Burak KAZAZ, (Syracuse University)
January 19th 2021, 3:00 pm – 4:00 pm (CET)
In this tutorial, we describe predictive and prescriptive analytical methods that assist primary enterprises that produce and distribute wine 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 known as 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 in mitigating 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 it 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 risk exposure and maximize the expected profits of the winemaker.
On the buyer side, the tutorial introduces stochastic portfolio optimization models for both wine distributors and importers in their decision regarding how to allocate 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.
Wine is an exemplary agricultural product; its production and quality perceptions are widely tracked by businesses and consumer.
The predictive and prescriptive models of this tutorial help create transparency in this largely opaque market.
They assist the industry in its drive towards market efficiency.
The tutorial also offers future research directions in wine analytics and describes how these techniques can be beneficial for the production and distribution of other agricultural products.