In 1973, Burton Malkiel delivered what would become a seminal tome on the virtues of passive investing. Entitled A Random Walk Down Wall Street, Malkiel’s book, now in its eighth edition, takes on all forms of active investing, from rigorous fundamental analysis to the outlandish idea of basing stock movements on the results of the latest Super Bowl. Malkiel’s conclusion, consistent with the passive-only mantra, is that when the added costs of active investing are factored in, passive investing will regularly beat active investing over the long run.
Again, average is not a dirty word to the purveyors of passive investing. But these advocates also understand that the term “random walk” rings foul in the ears of active investors. This is why Malkiel used it in his title, a jab at the active managers who believe there are predictable (nonrandom) patterns in the market data that regularly can be exploited for profit. Writes Malkiel, “On Wall Street, the term ‘random walk’ is an obscenity. It is an epithet coined by the academic world and hurled insultingly at the professional soothsayers. Taken to its logical extreme, it means that a blindfolded monkey throwing darts at a newspaper’s financial pages could select a portfolio that would do just as well as one carefully selected by the experts.”[1]
In a strict sense, this analogy will hold up: Blind dart-hurling monkeys could well beat out the sum total performance of all active managers over a long-enough period of time. But this result is only an average result over the long term, one that masks the fact that there are winning active managers (and funds) at any given time.
Think of this: Using Malkiel’s imagery, let’s say a number of blindfolded monkeys are throwing darts at a blackboard that contains the names of all the stocks in the S&P 500. On a cap-weighted basis—which, we determined in Chapter 14, “Ending the Never-Ending Debate: Active vs. Passive Investing and Why You Can Take Both Sides,” means that some stocks in an index, based on their market capitalizations, will be given a greater value over others—the chance that any one monkey will hit a winner always must be equal to the number of stocks that are outperforming the index at any one time. If only 40 percent of the stock names are outperforming, a monkey has only a 40 percent chance of hitting a winner and a 60 percent chance of nailing a loser.
The number of stock names within the cap-weighted scheme is of critical importance here. A cap-weighted index can (and often will) show a disproportionate number of stocks in the bottom half of the index because it takes fewer stock names with heavier weights to fill out the upper half. (For instance, if 50 companies in an index have a weight of 1 percent and 10 companies have a weight of 5 percent, those 50 companies will sit in the bottom half of the index, while those 10 companies will fill out the top. Such top-bottom disproportion is a common feature of cap-weighted indexes.) Similarly, 50 percent of the weight of an index will always outperform and 50 percent will always underperform, with the number of stock names represented by each 50 percent also being inconstant.
In Table 14.1 in the previous chapter, I showed a fictional index of ten stocks that, after dividing by weight, had three stock names in the top half and seven in the bottom. If the stock names were jumbled and placed on a wall, a dart-throwing monkey would enjoy a 30 percent chance of hitting a name from the top half of the index and a 70 percent chance of hitting one from the bottom. Now, what if we are in a small-cap cycle, meaning that the smaller stocks in the bottom half of the index would, on average, outperform? Well, this would mean that our monkey would stand an excellent chance (more or less 70 percent) of hitting a winner.
The concept of market breadth is at play here. As described in the last chapter, we can say that a broad market exists when more than 50 percent of the stock names in an index are outperforming that index. Hence, the greater the market breadth, the greater the chance that an active fund will outperform its benchmark—or the greater the chance that active investing will beat out passive investing.
One easily can apply this dart-throwing test to the world of active funds, and I do so in a most revealing way in this chapter. But first a word on actively managed funds. Just as there are large-caps and small-caps, there are large-cap and small-cap funds that are managed by professionals who actively switch between stocks in search of the best-performing mix. As I pointed out in Chapter 8, “Pipelines to Our Investment Returns: How We Get What We Want, in the Amount We Want, and When We Want It,” mutual funds tend to have mandates whereby they purchase “like” assets, such as mostly value, growth, small-cap, large-cap, or international stocks. Fund managers, in other words, are often constrained by size and style, and here we can put this insight to good use. If we believe in the existence of size cycles, we also must believe that there will be periods when actively managed large- and small-cap funds will move in and out of favor.
