Fundamental Indexation (FI) creates a broad-based market portfolio, like traditional market capitalisation weighted indices, but weights stocks according to a firm’s economic size, not stock price. Using the Dow Jones Industrial Average index, we find evidence of the ability of FI to time the market during the technology boom and bust (August 1998 to August 2002). However, in the global financial crisis, FI underperforms against a market capital-weighted index, thereby undermining much of its claim to success. Overall, the superior outperformance of FI is clearly linked to loadings on the Fama and French book-to-market and size factors. We find that equal-weighted indexation, which represents a traditional form of non-market capitalisation, performs well and appears to be successful at timing the market, transaction costs aside.*
Arguably, market capitalisation-weighted indexes (MCWIs) are sub-optimal since, by construction, they must overweight overvalued shares and underweight undervalued shares. However, this tendency can be overcome by fundamental indexation (FI), where the weights are assigned to stocks on the basis of non-market measures of a firm’s size: book value, revenue, cash flow, dividend, sales, and even employee numbers. Some studies have claimed that such a preferred weighting approach allows assets to be proportioned to reflect more accurately the true ‘economic’ weightings of portfolio firms, and that FI is thereby immune to pricing ‘bubbles’.
A number of authors confirm that FI outperforms when benchmarked against the traditional capital asset pricing model (CAPM), but does not outperform against the Fama–French (1993, 1996) three-factor model, which has additional risk premiums for high book-to-equity and small-firm stocks. Since FI indexes, by construction, display a bias toward higher book-to-market equity and small-firm stocks, it is possible to interpret FI’s reported performances as a repackaging of known ‘value’ (high book-to-market equity) and ‘small firm size’ effects.
This paper seeks to determine whether the outperformance of FI can be separated from that of exposure to the Fama–French factors. Following the theoretical underpinnings of FI as a strategy of avoiding bubbles in individual prices, FI should benefit from those periods when market bubbles are corrected, as well as from individual stock price corrections. Thus, we investigate whether FI is capable of timing the market at the level of both ongoing market fluctuations and major market crises.
For this purpose, we obtain the stocks of the Dow Jones Industrial Average index (DJIA), which provide 48 years of reliable stock market data over cycles that include the ‘Nifty Fifty’ era of the 1970s, the 1987 stock market crash, the tech boom and bust of 2000, and the recent global financial crisis of 2008. The DJIA stocks have high liquidity, volume, and depth, and consequently low noise and high market efficiency compared with stocks of smaller firms. These features imply a challenging environment for FI, since the noise effect that FI seeks to manipulate is suppressed in these stocks.
In the context of the DJIA, we find evidence of the ability of FI to time the market in a single period of crisis, which is the technology boom and bust. However, FI underperformed against an MCWI in the global financial crisis, which undermines a good deal of FI’s claim to success. It appears, therefore, that the superior outperformance of FI remains inextricably linked to loadings on the Fama–French book-to-market and size factors. An interesting question then becomes whether the noise model of FI can be interpreted as a theoretical explanation for the observed book-to-market effect. We see that this approach opens up exciting possibilities for a theoretical underpinning of the Fama–French model in a framework of share price corrections.
Interestingly, we find that equal-weighted indexation, which represents a simple form of non-market capitalisation indexing, is highly successful (ignoring transaction costs). From a practical perspective, the challenge for FI is to demonstrate that its strategy represents an optimal compromise between the benefits of an equally weighted portfolio and those of following a market index.
* This research was also supported by an Australian Research Council Linkage Grant.
This Working Paper was produced by the CSIRO-Monash Superannuation Research Cluster a collaboration between the CSIRO and Monash University, the University of Western Australia, Griffith University and the University of Warwick in the United Kingdom. In addition, the Cluster engages on an ongoing basis with a range of industry supporters, government agencies and industry peak bodies who assist in providing guidance and feedback to researchers, providing data, and in disseminating outcomes. The purpose of the Super Research Cluster is to examine issues pertaining to the future of Australia’s superannuation and retirement systems.