{"id":293,"date":"2009-07-04T11:41:19","date_gmt":"2009-07-04T19:41:19","guid":{"rendered":"https:\/\/bayesianinvestor.com\/blog\/index.php\/2009\/07\/04\/confusing-sp-index-earnings-numbers\/"},"modified":"2015-10-13T13:52:55","modified_gmt":"2015-10-13T21:52:55","slug":"confusing-sp-index-earnings-numbers","status":"publish","type":"post","link":"https:\/\/bayesianinvestor.com\/blog\/index.php\/2009\/07\/04\/confusing-sp-index-earnings-numbers\/","title":{"rendered":"Confusing S&P Index Earnings Numbers"},"content":{"rendered":"

I just noticed some confused arguments between Jeremy Siegel and Standard and Poors over how to aggregate earnings for companies in a stock index to produce a meaningful report of what the companies in the index earned.
\nSee here<\/a> and here<\/a>.<\/p>\n

Siegel provides an example involving percent changes in Exxon-Mobil and Jones Apparel. But that has a weak resemblance to what S&P is doing. A more accurate analogy to what S&P is doing would use changes to market cap rather than percent changes. If Jones Apparel declined in market cap by $10 billion, it would hurt the index just as badly as a $10 billion decline in Exxon-Mobil’s market cap. Looked at that way, S&P’s approach looks sensible.<\/p>\n

But since Jones Apparel has a market cap of less than $1 billion, the current bankruptcy laws make it far-fetched that Jones Apparel could lose more than $1 billion in market cap.<\/p>\n

If you’re using earnings as a proxy for the health of the economy, S&P’s method doesn’t create a problem – the bankruptcy laws affect who loses money, but the money is still lost. But for an investor, Siegel has a point which is half right.<\/p>\n

Siegel’s solution of weighting earnings by market cap may work well under any realistic conditions, but has no sensible theory behind it, and can fail badly under some far-fetched conditions. Imagine that Jones Apparel reports an unexpected one-time windfall of $1 trillion, which ought to raise the market cap of Jones Apparel by about $1 trillion. The way S&P computes S&P 500 earnings, an investor looking at S&P 500 earnings would see a strong hint that the value of the S&P 500 ought to rise by about $1 trillion. But under Siegel’s method, the initial effect on S&P 500 earnings would suggest a barely noticeable rise in the value of the S&P 500 of under $1 billion. Then at some point the Jones Apparel market cap would soar and the S&P 500 earnings would be recomputed with much different weights and investors would see a much different picture. So Siegel has proposed something which could result in a potentially large change in reported S&P 500 earnings without any change in the what shares someone who invests in the S&P 500 holds and without any changes in reported earnings.<\/p>\n

Morningstar has a method (PDF)<\/a> designed for evaluating portfolios that uses a harmonic weighted average and ignores companies with negative earnings. That has advantages, but the magnitude of losses provides some hints about how far a company is from profitability, so an ideal method should pay some attention to losses.<\/p>\n

Siegel mentions comments by Shiller that suggest Shiller has better (but possibly impractical) ideas. I doubt Shiller’s analysis provides as much support for Siegel’s argument as Siegel claims.<\/p>\n

Any sensible investor looks at a multi-year average of earnings along the lines suggested by Shiller, which minimizes the problems associated with faulty weighting of earnings.<\/p>\n","protected":false},"excerpt":{"rendered":"

I just noticed some confused arguments between Jeremy Siegel and Standard and Poors over how to aggregate earnings for companies in a stock index to produce a meaningful report of what the companies in the index earned. See here and here. Siegel provides an example involving percent changes in Exxon-Mobil and Jones Apparel. But that […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"footnotes":"","jetpack_publicize_message":"","jetpack_is_tweetstorm":false,"jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","enabled":false}}},"categories":[18],"tags":[145],"class_list":["post-293","post","type-post","status-publish","format-standard","hentry","category-investing","tag-index-investing"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p80O1l-4J","_links":{"self":[{"href":"https:\/\/bayesianinvestor.com\/blog\/index.php\/wp-json\/wp\/v2\/posts\/293","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bayesianinvestor.com\/blog\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bayesianinvestor.com\/blog\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bayesianinvestor.com\/blog\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/bayesianinvestor.com\/blog\/index.php\/wp-json\/wp\/v2\/comments?post=293"}],"version-history":[{"count":1,"href":"https:\/\/bayesianinvestor.com\/blog\/index.php\/wp-json\/wp\/v2\/posts\/293\/revisions"}],"predecessor-version":[{"id":639,"href":"https:\/\/bayesianinvestor.com\/blog\/index.php\/wp-json\/wp\/v2\/posts\/293\/revisions\/639"}],"wp:attachment":[{"href":"https:\/\/bayesianinvestor.com\/blog\/index.php\/wp-json\/wp\/v2\/media?parent=293"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bayesianinvestor.com\/blog\/index.php\/wp-json\/wp\/v2\/categories?post=293"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bayesianinvestor.com\/blog\/index.php\/wp-json\/wp\/v2\/tags?post=293"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}