Wine Analytics

Author: Burak Kazaz, Syracuse University In this tutorial, we describe predictive and prescriptive analytical methods that assist primary enterprises in the wine supply chain in their decision-making processes. The tutorial begins with predictive models that estimate the true value of wine futures prices. These estimation models are essential to the financial exchange called the London International Vintners Exchange, Liv-ex, where wine futures contracts are traded. Coined as “realistic prices” by Liv-ex, these predictive models assist buyers in their purchasing decisions as they can determine whether a futures contract is underpriced or overpriced. The tutorial then develops risk mitigation models to assist winemakers so that they battle with uncertainty in weather conditions and tasting expert reviews. These prescriptive models rely on predictive analytics which help determine consumers’ utilities from buying the wine in advance, or later, or not purchasing at all. Prescriptive models such as a multinomial logit model focus on determining how much of the wine should be sold in advance in order to reduce the risk exposure and maximize the expected profits of the winemaker. On the buyer side, the tutorial introduces stochastic portfolio optimization models for wine distributors and importers in their decisions regarding how to allocate their limited budgets between wine futures contracts and bottled wine. These prescriptive models are, once again, built on predictive analytics that estimate the evolution of futures and bottle prices over time under fluctuating market and weather conditions.