Identifying undervalued wines on the market, which may reveal themselves as valuable bargains, is no easy feat for a wine collector: information is often fragmented across several sources and it is difficult to pinpoint exactly what should be the most equitable price for a wine.
We recently upgraded our Fair Price model on our platform: in a nutshell, Saturnalia users are now able to identify at a glance which wines are undervalued on the Bordeaux market.
How is the Saturnalia Fair Price calculated? Our Fair price is a regression model that expresses which wines on the market are the most convenient and which are overpriced based on their scoring and price history. The system is built on two main hypothesis:
How do you understand whether a wine is over- or under-valued? Simply check if the vintage point is above or below the dashed line: above means potentially overpriced, below the opposite.
Platforms such as Liv-ex developed in the past similar methods to help merchants and private collectors identify what the fair value for a wine should settle on. The pictures below offer two examples of our Fair Price model, compared to Liv-ex Fair Value.
Let’s consider the charts above showing the Liv-ex Fair Value for Ducru Beaucaillou (figure 2) and Haut-Brion (figure 4). First of all, both are examples of good correlation, with R² above the 0.5 threshold. If we consider Ducru Beaucaillou, the behaviour of the two models (Saturnalia and Liv-ex) is very similar. However, the Liv-ex Fair Value tends to decrease with scores below 89: a trend that is not common. On the other hand, the second case – Haut-Brion – shows a totally different approach. It seems to suggest that a higher score corresponds to a lower market price or at least a plateau in value. Our model – based on the previous input assumptions – does not allow this fitting, being able to score a good correlation anyway (R²=0.75).
Following our initial explanation, can you recognise a good deal for these wines? 2015 for Ducru seems overpriced (12×75, £1,700) while a good bargain could be vintage 2019 or 2021.
Thus, it only takes a rapid glance to distinguish between undervalued and overvalued wines, making our model a helpful tool in providing additional information when making a market decision. Obviously, our model is not 100% reliable: the correlation between scores and prices is not a given, as other factors which cannot be predicted by the model may enter the scene. Let’s consider for example what happened with Figeac after September 2022 classification: as you can see from our chart below (figure 5), all vintages have benefited from an increase in value towards the end of the time period. Our model does not include such market commotions, and the same goes for ageing potential.
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