We discussed in Chapter 13, “The Fight Is On: How to Invest Properly Relative to Regulations, Inflation, and Taxation,” how small- and large-cap cycles are predictable, in that the former emerges during periods of economic uncertainty and that the latter manifests in the converse, more certain, environment. For the most part, the level of economic certainty can be described in terms of the burden of inflation, taxation, and regulation at any given time. Because small-caps exhibit more nimbleness than large-caps within national borders (they can morph and adjust to skirt regulations, hedge against inflation, and avoid certain taxes), they will outperform during periods of uncertainty, when tax, inflationary, and regulatory conditions are in flux. Large-caps, on the flip side, will beat small-caps when these burdens fix and times are certain.
By applying this knowledge to the stocks in your portfolio, you will know when to favor large-caps over small-caps. But in terms of active versus passive, the switch is not as clear-cut as leaning toward active large-cap funds during large-cap cycles and active small-cap funds during small-cap cycles. To see this, we need to add weighting schemes to the concept of market breadth.
The market caps of the stocks in a cap-weighted index will, by definition, vary. If we take any cap-weighted index and rank the stocks in descending order by market cap, we will see a disparity in the number of stock names in the top and bottom halves. Typically, there will be fewer, heavier-weight stocks in the top half and more lighter-weight stocks in the bottom half. Hence, in a small-cap cycle, more than 50 percent of the names in a broad index (the bottom, lighter half) will outperform the index. This makes small-cap cycles and active management (in general) perfect partners.
From here we can narrow the discussion based on the mandates placed on fund managers. In general, small-cap fund managers will select from a basket of small-cap stocks and attempt to beat a small-cap benchmark, such as the S&P 600. At one point in recent years, the largest company in this cap-weighted index had a weight of about 0.7 percent, while the top ten holdings represented less than 6 percent of the weighted index. Contrast this with the large-cap S&P 500 at the same time, when the largest company in the index had a weight of more than 3 percent and the top ten holdings accounted for more than 19 percent of the index’s total weight. Clearly, the small-cap index appears much less top-heavy than its large-cap cousin, which is usually the case when comparing small- and large-cap indexes.
In a way, the scheme of a cap-weighted small-cap index is closer to that of an equal weight, meaning that the number of names outperforming the index will be nearer to 50 percent at most times. This indicates that the odds of a small-cap fund beating a small-cap benchmark at any time will hover near 50 percent and that a small-cap fund manager needs only a small edge to regularly come out on top.
And what about large-caps? What are the odds that a large-cap fund will beat a large-cap benchmark? Two snapshots of the large-cap S&P 500 reveal some drastically different conditions for active large-cap managers. At one point in the later, large-cap 1990s, the ten largest companies in the S&P 500 accounted for a full 50 percent of the index’s weight. Because these were large-cap days, this meant that a full 490 companies would, on average, underperform the index. With such a narrow window for picking the outperforming stocks, a passive indexing approach at this time would have made very good sense. Put another way, large-cap active funds and large-cap cycles are not perfect partners.
More recently, in an index snapshot taken during the small-cap cycle of the early twenty-first century, it took the largest 50 companies in the S&P 500 to account for 50 percent of the index’s weight. In a world of 500 stock names, this result is not that much different from the one in which ten companies made up half the index’s weight. But here the conditions drastically change for the large-cap manager, who would have a much greater chance of picking an outperformer among the 450 stocks in the lower half of the index (because, presumably, the smaller stocks in the lower half would outperform during the small-cap cycle).
This discussion boils down to the fact that there indeed are times when active funds will beat their passive benchmarks and that the existence of size cycles makes these opportunities predictable. Next I present some size-based stock data to help us form some decision rules on when to switch between an active and passive mode.
Mutual fund managers (most of them) are not monkeys. They are smart human beings who, in the pursuit of outperformance, work very hard to select the right mix of investments for their funds. Their jobs and reputations are always on the line, so they have a very good incentive to beat the market. Sadly for them, the odds are not always stacked in their favor—or equally in their favor, based on the constraints of large- and small-cap fund management.
Table 15.1 reports the percentage of stock names in two S&P indexes—the large-cap 500 and small-cap 600—that beat their respective indexes during the 1998–99 large-cap cycle and the 2000–05 small-cap cycle. (Note: In Chapter 13 and in Figure 13.1, I indicated that 1999 was a small-cap year, which, in terms of overall stock returns and per the conversation of certainty, it was. For the record, both small-caps and large-caps were strong performers that year, up 29.8 percent and 21 percent, respectively. But in contrasting the S&P 500 and 600 indexes, I am forced to consider it a transition year from large-cap to small-cap, favoring the large-cap result. Simply, when comparing size results between different indexes, you will sometimes get different results.) Returning to our dart throwers, elevated here from monkeys to humans, we can come to some general conclusions about the promise of active large- and small-cap strategies during different size cycles.
