Horolonomics

This will be one of my more brief posts on the state of the watch market. The punchline is that, when you review charts anywhere, always make sure to check if the publisher has included the origin in the chart. The origin is the point where both variables presented in the chart take on the value zero (the really important thing is that the origin for the vertical value is included).

Let me illustrate why this is important. In the first image presented below, I present data from a watch pricing analytics company. The data represents an "index" of Rolex asking prices on the preowned market. I think "index" is probably not a great way to describe this data, it really represents an average of some sort. In fact, I'm not really fond of this type of index for other reasons. A stock price index, for example, represents averaging of homogenous assets. It's true that stocks come from heterogeneous industries, but they are all subject to largely identical reporting and regulatory requirements. Stocks also all operate the same way in terms of dividends, etc. Watches are very heterogeneous, so averaging those is a bit more like averaging an apple and an orange. It just doesn't make sense.

Anyway, I used a helpful tool to recreate the data that the analytics organization publishes in graphs on Instagram. As as far as I know, they don't provide the raw data. I'll note that my data is an approximation of the original data because the tool I used to recreate the data isn't perfect.

The graph published by the analytics company is designed with a vertical axis starting at a value of $12,000. In other words, the analytics company omits the origin from their graph. The resulting line reminds me of that mountain Richard Dreyfuss' character was obsessed with in the movie Close Encounters of the Third Kind.

I've included a picture here for reference, the actual formation is called Devils Tower and it is in Wyoming. The end impression is that Rolex prices skyrocketed quickly, mostly during the pandemic, and now they are collapsing.

But what happens when we include the origin in the graph? Visually, we get a very different impression and it isn't nearly as dramatic. I present that image here.

This graph is also more accurate. We see a slow increase in asking prices and then an almost equally slow decrease. If we use a ruler to measure the distances traced by the line, the first graph makes it appear that the Rolex index increased by over 600% in less than a year. This is absolutely not what happened to the index. In reality, the index increased by 29%.

This is not an isolated distortion from the watch industry analytics company in question. I also recovered the data from a graph they published showing the asking price for the Tudor Black Bay GMT. Their published figure, which I recreate here, leaves out the origin and seems to suggest that the Black Bay has recently shown a fairly precipitous drop in its value.

When you include the origin, the decrease looks far more modest, which is the true result when it comes to the reported asking price. If we believe the analytics company, the Black Bay GMT asking price decreased by roughly 10%. This is still a noteworthy decrease in value, but dollarwise it amounts to about $475. It is good to know this is happening, but it isn't really precipitous.

According to Mark Twain, British prime minister Benjamin Disraeli once said, "There are three kinds of lies: lies, damned lies, and statistics." This sentiment has, unfortunately, resonated with many. Really, though, it is not statistics that lie. Instead, when proper practice is not followed in data analysis and inference, the result is often misleading. The good news is that I've also seen signs that watch data analytics companies are responsive to feedback and trying to do better. Let's hope that trend continues.

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My book on the history of Rolex marketing is now available on Amazon! It debuted as the #1 New Release in its category. You can find it here.