Birinyi Associates Topical Study #40: What Do Stocks Really Return?
The
stock market's comeback in 2009 has probably reinforced the old adage,
"the market always comes back".
That view has received considerable currency from Jeremy Siegel's book,
Stocks for The Long Run (SLR), which details the performance of the
Recent efforts by us and others have at least called that into question (especially when adjusted for risk), while a WSJ column questioned the availability and veracity of data.
We undertook an analysis of Jeremy Siegel's Stocks for the Long Run. The Financial Times recently commented that this work was "influential in persuading asset allocators to put a big weighting toward equities." We found Siegel’s effort to be lacking in data, details, and methodology in addition to other shortcomings. In fact relatively little of the book deals with the title. It may well be, as Barron's has suggested, useful for the 'amateur' investor as it covers some basic topics but with little depth.
We are not enthusiastic regarding this book and its conclusions for reasons which include:
- We find little evidence that the author undertook basic, roll up your sleeves research. The book depends heavily on a 1989 study for the NBER by William Schwert which in turn was a "cobbling" together of a number of other prior studies varying greatly in terms of composition and methodology.
- Earlier researchers suggested that pre-1871 data was not available. Siegel defended his publication by noting that other, more recent, analysts have found the historic data to be available; however, one study's data was not as complete as suggested, and in one instance had a huge error in data collection.
- Indexes and measures which overlapped those used by Siegel often have differed substantially from those Siegel used.
- The data used in SLR showed an average annual price gain of 2.9% for the 200+ years; his total return result, 8.3%, was achieved by an aggressive dividend assumption, in excess of that suggested by other analysts.
Investors should be aware that there are issues in index collection and compilation. We have found instances where DJIA data is incorrect by a significant factor. And S&P, not only historically but as recent as 2004, has had issues with which we disagree.
Our
experience is that academics, like other analysts, are prone to what we term
"a propensity to financial bias;" they should be more rigorous,
detailed, and searching; rather than accepting a given and contending that it
is a truth.
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