A dart thrower has a better chance of outperforming any index during a small-cap cycle.
Simply, when a size cycle switches from large-cap to small-cap, the number of stock names outperforming each benchmark index will increase. For the large-cap S&P 500, this is a function of the bottom half of the index (or the smaller-weight names) providing the outperformance during the small-cap cycle.
The odds of a dart thrower outperforming an index change systematically over the course of a cycle, and the odds of a larger-cap dart thrower change the most.
Averaging out the results, 32 percent of the large-cap stocks outperformed the S&P 500 benchmark during the large-cap cycle, while 61 percent outperformed during the small-cap cycle. That’s a big difference: a full 29 percentage point swing. In comparison, 42 percent of small-caps outperformed the S&P 600 during the large-cap cycle, while 49 percent beat the same index across the small-cap cycle. This is a smaller systematic change, yet 7 percentage points is important nonetheless. Note, again, that the smaller-cap S&P 600 will perform more like an equal-weight index at most times. As a result, the index will reveal a smaller shift in the level of out-performance between cycles.
During a small-cap cycle, a large-cap dart thrower has a better chance of beating a large-cap benchmark than a small-cap dart thrower has of beating a small-cap benchmark.
The only place we see greater than 60 percent outperformance is within the large-cap universe of the S&P 500 during the small-cap cycle, while there is only a 49% chance of outperforming the small cap S&P 600 universe during the small-cap cycle. Again, these is a direct result of the capitalization weights. In percentage terms, the stock names outperforming the large-cap index is much larger than the percentage of the number of stocks outperforming the smaller capitalization index S&P 600. Therefore, the odds tend to favor the larger-cap manager. Averaging out both indexes across the small-cap period, relative-to-benchmark outperformance favors large-caps by 12 percentage points (61 percent minus 49 percent).
During a large-cap cycle, a small-cap dart thrower has a better chance of outperforming a small-cap benchmark than a large-cap dart thrower has of beating a large-cap benchmark.
It does sound ironic that a large-cap fund manager will be at a stock-picking disadvantage during a large-cap cycle. But there is no escaping the realities of the weighting scheme as it relates to market breadth. During large-cap cycles, the largest of the large will get only that much larger, pushing more names into the bottom half of an index, which is out of favor during a large-cap cycle. In the 1998–99 large-cap period, only 32 percent of large-cap stocks outperformed the large-cap index, meaning that 68 percent underperformed on average—poor odds for a dart thrower. Over at the S&P 600, the outperformance odds, at 42 percent, were more in favor of the small-cap dart thrower. Still, the odds of underperformance were 58 percent.
A dart thrower is better throwing during small-cap cycles in general.
Fund and index constraints aside, the odds that an active stock-picking strategy will prevail always will be higher during a small-cap cycle. At these times, there simply are more winning names floating around.
If we momentarily shift away from the size-cycle mindset, we can perform a litmus test on the viability of an active/passive switching strategy within a portfolio.
Not so long ago, Standard & Poor’s began publishing an equal-weighted version of the S&P 500 index. In this scheme, because there are 500 stocks, each stock is assigned a weight of 1/500, or 0.2 percent, meaning that each stock in the index enjoys the same level of importance. In blind-monkey terms, each stock return in the index becomes a stand-in for the average return that can be achieved by tossing darts at the S&P 500 board of stocks. And if we take the analogy to its extreme, turning our active fund managers into blindfolded monkeys, we can equate the performance of the equal-weighted S&P 500 with that of the universe of actively managed funds. As goes the equal-weighted index, so goes active management. Meanwhile, we can use the cap-weighted S&P 500 as a stand-in, or benchmark, for passive performance because this historically has been the case.
Table 15.2 pits the performance of the cap-weighted S&P 500 against the equal-weighted version from 1989 to 2005, with the bolded results showing the triumphant index year to year. Not only is the cyclical nature of the results obvious, but so is the fact that, on average, the index in favor switches in unison with our size cycles: Passive (per the cap-weighted proxy) outperformed active (per the equal-weighted proxy) during what were, for the most part, large-cap years, whereas active beat passive during most of the small-cap years. Even though the results were a little more erratic for the 2000–05 small-cap period (the cap-weight index beat the equal-weight index two out of six times), the overall result for the period favored the equal-weight index and, hence, active management.
