a simple accounting identity. For any given period and region, the relationship between the components is as follows:

Total Supply = Total Use

Expanding these terms gives us the full picture:

Beginning Stocks + Production + Imports = Consumption + Exports + Ending Stocks

This is the master equation. However, traders are often most interested in the change in the market balance from one period to the next. By rearranging the equation, we can isolate the change in inventory:

Ending Stocks - Beginning Stocks = (Production + Imports) - (Consumption + Exports)

Let's simplify this:

Change in Stocks = Total Supply - Total Demand

This powerful equation tells you the net result of all market activity in a period.

• If Change in Stocks > 0, supply was greater than demand, and the market was in surplus.
• If Change in Stocks < 0, demand was greater than supply, and the market was in deficit.

The following reading formalizes these equations.

Constructing a Balance Sheet: A Practical Example

Now, let's move from theory to practice. We will construct a simplified balance sheet for the U.S. refined copper market for February 2022, using data from a monthly report by the U.S. Geological Survey (USGS).

The resource below is a typical example of the kind of government data release that commodity analysts rely on. We will focus on Table 7, which, despite its title, contains all the necessary components for our balance equation.

Let's use the data from that table for February 2022 to populate our balance equation. Note that government statistics often have small discrepancies due to rounding, so our manually calculated numbers might differ slightly from the totals shown.

Here are the components for February 2022 (all in metric tons):

• Production (Supply): The table splits this into Primary refined copper production (72,100) and Copper in old scrap (13,400). Scrap is a key source of secondary supply.
  • Total Production = 72,100 + 13,400 = 85,500
• Imports (Supply): Refined imports for consumption = 34,300
• Exports (Demand): Refined exports = 3,110
• Stock Change (Balancing Item): Refined stock change during period = -5,850

The negative sign for the stock change is critical. It signifies that inventories decreased—a stock draw. This immediately tells us the market was in a deficit.

Let's verify this using our equation: Change in Stocks = (Total Production + Imports) - (Exports + Consumption).

The USGS table calculates a figure called "Apparent consumption". This is a derived figure, not a directly measured one. It's calculated to make the balance sheet close. Let's see how. According to footnote 4, the formula used is a rearrangement of our master identity. If we solve for consumption, we get:

Consumption = (Total Production + Imports) - Exports - Stock Change
Consumption = (85,500 + 34,300) - 3,110 - (-5,850)
Consumption = 119,800 - 3,110 + 5,850 = 122,540

The USGS table reports the "Apparent consumption" as 123,000 tonnes. Our calculated value of 122,540 is very close, with the small difference attributable to rounding in the source data. This demonstrates a key aspect of fundamental analysis: often, one of the components (usually consumption) is not directly measured but is implied by the other, more easily measured components of the balance sheet.

Interpreting the Balance: Is the Market "Tight"?

We've established that the U.S. copper market was in a deficit of 5,850 tonnes in February 2022. But is this a large or a small number? A deficit is bearish if it's small and inventories are high, but it can be extremely bullish if inventories are already low.

To answer this, we need to put the absolute inventory level into context. We do this by normalizing it against the rate of consumption. The two most common metrics are the stocks-to-use ratio and days of cover.

Let's calculate the "days of cover" for the U.S. market at the end of February 2022.

1. Find the ending stock level: In the USGS report (LINK), Table 10 on page 11 shows Refined copper stocks at the end of February 2022 were 127,000 tonnes.
2. Calculate the daily consumption rate: Using our calculated "Apparent consumption" for the month (122,540 tonnes) and assuming February has 28 days:
   • Daily Consumption = 122,540 / 28 ≈ 4,376 tonnes/day
3. Calculate Days of Cover:
   • Days of Cover = Ending Stocks / Daily Consumption = 127,000 / 4,376 ≈ 29 days

This means that at the end of February 2022, there was enough refined copper in U.S. warehouses to cover approximately 29 days of consumption. By itself, this number is just a fact. Its power comes from comparison. A trader would compare this to the historical average for that time of year. If the 5-year average days of cover is, say, 45 days, then 29 days would signal a significantly "tighter" than normal market, which is generally a bullish sign for prices.

Conclusion

In this lesson, we have moved from a qualitative view of the commodity world to a quantitative one. You now have the foundational tool for fundamental analysis: the commodity balance sheet.

Here are the key takeaways:

• A commodity balance is an accounting identity that equates total supply with total use: Beginning Stocks + Production + Imports = Consumption + Exports + Ending Stocks.
• The market balance is determined by the change in inventories: Change in Stocks = Supply - Demand. A negative change indicates a deficit, while a positive change indicates a surplus.
• Data from government and industry groups can be used to construct a balance sheet, but you must pay close attention to definitions and footnotes.
• Key figures like consumption are often not directly measured but are implied by the other components of the balance sheet.
• To interpret whether an inventory level is "high" or "low," it must be normalized using metrics like the stocks-to-use ratio or days of cover and compared against historical data.

In today's lesson, we worked with a pre-packaged data report from the USGS. In our next lesson, "Extract production, consumption, and inventory data for one industrial metal from public industry and government sources," we will tackle the practical challenge of finding and assembling this data yourself from various online sources. This will put you one step closer to building your own independent market analysis.