Skip to Content
Commentary

Let’s Not All Become Fundamental Indexers Just Yet

The air is coming out of the argument that fundamental indexing is a revolutionary innovation.

Fundamental indexing has been touted by its proponents as a revolutionary innovation in the field of passive investing. Weighting stocks by market capitalization, they say, inevitably causes a drag on performance, owing to the market's inherent mispricing of stocks. Their claims are based on a paradigm of asset pricing called the "noisy market hypothesis," which argues that stocks' market prices stray from their fair values in a random fashion, and that because they do, market-cap-weighted portfolios--which inherently favor stocks with rising prices--are skewed toward overvalued stocks. (For our purposes, consider the definition of "fair value" to mean a number that would represent the "true" or intrinsic value of a stock that would perfectly describe its worth.) Hence, the reasoning goes, a portfolio with weightings that are derived independently of market value, such as a fundamental weighted index, will outperform its market-cap-weighted counterpart.

The fundamental indexers' biggest criticism against cap-weighted indexes stands on flimsy ground, though. Andr� Perold of Harvard Business School demonstrated in a paper in Financial Analysts Journal (November/December 2007), for example, that even if market prices deviate from fair values, it does not automatically follow that cap-weighted indexes load up on overvalued stocks. That is because there is simply no reason to conclude at the outset that a stock that commands a high valuation is overpriced. It is just as likely that the "expensive" stock deserves its premium because of its superior growth prospects, or that a "cheap" stock's fair value could be even lower than its market price. Proponents of fundamental indexing make their case against market-cap weighting by implicitly (and perhaps unknowingly) assuming that a market observer does know a stock's fair value, thereby contradicting one of their own assumptions.