By Sisi Liang,
I believe in connecting seemingly unrelated ideas. I believe that some of the most profound breakthroughs come from seeing commonality among completely unrelated things. I believe that synthesizing and making this kind of connection is fundamentally human. And it’s one of the things that give me the most joy.
What do James Joyce’s Ulysses and Finnegans Wake have in common with real analysis and abstract algebra in mathematics? They both taught me how to learn and work with difficult concepts—that I need to first accept what is, and then and only then can I respond to it. Plus, nuclear physicists now have discovered that the text from Finnegans Wake is a purely mathematical multifractal. How cool is that?!
What do credit cards and wine have in common? Consumer behavior on their credit cards follows a lifecycle, from the moment they become a “member”—that for credit cards, on average, a consumer has the highest probability of default after around 2 years of becoming a member, and the odds becomes lower from that point on. This means there is a lifecycle curve for an average consumer. This in itself was fascinating to me, because it gives us so much predicting power, and it was able to predict the 2008 financial crisis 2 years before it happened.
But even more exciting is the fact that your “member since” is, in fact, your “vintage.” And this “vintage” concept comes from wine. As a credit card holder, your behavior is framed by your vintage (the “age” you have been on the credit card), your vintage quality (your credit quality, such as your credit score), and your environment (the economy, and anything in the external market). Similarly, the same framework applies to high-end wine prices in auctions. These fine wine prices can be determined by the vintage of the wine (the “age” of the wine), the vintage quality (the weather condition and other factors related to the year when the grapes were harvested and when the wine was made), and the environment (the market condition—demand, supply, the economy, etc.). When the seemingly unrelated things are connected by a framework, we can use this framework to forecast both—losses in retail banking, and price appreciation in wine auctions.
I deeply believe in this modeling methodology, and believe that more people should know about it and take advantage of it. Therefore, when renowned data scientist Joe Breeden came to me with the idea of modeling fine wine prices to help wine investors and collectors maximize their long-term returns, I took on it with the mission to bring it out to the right people. We have now built this website with more than 1.5 million auction prices from auction houses around the world spanning 15 years. Here you can search for any particular wine and vintage that have been sold in auctions (at a certain level of frequency), and see their past prices and our forecasts for the wines’ future long-term appreciation, so that as a fine wine buyer you can time your purchase more strategically and know if you’re purchasing in the money or out of the money.
We believe in using powerful tools from other, seemingly unrelated disciplines and apply them to a problem we’re trying to solve. The “otherness” of the solution is where its power lies. And we believe in simple and elegant solutions to complex problems.
Our forecasts are for people (in this case, wine buyers—investors and collectors, auction houses and investment funds) with a curious mind, and who want to maximize their long-term returns in the fine wines they buy.
“Once you see it, you can’t unsee it”—we want our customers to become completely aware of the lifecycle and vintage quality effects of wine price appreciation, and to become buyers who take advantage of this lifecycle effect in foretelling aspects of the future. We want them to become buyers with higher standards for any forecasting tools they use.
It is for providing forecasts in fine wine price appreciation in auctions, for maximizing the buyers’ long-term returns, and for expanding our understanding of the underlying commonality among things that are completely unrelated on the surface.
Individual fine wine buyers—investors and collectors; investment funds that specialize in wine or using wine as a diversification asset class; and for auction houses to add a benchmarking tool to properly price their wines.
People who buy wines solely for drinking—although, many people who buy high-end wines end up not being able to drink them all, and have to sell some of them at a certain point. Retail wines. Cheaper, non-investment grade wines (these wines could still be highly enjoyable for drinking, but wouldn’t be good for forecasting or investing because they have much shorter life span).
Sisi Liang loves to find connections between seemingly unrelated ideas. Her curious mind has taken her to places from business strategy to entrepreneurship, from angel investing to marketing strategy, from metals mining equity research to regulatory stress test modeling in the largest financial institutions. She's a trailblazer and a ruckus maker.
Sisi holds a BA in English and Mathematics double major, with Honors, from Washington and Lee University, and an MS in Quantitative Finance. She is also an alumna from Seth Godin's altMBA program. Her passions for forecast modeling, the poetic and commodity elements in wine, yoga, along with her curiosity in the interconnectedness in diverse fields have drawn her to the collaboration of auctionforecast.com.