Introducing Risk Management API: A Forward Curve Risk And Forecast Model
Forward curves in commodity markets have a unique position in the trade. In essence, these time spreads are fundamental to daily trading activity and contract pricing. However trading firms often overlook them when developing forecasting or risk management tools. This is why AgFlow has developed a forward curve API dedicated to agricultural commodities risk management.
Basis Contracts: Fundamental Pricing Mechanisms For Agriculture Trade
Basis contracts, where delivery of physical goods is agreed for a future date at a specified price over or under a futures contract, are explicitly time spreads. A significant portion of any trading firm’s book is generally composed of contracts for long-dated delivery. Often extending six months or more into the future. Therefore, the core of most physical commodity trading is, in fact, trading the shape and evolution of the forward curve.
Given the critical importance of forward dated pricing, AgFlow wondered why rigorous analysis of time spread behavior is not fundamental to every trading firm. Thanks to our network, we realized that many different factors make it difficult or impossible for trading analysts and risk managers to successfully build tools to forecast and manage risk along the forward curve.
The most critical challenge is data availability. However fragmented sources, sometimes biased opinions, and irregular information flow resulting from illiquidity on further dated contracts make things even harder.
Storage: Unveiling The Connection Between Maturities Along The Forward Curve
Numerous research papers have demonstrated that intra-commodity time spreads are both statistically semi-predictable and informative for flat price forecasting. In fact, rigorous analysis of agriculture forward curves, specifically of wheat, have provided a significant contribution to a wide body of economic research.
In 1949, Holbrook Working, a Professor and Researcher at the renowned Food Research Institute at Stanford University, wrote a seminal economic paper entitled Theory of price of storage. Before this paper, it had been the norm in economic theory to consider futures contracts at different maturities on the same underlying commodity, the forward curve, as being “substantially independent”. And that the factors impacting one contract (such as expectations of a large harvest in a given month) had little bearing on the others.
Working’s Theory of price of storage, backed by a large body of empirical studies on the behavior of wheat futures, invalidated this earlier view. It also established the basis of interpolar pricing relationships that form a key element in understanding the spread behavior of storable commodities, fixed income curves, and even foreign exchange rate futures.
AgFlow’s Risk Management API: Extending Transparency Along Agriculture Forward Curves
Who would have guessed that early research in the wheat forward curve would provide such a critical economic breakthrough? This research as since then been key to understanding, pricing and trading forward contracts across asset classes.
With this in mind, AgFlow utilized its unparalleled database of physical cash prices – including bids, offers, and trades. We examined leading research on curve behavior and dynamics and applied advanced machine and deep learning algorithms to build a proprietary solution that provides clients fair, independent assessments of values that extend across the full-forward curve.
This tool looks to provide fair and independent estimates of full-forward price curves for over 100 global tickers in grains, oilseeds, and vegoils. These valuations are updated and delivered on a daily basis using a RESTful API that easily integrates into clients’ risk management or forecasting software. Which allows simple and automated estimates of hard to source and model price estimates for liquid or illiquid contracts.