"[S&P] recently shocked investors with an announcement that reported earnings for its S&P 500 Index for the fourth quarter of 2008 are forecast to be negative for the first time since such data were calculated in 1936. ... What this dismal news actually reflects in the bizarre way in which S&P (and most other index providers) calculate 'aggregate' earnings and P/E ratios for their indexes. Unlike their calculation of returns, S&P adds together, dollar for dollar, the large losses of a few firms without any regard to the market weight of the firm in the S&P 500. If they instead weight each firm's earnings by its relative market weight, identical to how they calculate returns on the S&P 500, the earnings picture becomes far brighter", Jeremy Siegel (JS) at the WSJ, 25 February 2009.
I agree with JS, a Wharton finance professor. S&P's failure to weight losses make no sense. This failure reveals a larger problem with almost all aggregate statistics. They are frequently useless for making policy decisions.
4 comments:
I wonder what you think of this article that argues Siegel is wrong?
If calculating weighted earnings is the appropriate method, why did JS fail to go back re-calculate earnings from the last 20, 50, or 75 years?
That way we could compare the weighted earnings P/E multiple with different eras. Comparing P/E multiples with different measures for earnings is comparing apples to oranges.
His piece was lazy at best and misleading at worst.
McGraw-Hill >>> totally in the tank ... time for a big broom...
Doug:
S&P made this argument in a letter to the WSJ. I reject it. The concept of "aggregated earnings" is fallacious, it's like the concept of GDP, or CPI. Any statistic you use will have assumptions. I think JS's calculation makes more sense than S&P's.
Post a Comment