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PART One
Equities
EQUITY STYLES AS ASSET CLASSES
Although equities are frequently referred to as an asset class, they are in practice modeled as several distinct subasset classes, each represented by a different index. In the United States, investors often divide domestic equities along two dimensions: market capitalization and value/growth orientations. This practice is based on a large body of academic research that shows that, over the long run, small-cap stocks outperform large-cap stocks and value-oriented stocks outperform growth-oriented stocks.
In the 1990s, Morningstar popularized the concept of style investing with its now ubiquitous nine-square equity Style Box, as shown in Figure 1.1.
The popularity of equity style investing led all of the major equity index providers to create families of style indexes along the lines of a style grid. Morningstar launched its own family of style indexes in 2002. The creation of these families of indexes and the growth of style-specific actively managed funds made it fairly straightforward to introduce equity-style asset classes into asset allocation models. Today in the United States, it is common to see specific allocations to U.S. large-cap value stocks, U.S. large-cap growth stocks, U.S. small-cap value stocks, and so on, in an asset mix.
Unfortunately, using equity style groups as asset classes is not as straightforward as it first appears to be. Each index provider uses its own methodology to decide how to distribute stocks among its family of style indexes. Therefore, the choice of index provider has a significant impact on the capital market assumptions (expected returns, standard deviations, and correlations) that go into an asset allocation model. This is the reason that I chose Kaplan, Phillips, and Pascavis (2009) as the first chapter for this book. In this chapter, we compare the statistical properties of five families of U.S. equity style indexes. (Naturally, the results favor the Morningstar index family!)
Although there is research that supports the style approach to classifying equities in international markets, and index providers have introduced equity style indexes into these markets, the concept has not gained much traction outside of the United States. In Chapter 2 (Kaplan 2010), I make a case for style investing for European markets, using the Morningstar European equity style indexes to illustrate my points.
FLAWS OF FUNDAMENTAL INDEXATION
Until the publication of Arnott, Hsu, and Moore (2005), there was little question that the proper way to construct an asset class index, particularly an equity class, was to weight the index constituents in proportion to their market values. Arnott and his co-authors criticized this practice and argued that investors would be better served by indexes that are weighted on fundamental measures of size, such as revenues, earnings, and book value, rather than market values.
As I discuss in Chapter 3 (Kaplan 2008), several researchers criticize fundamental indexation on both theoretical and empirical grounds. They show that the theoretical arguments for fundamental indexation are flawed and that the empirical results are largely the result of style bias inherent in Arnott's weighting method, which systematically overweights value stocks and underweights growth stocks relative to market-value weights. In Chapter 3, I critique fundamental indexation and argue in favor of a hybrid approach that uses weighting techniques that combine market and fundamental values. After the publication of my article, Arnott and I held a lively debate moderated by Larry Siegel. Chapter 4 (Arnott, Kaplan, and Siegel 2009) is an edited transcript of our debate.
In Chapter 5 (Arya and Kaplan 2006b), Sanjay Arya and I propose another hybrid weighting technique, called collared weighting. With collared weighting, most of the portfolio is weighted by market value; only those stocks with outlying valuation ratios (both high and low) are subject to a fundamental weighting. This dynamic changes, however, during periods of extreme valuation ratios (such as during the tech bubble of the late 1990s). During these periods, most of the portfolio is fundamentally weighted.
Some index providers design equity indexes to represent very specific strategies, such as dividend income. Instead of using market-value weightings, dividend indexes base their weights on income objectives. In Chapter 6 (Arya and Kaplan 2006a), we argue that the most suitable weighting method for a dividend-oriented index is fundamental weighting based on the total dividends available to investors provided by each index constituent.
ESTIMATION ISSUES
The last three chapters of this section deal with estimation issues that arise in equity-asset-class modeling. Chapter 7 (Kaplan 2003) addresses the asset-allocation issues of using actively managed equity funds in a portfolio of style-specific indexes. The direct way of doing this is to examine each fund's equity holdings. However, this holdings-based approach requires a large dataset of fund portfolios and the characteristics of individual stocks. Sharpe (1992) proposed an alternative method, known as returns-based style analysis. In returns-based style analysis, the weights of the various indexes are estimated by what is essentially a time series regression of the returns of the funds versus the returns of the indexes. This approach avoids the need for knowledge of the fund's holdings or data on the fund's constituents. By using Morningstar's database on fund holdings and individual stocks, I was able to conduct a thorough study to compare the results of the two methods.
Chapter 8 (Ibbotson, Kaplan, and Peterson 1997) addresses a statistical issue that arises when estimating the behavior of the returns of small-cap stocks; namely, the expected return premium and the systematic risk of small-cap stocks. Frictions in the markets for small-cap stocks induce correlation between the returns of small-cap stocks and the lagged returns of large-cap stocks. This results in investors overestimating small-cap premiums and underestimating the systematic risks (betas) of small-cap stocks relative to large-cap stocks. Thus, investors might be tempted to overweight small-cap stocks in their asset-allocation models.
In Part III of this book, I include a chapter on hedge funds that raises a similar issue: the overestimation of alphas and the underestimation of ...