Table 15.2. Annual Returns of the Equal-Weighted and Cap-Weighted S&P 500
Cycle | Cap-Weighted | Equal-Weighted | Best | |
|---|---|---|---|---|
Large | 1989 | 6.7% | 7.4% | 6.7% |
Large | 1990 | 3.9% | –4.9% | 3.9% |
Small | 1991 | 30.5% | 35.5% | 35.5% |
Small | 1992 | 7.6% | 15.6% | 15.6% |
Small | 1993 | 10.1% | 12.5% | 12.5% |
Small | 1994 | 1.3% | 1.6% | 1.6% |
Large | 1995 | 37.6% | 32.2% | 37.6% |
Large | 1996 | 23.0% | 23.1% | 23.1% |
Large | 1997 | 33.4% | 24.6% | 33.4% |
Large | 1998 | 28.6% | 11.0% | 28.6% |
Large | 1999 | 21.0% | 10.2% | 21.0% |
Small | 2000 | –9.1% | 8.2% | 8.2% |
Small | 2001 | –11.9% | 2.3% | 2.3% |
Small | 2002 | –22.1% | –10.2% | –10.2% |
Small | 2003 | 28.7% | 26.0% | 28.7% |
Small | 2004 | 10.9% | 23.0% | 23.0% |
Small | 2005 | 8.1% | 4.91% | 8.1% |
Average | 11.0% | 12.4% | 15.7% |
The most important result in this investigation, however, is how well an active/passive switching strategy would have done across our 17-year sample period. The passive-only (S&P 500 cap-weight proxy) strategy would have returned a respectable 11 percent, and the active-only (S&P 500 equal-weight proxy) would have generated an even better 12.4 percent return. But the switching strategy would have delivered an outsized 15.7 percent return.
The results shown in Table 15.2 don’t quite jibe with the multiple findings that passive beats active investing over the long run. But they also don’t suggest the dominance of an active-only strategy. Adjusted for fees, the passive-only advocate could here make the case that active-only investing would not necessarily have outperformed passive-only across the period. But the more difficult case to make is that a switching strategy is not somehow superior.
One could, of course, hold to the efficient-market principle that the future path of stocks is unpredictable, so no such switching strategy can be implemented reliably. Yet because this active/passive switch is based firmly on the existence and proven predictability of size cycles, it becomes a fully functional and reliable strategy.
I believe in the efficiency of markets over the long run. I also believe in entering retirement having performed in an above-average way over your investment life. If you go all passive, I do predict that the long-run performance of the stock and bond markets will deliver you firm, average results. Average, here, again becomes a welcome and comforting word. If you go all active, on the other hand, you might or might not achieve market-beating results. Of course, with active investing comes greater risk because you and/or your manager(s) will be pitted against the collective knowledge of the market. But it is a fundamental reality of investing that the potential for greater-than-average returns exists alongside greater risk.
Thus, my proposal is nuanced on the passive versus active front: The long-run data might tend to show that passive investing is superior to active investing. But it also clearly reveals periods when active investing beats passive. The challenge, then, is to catch those periods, to be active at times and passive at others, and thus gain the best that both worlds have to offer. The challenge here is far from difficult, in that the large versus small decision will guide the active/passive switch:
Invest actively during small-cap cycles. The odds of beating an index turn decidedly in your (or your active fund manager’s) favor during small-cap cycles. At this time, you should choose actively managed funds to fill the allocation buckets in your portfolio.
Invest passively during large-cap cycles. The odds of beating the market systematically decline during large-cap cycles. And although they decline more for large-cap fund managers than small-cap managers, you will be best served by choosing index funds and/or exchange-traded funds (ETFs) at this juncture.
In proposing this, I am not suggesting that you become some sort of bizarre cross-breed investor, although you might be accused of this. To be sure, the active versus passive debate shows no signs of abating. And if you make a habit of reading the financial literature, there will be no escaping the onslaught of argument attempting to lure you to either side.
Not surprisingly, active managers always have the better argument during small-cap cycles, while passive-only purveyors crow a little more loudly when large-caps are in favor. Maybe you can use this as your switching indicator, although I suggest that you follow a more reliable strategy of tracking size cycles (in relation to the level of certainty that exists or threatens to develop in the economy) and simply go passive when the cycle turns large-cap and active when it shifts small-cap.
Critically, these cycles persist. And there’s nothing wrong with being a little late in making a switch, if the switch you end up making delivers higher returns.