Case Study: Hedging Soymeal Price Risk for Feed Mills in Vietnam Industry Background Vietnam has a population of over 90 million people and consumes over 6 million metric tons (MT) of soymeal, mostly as animal feed for hogs, the most popular meat consumed in the country. Vietnam is one of the world's largest importers of soymeal, importing over 4.3 million MT2 in 2017, 85% of which was from Argentina and the rest mainly from the U.S. and Brazil. Soymeal production within Vietnam is small, and domestic demand is mostly met by imports. Numerous small- to medium-sized feed mills buy and import most of the soymeal. Risks Associated with Soymeal Imports Vietnam is the world's second biggest soymeal importer (after the EU-27 bloc); the three largest soymeal exporters are Argentina, Brazil and the U.S. The Sino-U.S. trade tariff disagreements that started in April 2018 have had an impact on the global soybean and soymeal trade resulting in the possibility for additional price volatility. Firms involved in importing soymeal into Vietnam may want to consider an active hedge program to guard against unforeseen price volatility

Commodities are a volatile asset class. Soymeal prices were relatively calm in the second half of 2018 despite turbulence caused by the Sino-U.S. trade tariff negotiations. Volatility typically increases from May to July when the U.S. soybean planting season gets underway. When traders buy soymeal from overseas soybean crushers, the cargoes are usually procured as basis contracts where the soymeal is priced against an index such as the CBOT Soybean Meal futures price. The international traders importing soymeal in this manner typically hedge their price risk. The international traders then may sell to local traders, who then on-sell to domestic feed mills either at a fixed price or at a basis to the Soybean Meal futures price. Vietnam is home to many small feed mills, who buy soymeal from traders either at fixed prices or at a basis. Purchases direct from crushers or international traders are typically conducted in USD while purchases from local traders are typically conducted in Vietnamese Dong (VND). For purposes of this case study, currency risk is ignored by assuming that the foreign exchange rate between USD and VND is constant. Therefore, for mills buying at a basis, the main price risk is that soymeal prices may rise between the time of the contract and delivery on the contract. For mills buying on fixed prices, the main price risk is the opportunity cost that prices may decline between the time of the contract and delivery on the contract. Company Profile and Situation Consider an example company and its situation - Tortilla is a medium sized feed mill which buys soymeal from international and local traders. It buys in small parcels of 2,000 to 5,000 MT at a time, and its purchases can be at fixed prices or at a basis to the CBOT Soybean Meal futures price. In March, Tortilla placed a purchase order with an international trader for 2,000 MT of soymeal for physical delivery in June. This parcel would be part of a larger 50,000 MT cargo that will be loaded from the Puerto Parana port in Argentina for May shipment, and be delivered to the Phu My-Ba Ria Serece port off Ho Chi Minh City3 in June. In March, soymeal was quoted at $380 per MT in the Argentinian cash market for May shipment. Tortilla agreed to buy at a fixed price of $390 payable upon delivery in June. Due to global economic conditions, Argentinian soymeal prices fall by $60 per MT when June arrives. Other feed mills in Vietnam who were actively placing orders for soymeal in June were being quoted $320 per MT, for August shipment. Tortilla wondered if it should have bought on basis instead of at fixed prices. Tortilla did not open a letter of credit at the time it bought the meal, so the firm may face difficulty getting its cargo financed from banks since banks sometimes refuse to finance cargoes if there is a risk that the customer might fail to repay the loan.

450 400 350 300 250 Jan-16 Feb-16 Mar-16 Apr-16 CBOT Soybean Meal Historical Price & Volatility May-16 Jun-16 Jul-16 Aug-16 Sep-16 Source: Bloomberg, CME Group data Oct-16 Nov-16 Dec-16 Jan-17 Feb-17 Mar-17 Apr-17 May-17 Price ($/bu) Jun-17 Jul-17 n Aug-17 Sep-17 Oct-17 Nov-17 Dec-17 Jan-18 Feb-18 Mar-18 Apr-18 May-18 -30D Volatility (%)(RHS) Jun-18 Jul-18 Aug-18 Sep-18 Oct-18 Nov-18 Dec-18 Jan-19 Feb-19 Mar-19 40 30 20 10