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ā† Back to Blog Ā· 2026-09-05 Ā· 6 min read Ā· Strategy Case Study

If you were actively trading in the second half of 2021, you probably remember the absolute chaos in the Chinese energy markets. Factories were shutting down, power was being rationed, and thermal coal went on a historic, parabolic rally before experiencing an equally violent crash. Most retail traders who tried to short the top got carried out, and those who chased the momentum eventually got caught in the policy-driven reversal. It was a minefield for directional traders.

But for those of us who prefer spread trading, the 2021 power crisis was a masterclass in fundamental market dislocations. When you trade a spreadā€”going long one correlated commodity and short anotherā€”you neutralize a massive chunk of macro noise. You aren't betting on the absolute direction of the market; you are betting on the relative value between two fundamentally linked assets. Today, we are going to break down how you could have traded the thermal coal and aluminum spread during that crisis, complete with contract specs, concrete rules, and execution realities. This is the kind of logic you can apply to any Chinese commodity futures pair.

The Macro Setup: Why Coal and Aluminum?

To trade a spread effectively, you need a fundamental anchor. You need to know exactly why Commodity A should move relative to Commodity B. The connection between thermal coal and aluminum in China comes down to one brutal reality: electricity costs.

Producing one ton of primary aluminum requires roughly 13,500 kilowatt-hours of electricity. It is one of the most energy-intensive industrial processes on the planet. In China, a significant portion of aluminum smelting capacity relies on coal-fired power. When thermal coal prices spike, the cost of generating electricity skyrockets. If power costs rise faster than aluminum prices, smelting margins collapse into negative territory.

What happens when smelters operate at a loss? They curtail production. During the 2021 power crisis, high coal prices and mandated energy consumption caps forced Chinese aluminum smelters to shut down capacity. This dynamic creates a fascinating spread opportunity. When coal rips higher and aluminum lags, the smelting margin is being crushed. Eventually, the market has to correct this: either coal falls back to earth (which it did, hard, after heavy policy intervention) or aluminum spikes to catch up to the new cost structure due to supply cuts. Either way, the spread between coal and aluminum reverts or shifts violently.

Contract Specs and Execution Realities

Before we look at the strategy rules, letā€™s talk about the instruments. Trading China futures requires a solid understanding of contract specifications. For this spread, we are looking at two different exchanges: the Zhengzhou Commodity Exchange (CZCE) for thermal coal, and the Shanghai Futures Exchange (SHFE) for aluminum.

Thermal Coal (CZCE: ZC)

Aluminum (SHFE: AL)

Notice the execution realities here. The most critical detail is the mismatch in trading hours. SHFE aluminum has a night session, while CZCE thermal coal does not. If a global macro event hits the tape at 22:00 Beijing time, your aluminum leg can gap or move while your coal leg is frozen. This means you are carrying overnight spread risk on one leg. In a backtest, you must account for this slippage and gap risk. You cannot assume both legs will always fill at your desired spread price if you need to adjust positions overnight.

The Spread Strategy: Trading the Smelting Margin

We are going to trade the Coal-to-Aluminum price ratio. Because the contract multipliers are vastly different (100 tons vs. 5 tons), we need to calculate the notional value of our legs to ensure we are dollar-neutral, or rather, RMB-neutral.

The core logic is a mean-reversion play on extreme margin distortion. When coal outpaces aluminum to a statistical extreme, we bet that the market will correct the smelting margin. We do this by shorting coal and going long aluminum.

The Math:

  1. Calculate the daily settlement price for the front-month ZC and AL contracts.
  2. Calculate the ratio: Ratio = ZC Price / AL Price.
  3. Calculate the 20-day rolling mean and standard deviation of this ratio.
  4. Calculate the Z-score: Z-score = (Current Ratio - 20-day Mean) / 20-day Std Dev.

Concrete Trading Rules:

Backtesting the Rules in a Crisis

When backtesting this strategy against the 2021 power crisis, the results highlight both the power and the danger of fundamental spread trading. In the middle of the year, as coal prices accelerated, the Z-score would have triggered our entry signal multiple times. The spread would have initially gone against youā€”coal kept climbing, dragging the Z-score higher. This is why the stop loss at +3.0 is non-negotiable.

However, when the Chinese government heavily intervened in the coal market in late 2021 to cap energy prices, coal crashed spectacularly. Meanwhile, aluminum prices remained elevated due to the permanent loss of smelting capacity that had been shut down during the crisis. The ratio collapsed violently back through the mean.

A trader who patiently waited for the Z-score to stretch and then shorted coal against long aluminum during the policy reversal would have captured a massive spread contraction. The key takeaway from the backtest is not that the strategy is a magic bullet, but that it kept you alive. A naked short in coal during the middle of the rally would have liquidated your account. The long aluminum leg acted as a hedge, absorbing the pain until the fundamental reality reasserted itself.

Practical Application Beyond Coal and Aluminum

The beauty of this structural approach is that it is entirely portable to other Chinese commodity futures. You are trading the crush margin or the processing margin. Once you understand the fundamental link between raw materials and finished goods, you can build similar statistical arbitrage models across the board.

Take the steel complex, for example. Many global traders want to trade rebar/iron ore. The logic is identical: iron ore and coking coal are the inputs, rebar is the output. When iron ore spikes and rebar lags, the steelmaking margin is crushed. Mills cut production, iron ore demand drops, and rebar supply tightens. You can apply the exact same 20-day Z-score model to the Iron Ore/Rebar ratio. Short iron ore, long rebar when the Z-score hits +2.0. Exit at 0. Stop out at +3.0.

This is how professionals operate. They strip away the directional bias and trade the structural inefficiencies of the market. But theoretical backtesting on a spreadsheet is only the first step. Real markets have slippage, overnight gap risk on mismatched trading sessions, and emotional pressure.

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