Oct
19
Comparing Two Mountains, from Victor Niederhoffer
October 19, 2011 |

Dear Steve,
Hope you are well. A statistical problem has come up. The idea of comparing two charts, in this case Netflix and Green Mountain Coffee. I wonder if statisticians have a way of handling this problem. I've seen some books on statistics on place but never this problem of comparing two mountains as to their similarities. I wonder if you could refer me to the proper area. I asked a geologist whether they have a way, and apparently they take into consideration many physical factors. I am going to enclose the chart separately.
Stephen Stigler replies:
Hi Vic,
Any statistical model would have to have a dynamical model for the mountain. It could be an empirical model, like if you had a sequence of mountains, as with predicting sunspot cycles or tides. But it would either need a number of examples (not just two) or a very strong math hypothesis. You might be able to generate a set of examples if you focus on a telling feature, like one day descent of x% after trading within + or - y% for z days.
Hope all is well with you & yours!
Best,
Steve
Pitt Maner comments:
A geomorphologist would have to consider many factors in trying to interpret how the hills and valleys were formed, the timing of such, and what they might look like in the future. Erosion is a key but it can occur at differing rates within a range of timescales based on rainfall, climate, vegetation, composition and homogeniety of the rocks, fractures, landslides, river sediment carrying capacities and as noted in the article below—Slope . There are instances, however, where the rate of erosion at the surface is offset by the continuing forces of uplift (denudational isostatic rebound for word lovers).
There are rules of thumb— with the higher slopes and steep mountain ridges eroding quite quickly —E. Himalayas at a whopping 2 to 3 mm/yr, as example. But those erosional rates will change over time to meet new equilibrium requiremen ts.
"I don't think we'll ever find the single smoking gun of erosion," says Portenga, "the natural world is so complex and there are so many factors that contribute to how landscapes change over time. But as this method develops, we will have a better sense of what variables are important — and which are not — in this erosion story."
For example, it has been a truism of geology for decades that rainfall is the biggest driver of erosion. Semi-arid landscapes with little vegetation and occasional major storms were understood to have the greatest rates of erosion. But this study challenges that idea. "It turns out that the greatest control on erosion is not mean annual precipitation," says Bierman. Instead, look at slope.
"People had always thought slope was important," Beirman says, "but these data show that slope is really important."
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When trying to extract significant patterns from unrelated charts I often use moment matching techniques. This will normalise the timeseries in order for them to be more accurately compared. For instance a simple approach would be to take the log of both charts and then scale both by their standard deviation.
Doesn’t Thoreau discuss this question in the section of Walden where he investigates the depth of lakes in comparison to the topography of the surrounding land? Obviously a lake would be the inverse of a mountain.
You might look at Mahalanobis distance, a stat tool designed to measure difference in skull dimensions. Here is a worked example.
http://help.lockergnome.com/office/excel-calculate-Mahalanobis-distance–ftopict950835.html
regards…Steve
You could create a ratio chart that combines the two and then apply statistical analysis to that. What you often find is that one of the two charts dominates the other in the composite, appearing little changed. Follow this link for copious examples:
http://stockcharts.com/def/servlet/Favorites.CServlet?obj=ID3027592
Well what do you know Vic, youre in luck! I’ve just done a brief analysis of the ratio chart for these two and according to this there is a high probability of the ratio more than doubling over the next year or so in Netflix’s favour. I might even put this one on myself tomorrow!
Proper area to be referred to is the volcano called David Einhorn.
A great investor and a great guy.
Well that’s annoying. The pair is up nearly ten percent this morning. I’m going back to bed.