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Small-Cap Returns vs. Large-Cap Returns Gunner's Note: Today you will be reading the wisdom of Satya Dev Pradhuman. Pradhuman is the Director of Small-Cap Research at Merrill Lynch and was ranked the No.1 small company analyst for the year 2000 by Institutional Investor Magazine. He has also served as a quantitative analyst focusing on small-cap and mid-cap equity and equity derivatives at Merrill Lynch, and has held positions in research at E.F. Hutton and Lehman Brothers. Today, Pradhuman will discuss historical small-cap returns -- do they really consistently beat the big stocks? Read on to find out... You can also check out Pradhuman's entire book here.
Some of the more compelling factors that have been cited as arguments against the existence of a size premium include: measurement error, inferior profitability comparisons, and the erratic nature of spikes in small-cap returns. Another popular but qualitative argument holds that small companies are inferior to large companies in terms of product and services, management depth, balance sheet, and similar factors. Other relevant issues investors must reconcile, before taking on a small-cap position, relate to the illiquidity of small stocks, which interferes with the ability to invest quickly. ******************************* Three Events Will Wipe Out Millions of American Investors by December 31, 2006 One of the world's most famous market analysts just revealed his two favorite wealth fortress investments for protecting his -- and your -- money... Read on to find out how you can get both those recommendations... ******************************* Flaws in Performance Data Historical data are always subject to frailties of human error. By extension, a measured effect is only as good as the database from which it is drawn. One way in which critics debunk the size premium is to claim that the data are flawed. They argue that databases tracking security prices as far back as the 1920s must contain some degree of error. Yet the services that provide such pricing data claim that they accurately capture all events that have been transacted in the equity markets. Factors such as survival bias, or databases that do not account for companies that have gone bankrupt or not "survived," or other data hitches such as flawed data entry, certainly leave open the possibility that compelling small-cap returns have been measured less than perfectly. Because of the robust sample size, however, it becomes difficult to argue that errors in the data, which are clearly drawn at random, consistently bias the smaller stock returns. The sizable universe of companies makes it more likely that the measured returns over the long term are closer to the realized returns. Another issue that has surfaced relates to the definition of small stocks. According to this argument, as laid out by Bill Fouse, small stocks have generated excess returns in the past because large companies were accidentally included in the sample of small companies. In the initial studies on size, size groups were reconstituted over five-year periods, which meant the sample size of the small-cap index remained unchanged for five years. As a result, some of the more successful small-cap ideas could have migrated to the large-cap universe but were mistakenly credited to the small-cap universe. Although this argument has some merit, the lengthy five-year holding period would also be likely to cover collapsing secondary stocks that small-cap investors would be unlikely to hold. These stocks, which would be incorrectly credited to the small-cap index, would detract from small-cap performance measures. Accordingly, it might be more appropriate to assign weakening issues to a group outside the small-cap universe. For instance, faltering secondary stocks that are losing market value might be more appropriately assigned to a segment of microcap stocks. Even though the upward migration of shares can produce an upward bias in small-cap benchmarks, downward migrations can likewise create a downward bias in returns. Although investors need to examine all benchmark results with a critical eye, a migration bias may be less relevant than other issues. Because the markets are fluid, there are always likely to be migration effects, whether upward or downward. Over the long term, these effects are likely to cancel each other out and have little impact on any potential return bias. ******************************* Small-Cap Value Plays Can Stomp the Market By 30% Look no further than Small-Cap Strategy Report for all of your small-cap value plays. Learn how James Boric can show you how you could bag 30% gains consistently, year after year, with some of the best small-caps on the market... ******************************* To determine the significance of the migration effect, the holding periods of a small-cap benchmark could be shortened-for example, from five years to four years. The benchmark results could then be analyzed to determine whether they are significantly different when the rebalancing frequency is cut down to three years, two years, or one year. In one simulation, several identical small-cap portfolios were created to vary only by the length of the holding periods. The portfolio results were nearly identical. Based on this study, there seems to be little evidence that the performance of a small-stock index calculated over a five-year holding period varies greatly from that of an index with a four-year holding period. In fact, the results appear to be fairly uniform across holding periods. The significant number of companies that comprise the small-cap market accounts for the stark similarities among small-cap benchmarks reconstituted across holding periods. In other words, once a benchmark is constructed with several hundred companies, as most small-cap benchmarks are, the averages are more likely to converge, reflecting quite similar results. Although index turnover can appear significant, the net performance results do not necessarily vary because of the tendency for a broad core of small-cap names to remain in an index over lengthy periods. Suspect Small-Cap Cycles The size premium has also been questioned in relation to performance cycles. In an argument posed by Jeremy Siegel, a Wharton School professor and noted author, the degree to which small stocks outperformed large stocks in the 1970s was unusually strong and possibly suspect. According to this thinking, if the 1974-83 period were removed from the long-run performance analysis, the remaining data would yield a large-cap premium. That ten-year-period appears to have represented a bonanza for small-stock investing. Figure 6.2 presents the performance of the Ibbotson Small Stocks Index versus that of the Standard & Poor's 500. Note that the long-run data from 1926 to 1999 indicate that a dollar invested in small-cap stocks would be worth approximately $6,545, compared to approximately $2,842 for large stocks over the same time frame. If the years 1975 through 1984 were removed, however, large caps would have generated $2,004 and outpaced small stocks, which would have gained only $1,202 over this period.3 The period in question represents an unusual time, one of oil shocks and devastating inflation. Although it might seem reasonable to remove an anomalous subset of returns, this analysis neglects the possibility that unusual events have occurred in practically every decade. If the 1975-84 period were removed from the analysis, this elimination would also erase a bear market for large caps that occurred during the first half of this time frame. This approach inadvertently assumes that investors can adeptly time a large-cap bear market. It turns out that besides being a period in which small-cap returns were stellar, the 1970s also marked a bear market for large-cap returns.
Likewise, most of the subsequent period from 1984 to 1991 should be removed from analysis because large stocks exhibited unusually high returns during those years. In this time of severe disinflation long-term government bond yields fell from the mid-teens to roughly 5 percent over a 10-year period. Investors are unlikely to face such a significant period of disinflation within the foreseeable future. If the 1984-91 period were removed from the analysis, the long-run performance results, not surprisingly, would show that small stocks outperformed large. In fact, as presented in Figure 6.2, the margin of small-cap outperformance would be even greater than that of the long-run time series data. As this discussion demonstrates, selective measurements can cloud any analysis, including an analysis of the small-cap premium. Excerpted from Small-Cap Dynamics (c)2000 by Satya Dev Pradhuman. Reprinted by arrangement with Bloomberg Press. Urgent Legal Update: You could greatly improve your odds of seeing big gains in a bear market by watching what company insiders are buying. Read this special report to see how you could capitalize on these new loopholes today by using a system designed to show you gains of 68%, 85%, 133% and even 768% in just six months. |
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Satya Dev Pradhuman is the Director of Small-Cap Research at Merrill Lynch and was ranked the #1 small company analyst for the year 2000 by Institutional Investor Magazine. He has also served as a quantitative analyst focusing on small-cap and midcap equity and equity derivatives at Merrill Lynch, and has held positions in research at E.F. Hutton and Lehman Brothers. Ranked in the top echelon of small-cap analysts by Institutional Investor and Reuters, Pradhuman is often sought out and has been cited in leading publications such as The New York Times, The Wall Street Journal, Investor’s Business Daily, and Business Week, and has appeared on CNN, CNBC, and The Nightly Business Report. |
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