A History Lesson for Wall Street Resesarchers
Wall Street researchers are terrible at history!
The worst examples occur when they make hasty and sloppy comparisons. A current example is finding an old chart from one time period and lining it up with current trading. This is a blatant form of data dredging, but some find it to be compelling reading. (Here is a typical example from The Big Picture, but please note that the inference is not endorsed by Barry Ritholtz).
The problem is that everyone who follows the markets looks at charts on a daily basis. Even the non-technicians claim some basic skill. Show us a chart, and we all have an opinion.
At "A Dash" we have tried to point out that the data we really need for good research is rarely available. This forces us to reach back in time — often way back — to get enough data to review more than one or two market cycles.
We seriously doubt that market data from the Taft Administration has much relevance for today. In fact, we question any information from the era before stock options and futures, and maybe before the invention of the personal computer.
There are some market characteristics that endure over time. Sure, everyone should read and enjoy
It is a question that must be asked repeatedly, every time someone presents data that reaches back more than twenty-five or thirty years ago.
It helps to be fully grounded and in touch with what people really believed in the era you are using. If one wants to use data from 1900, why not see what people were thinking then?
There is a wonderful list of predictions for the year 2000 made in 1900 by J. Effreth Watkins in The Ladies Home Journal. It is a rather long list, but very entertaining. Each of us will find certain favorite observations. (Thanks to Tyler Cowen at Marginal Revolution, where we spotted this).
Our own overall conclusion is that Watkins was very good at extrapolating technology known at the time — the rise of automobiles and improvements in medicine (including diagnosis), and the anticipation of FedEx (with a lot of pneumatic tubes).
He was less successful at quantification. The U.S. was to have 350 to 500 million people. We would have a life expectancy of 50 instead of 35 in those days) and everyone would be able to walk ten miles a day or be thought a "weakling."
He was predictably weak on technology that was just appearing like airplanes, which he thought would never replace the automobile for passengers and freight.
Most mysterious are the predictions that must have seemed plausible, but went terribly wrong? Why DO we still have all of these mosquitoes?
The lesson for those doing market research: Take care to make sure that historical comparisons are well-researched and appropriate.
The lesson for our fellow consumers of Wall Street research: Let the warning bells go off when there is a chart or analogy including a time period from long ago.
Its clear that both individually as well as a group, Humans are bad at predicting the future.
Its especially important for investors to understand this. See:
The Folly of Forecasting
http://www.thestreet.com/_tscana/comment/barryritholtz/10226887.html
for specific details.
Reading financial history as opposed to looking for meaning in charts is useful although I don’t think these historians who attempt to make projections like David Hackett-Fisher and Niall Fergusson are likely to be prescient eventhough they write well and are fine historians.
What is your opinion on the “Siegel’s constant” of earnings yields between 6% and 7% or mean-reversion of earnings yields which has been observed over more than hundred years and on which much of the bears’ arguments such as those of Grantham or Hussman is based? Grantham likes to say that if this doesn’t hold, “capitalism is broken”. Further, based on trailing normalized earnings, the market is fairly valued against corporate bonds. I suppose this is where the disagreement between the inside (Fed model) and outside (normalized PE) comes in. Your thoughts on comparing these two long-term models?
Thanks for the comments and questions.
RB’s raise points of current interest — a topic on my “list.” I need a full article to do it justice.
Meanwhile, you can search the site for Hussman, where I have prior comments. Siegel recently stated that stocks were undervalued on an earnings/interest rate basis. The mean reversion profit margin argument has not been carefully analyzed — how, when, why, what effect on final earnings. That’s a project.
Stay tuned —
Jeff
Yes, but Siegel also said that stocks were not cheap on an absolute basis. I presume he was comparing with a historic earnings yield. This is the link I could find:
http://tinyurl.com/2b7ccw
Did you see David of UTX on CNBC a few days ago talking about how productivity was always rising? Seems like margins in aggregate can be competed away but that is because the better mousetraps get more mice. Mean reversion is moving target so how far back to go?
RB –
Thanks for the pointer. I am going from a “knowledge@wharton” podcast from a few weeks ago. (Yes, that is the kind of thing I sometimes listen to when walking the dog!) Experts like Prof. Siegel are so often cited and context is important.
Jeff
My take on “Siegel’s constant” of earnings yields is that monetary policy is completely different today than it was in the past, and part of the corporate earnings (esp. re: financials) is due to Cantillon effects of monetary policy decisions. Any mean-reversion of earnings model that fails to take into account the changes in monetary policy (and monetary flow and growth) is inherently flawed, as the “mean” of one time period doesn’t necessarily have the same “meaning” in another time period.
I think my favorite is “Prediction #27: Few drugs will be swallowed or taken into the stomach unless needed for the direct treatment of that organ itself.” Lots of pills taken into the stomach for “organ” treatment nowadays.
Great post. Equities don’t trade like they did in 1990, much less like they did in 1890.
While the market may be very different over history as defined by our age, the earnings yield history runs not only from 1980-present but also from 1801-1980. What might those in a post-agricultural economy have been saying? It’s worth a thought.