Download complete issue - IndexUniverse.com

Despite high t-statistics, statistical and economic significance,
and an R 2 of 99.99 percent, the discovery most often doesn’t
work going forward. The cause is simple: Try enough models,
equations and ideas, and a few are certain to look good. Even
when data mining creates fool’s gold instead of the real thing,
some of these do become filings for new ETFs.
The last challenge is “success.” Once word gets around
that some new strategy works, everyone rushes in.
Suppose you designed an index of technology stocks that
pay dividends to combine the stability of dividend payers
with growth and it beats the market quite handsomely.
Other tech-dividend indexes appear, hedge funds buy
up high-dividend tech stocks and CNBC runs a hot idea
story, while IndexUniverse lists all the newly registered
ETFs targeting the area. Prices of dividend-paying technology
stocks would be bid up, and performance going
forward would collapse amid falling dividend yields for
the group. There was no market rotation and the idea
wasn’t data-mined, yet success breeds its own failure.
A recent research paper by McLean and Pontiff 3 examines
the loss in stock predictability and strategy return caused by
research publication. Their study explores 82 investment
ideas going back over 20 years, testing losses that might be
blamed on data mining as well as crowds. The impact of data
mining and statistical analysis is mixed and not statistically
significant. The average effect of popularity through publication
reduces the expected returns after publication by 35
percent of the returns before publication.
Investment strategies, like many other investment
ideas, are often ephemeral. Moreover, the attractiveness
of strategy ETFs differs from the attractions of investing
in an ETF that tracks a broad-based market index like
the S&P 500 or a total market index. An investor owning
a strategy ETF hopes it is a good idea that will last long
enough; the investors who choose an ETF tracking the
S&P 500 or a total market index believe in low costs and
participating in the stock market.
Endnotes
1
Fama, Eugene F. and French, Kenneth R. (1993). “Common Risk Factors in the Returns on Stocks and Bonds,” Journal of Financial Economics 33 (1): 3–56
2
Carhart, Mark M. (1997). “On Persistence in Mutual Fund Performance,” Journal of Finance 52 (1): 57–82
3
McLean, R. David and Pontiff, Jeffrey E. “Does Academic Research Destroy Stock Return Predictability?” (Oct. 3, 2012). AFFI/EUROFIDAI, Paris, December 2012 Finance
Meetings Paper. Available at SSRN: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2156623
Faber continued from page 21
post for both opportunities arising from negative geopolitical
events as well as a sanity check against bubbling stock markets.
Comparing global equity markets on a relative basis allows the
portfolio manager to create portfolios of cheap stocks markets,
while avoiding or even shorting expensive markets.
Appendix: Other Valuation Models
Samuel Lee has a great article titled “The Hedgehog’s
Error” 9 on Morningstar’s website that sorts global
countries based on value (price/book) using the
French/Fama database. Not surprisingly, he finds that
sorting on value works well.
We utilize the database to sort the countries (12 in
1975 and rising to 20 by 1991) based on various measure
of value. In Figure 12, we demonstrate the results of
sorting the countries on a yearly basis and choosing the
cheapest x percent of the universe (from 10 to 33 percent).
Results are U.S. dollar based, nominal.
Endnotes
1 Shiller maintains a website with an Excel download that includes historical data with formulas illustrating how to construct his 10-year CAPE: http://www.econ.yale.
edu/~shiller/data.htm. For a step-by-step guide, Wes Gray at Turnkey Analyst has a good post that walks through the steps necessary to construct the metric: http://turnkeyanalyst.com/2011/10/the-shiller-pe-ratio/
2 “Estimating Future Stock Market Returns” by Adam Butler and Mike Philbrick tackles the issue of different measurement periods from one to 30 years (as well as other
valuation models).
3 John Hussman has a few good articles on this topic: “Estimating the Long-Term Returns on Stocks” and “The Likely Range of Market Returns in the Coming Decade”;
Joachim Klement also recently published the paper “Does the Shiller-PE Work in Emerging Markets?” that performs a similar analysis.
4 Rob Arnott of Research Affiliates touches on this important topic in his white paper “King of the Mountain” (http://www.researchaffiliates.com/Our%20Ideas/Insights/
Fundamentals/Pages/F_2011_Sept_King_of_the_Mountain.aspx). Two other books speak of CAPEs and inflation/deflation levels. The first is “Unexpected Returns:
Understanding Secular Stock Market Cycles” by Ed Easterling, and John Mauldin’s “Bull’s Eye Investing: Targeting Real Returns in a Smoke and Mirrors Market.”
5 One such resource is Russell Napier, who authored Anatomy of the Bear: Lessons From Wall Street’s Four Great Bottoms, and who discusses global CAPEs in a video here:
http://video.ft.com/v/946244201001/Long-View-Historian-sees-S-P-fall-to-400 . We also found two great recently published papers: “Does the Shiller-PE Work in Emerging
Markets?” by Joachim Klement (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2088140), and “Value Matters: Predictability of Stock Index Returns” by Angelini,
Bormetti, Marmi and Nardini (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2031406).
6 http://www.tweedy.com/research/papers_speeches.php
7 http://www.iijournals.com/doi/abs/10.3905/jpm.1991.409327
8 http://www.mebanefaber.com/2011/11/17/sorting-countries-by-dividend-yield-2/
9 http://etf.morningstar.com/BlogArticle.aspx?postid=3281399
www.journalofindexes.com March / April 2013 41