Researchers Kevin Guo and Tim Leung from the Department of Applied Mathematics at the Hong Kong Polytechnic University have published a study that sheds light on the persistent gap between futures and spot prices in the grains market. Their research, titled “Understanding the Non-Convergence of Agricultural Futures via Stochastic Storage Costs and Timing Options,” offers a novel approach to understanding this market phenomenon.
The study focuses on the positive basis observed at the maturity of futures contracts, a situation where the futures price does not converge to the spot price as expected. Guo and Leung propose that this non-convergence can be attributed to the timing options available to futures holders. Specifically, they argue that the ability to choose when to exercise the shipping certificate—an item delivered upon futures contract maturity—and subsequently liquidate the physical grain, contributes to the observed price discrepancy.
To model this behavior, the researchers incorporate stochastic elements into both the spot price and storage costs. They then solve an optimal double stopping problem to determine the best strategies for exercising the shipping certificate and liquidating the grain. This approach allows them to derive explicit no-arbitrage prices for the shipping certificate and the associated futures contract.
One of the key contributions of this research is the development of new models for stochastic storage rates. These models provide a more accurate representation of the real-world dynamics influencing the grains market. By calibrating their models to empirical futures data during periods of observed non-convergence, Guo and Leung demonstrate the premium generated by the shipping certificate.
The practical implications of this research are significant. For market participants, understanding the factors driving non-convergence can improve pricing strategies and risk management. For policymakers, it offers insights into the mechanisms underlying market inefficiencies, potentially informing regulatory interventions aimed at enhancing market transparency and stability.
Guo and Leung’s work not only advances the theoretical understanding of futures markets but also provides actionable insights for practitioners. By highlighting the role of timing options and stochastic storage costs, their research underscores the importance of incorporating real-world complexities into financial models. This study is a testament to the value of interdisciplinary research, combining mathematical rigor with practical market insights to address pressing questions in the field of agricultural futures. Read the original research paper here.