Event-Driven Strategy on Binary Outcomes
ZS1!Last week, I laid the groundwork for a new idea on event-driven strategy. Event-Driven Strategy Focusing on Global Crisis. Three-factor Commodities Futures Pricing Model and Game Theory Matrix were introduced, illustrated with my own experience trading COMEX Gold Futures (GC) during the US-China trade conflict in 2019. My idea was featured on Editors’ Picks, generating over 16,000 views and nearly 800 likes.
Today, I would expand my idea to traders who want to construct their own event-driven strategy, in a 3-step approach.
Firstly, to qualify as a crisis, it needs to have the magnitude to shock the global market. Below is a few examples of global crises in the past five years:
• US-China Trade Conflict (2018): The two countries account for 42% of global GDP and have a combined population of 1.7 billion people, 22% of the world total. New tariffs imposed on thousands of goods with multi-year cumulative amount reaching $2 trillion.
• African Swine Fever (2018): It reportedly wiped out 60% of the pigs in China. Supply shortage from the No. 1 pork producer sent pork price up 300% in China. Global markets from the U.S. to Europe also felt the pain, as meat prices went up across the board, affecting pork, beef, lamb, and poultry.
• Brexit (2019): The withdrawal of Great Britain from the European Union resulted in a loss of 20% of GDP and 13% of population in the world’s third largest economic block. The impact on Britain itself is less than certain, as it would trade less with EU members, and more with countries outside of Europe.
• COVID (2019): The Coronavirus outbreak has turned into a global pandemic, and dramatically changed the world and our lives as we know it.
• Trump defeated in the U.S. presidential election (2020): It put a stop to the “America First” policies. In just four years, U.S. political landscape has once again swung widely.
• Russia-Ukraine Conflict (2022): First major military conflict in Europe since WW2. In addition to the hundreds of thousands of casualty and millions of refugees, the ongoing conflict disrupted the global supply of energy and agricultural products, sending US inflation to a 40-year high.
• Lockdowns in China (2022): Dozens of Chinese cities have been under some form of lockdowns in recent months, affecting a quarter of its population. It also created huge bottleneck in global supply chain, sending rippling effects around the world.
Secondly, analyze the impact of a crisis and attempt to define it in binary outcomes. These outcomes must be mutually exclusive and collectively exhaustive (MECE). If you are unclear of the outcomes, or there are too many of them, it would be difficult to construct a trading strategy around the crisis. Riding on the above examples of crises events, we will have their binary outcomes as follows:
• US-China Trade Conflict: Fight or Talk (alternatively, Tariff or No Tariff)
• African Swine Fever: Contained or Spread Out (Not Contained)
• Brexit: Approved or Not Approved
• US Election: Democrats Win or Republicans Win
• Ukraine situation: Putin Wins or Putin Loses (Peace deal is considered a Loss for Russia)
• China’s Zero-Covid Policy: Shanghai Lockdown or End of Lockdown
Thirdly, search and identify financial instruments that are most affected by the crisis. How do you know which is the right one amid a wide range of financial instruments? A quick test is to observe whether its price change correlates to the binary outcomes of the crisis.
In a classical supply and demand diagram, fundamental drivers move price up or down along the supply and demand lines in a continuous fashion. A crisis event shifts the lines to the left or to the right, pushing sudden price bumps as the event hits the news headlines.
Deep dive into the trade conflicts between China and the U.S., we can deploy the event-driven strategy on a commodity directly impacted by tariff. Interestingly, it was not a Chinese commodity tallied by Mr. Trump, but a U.S. commodity being taxed by China – Soybeans produced by U.S. farmers.
On April 2nd, 2018, the Trump administration announced that it would impose 25% tariffs on about 1,300 industrial, technology, transportation, and medical products made in China. In less than a day, China responded by imposing a 25% tariff on 106 goods in 14 categories, including soybeans, automobiles, and chemicals originating in the U.S.
Following China’s announcement, CBOT Soybeans Futures (ZS) dropped 2.2% and touched a low of 9.83/bushel. In my view, the initial price down was an understatement. I believed that CBOT Soybeans could go a lot lower with the tariff making the U.S. grains less competitive than those from South America. Over the next week, I put in Short ZS Futures positions, mainly on back-month contracts. Here are the logics behind my trades.
As the world’s largest consumer and importer of Soybeans, China imports 85% of its soybeans for domestic consumption to meet the huge appetite in cooking (soybean oil) and animal feeds (soybean meal). United States is the largest producer and exporter of Soybeans, with 68% of its export going to China.
Tariff takes time to impact the market fully. At first, Chinese importers expedited purchase of US soybeans ahead of the tariff deadline. They also increased buying from Brazil and Argentina. Eventually, when the cheap grains were exhausted and inventory was depleted, they would be forced to buy from American farmers again. The higher price with tariff would encourage use of alternative ingredients and reduce the overall Chinese demand on soybeans.
This prediction has been proven to be on the right track, as CBOT Soybean Futures continued to decline in the next three months until it hit 8.00/bushel, down 20% from levels before the tariff.
Let’s rework the Soybean trade using our 3-step approach.
Firstly, Does it have the magnitude to shock the global market? Yes. 40 million metric tons of soybeans, or $15 billion a year, would be taxed by China. It had huge negative impact on U.S. farm incomes.
Secondly, could we define the Soybean tariff as an event with binary outcomes? Yes, it is either “Tariff On” or “Tariff Off”. If the tension escalated, tariff would stick and become a permanent part of soybean cost. On the other hand, if US and China started a trade talk, soybean tariff could be removed later. While the tariff impact on nearby futures is fixed, it is not so on back-month futures prices.
Thirdly, is Soybean Futures the right instrument to use? Let’s apply our three-factor commodities pricing model on soybean, as follows:
Soybean Futures Price = Soybean Cash Price + Market Sentiment + Probability of Tariff
In a “Tariff On” scenario, the probability of tariff increases to 100%. While production cost in the U.S. is not affected, Chinese exporters must pay 25% more to buy. The reduced demand for U.S. soybean has the net impact of pushing futures price down. Therefore, the sign of Tariff Premium should be negative in the case of soybean futures.
In a “Tariff Off” scenario, trade talk could reduce the probability from 100% to 25%, for example. A signal of Chinese demand recovery has the net impact of raising futures price up.
Typically, about 1/3 of US soybean, or 40 out of 120 million metric tons of the grain, is exported to China every year. This sheer size made tariff a dominant factor driving soybean price, outweighing fundamental factors such as planted acreage, weather, and yield.
This concludes the use of US-China Trade Conflict as a case study for applying the event-driven strategy. My next writings would explore new strategies on more recent event shocks such as the lockdowns in China and the Ukraine situation.
Meanwhile, please tell me what you think, either on TV or by email.
Happy Trading.
Disclaimers
*Trade ideas cited above are for illustration only, as an integral part of a case study to demonstrate the fundamental concepts in risk management under the market scenarios being discussed. They shall not be construed as investment recommendations or advice. Nor are they used to promote any specific products, or services.
Jim W. Huang, CFA
jimwenhuang@gmail.com
jimwenhuang@gmail.com
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