Artificial intelligence improves fine wine price prediction

The price fluctuation of fine wines can now be predicted more accurately using a novel artificial intelligence approach developed by researchers at UCL. The method could be used to help fine wine investors make more informed decisions about their portfolios and encourage non-wine investors to start looking at wine in this manner and hence increase the net trade of wine. It is expected that similar techniques will be used in other 'alternative assets' such as classic cars. Co-author, Dr Tristan Fletcher, an academic at UCL and founder of quantitative wine asset management firm Invinio, said: "People have been investing in wine for hundreds of years and it's only very recently that the way they are doing it has changed. Wine investment is becoming more accessible and is a continually growing market, primarily brokered in London: the world-centre of the wine trade. We've shown that price prediction algorithms akin to those routinely used by other markets can be applied to wines." The study, published today in the  Journal of Wine Economics  with guidance from Invinio, found more complex machine learning methods outperformed other simpler processes commonly used for financial predictions. When applied to 100 of the most sought-after fine wines from the Liv-ex 100 wine index, the new approach predicted prices with greater accuracy than other more traditional methods by learning which information was important amongst the data.