The Predictive Power of NZX Dairy Futures

We assess the market efficiency of four New Zealand Exchange (NZX) dairy futures, which are cash-settled to Global Dairy Trade (GDT) results. Importantly, we identify quantitative drivers of the deviations from futures to spot prices and compare the forecasting accuracy of the four dairy futures. The results of this study are relevant for local and international participants on New Zealand dairy spot and futures markets, from farmers and dairy processors to traders and international food manufacturers. Established in 2008, the GDT is an online platform that runs twice-monthly ascending price clock dairy auction events, providing widely-accepted price references for sellers and buyers of dairy commodities including whole milk powder (WMP), skim milk powder (SMP), butter, and anhydrous milk fat (AMF). WMP futures were launched by NZX in October 2010, SMP and AMF futures followed in February 2011, and NZX butter futures were introduced in December 2014. With these four contracts combined, over 800,000 metric tons of dairy futures were traded to July 2018. As New Zealand is one of the world’s largest dairy exporters, accounting for one-third of internationally traded dairy products in 2017 despite only being the eighth-largest dairy producer, both GDT spot prices and the NZX dairy futures have an immediate and significant impact on international dairy trade. The dataset spans October 2010 to July 2018, comprising of 179 GDT auction events, 179 WMP, 157 SMP futures, 151 AMF and 79 butter futures data and consists of data that is auction- but not commodity-specific as well as data that is both auction- and commodity-specific. For example, the quantity of volume sold at each GDT event is available for WMP, SMP, AMF, and butter separately, while the auction participation of buyers from different regions is only given for the entire auction event. The GDT data set of this study allows the assessment of futures’ forecast accuracy or market efficiency and additionally the identification of quantitative drivers thereof as well as interdependencies of spot and futures markets. We use standard regression methods to assess predictive power of futures and identify drivers of their forecast accuracy. We provide evidence the four examined NZX dairy futures – whole milk powder, skim milk powder, anhydrous milk fat, and butter – perform efficient price discovery, as they provide market participants with accurate and unbiased GDT price forecasts. We also identify several statistically and economically significant factors influencing futures’ forecast accuracy or market efficiency. For example, SMP, AMF, and butter futures are found to forecast each month’s first GDT result significantly more accurately than the second. Moreover, the forecast error is not driven by trade volumes or open interest, confirming existing literature that efficient forecasting is not dependent on high liquidity but informed trading. Also, several futures’ forecast accuracies were positively or negatively affected by the participation of certain buyer groups on GDT, hinting toward varying levels of activity among these buyers on the respective NZX futures market. Lastly, WMP futures are proven to provide significantly more accurate GDT price forecasts than the other three contracts.