Investors love talking about their home runs, the stocks that go from $5 to $100, the "twentybaggers" to steal from Peter Lynch. Your clients are probably no different. I'm sure many of you get a bit weary hearing your client discuss his investment idea that bought the vacation house or put his kid through Stanford (and why aren't you coming up with more of those ideas?).
Of course, I've found most investors' memories to be quite selective when it comes to their investments. They are quick to talk about their big winners, but you never hear about the stock that goes from $90 to $5 to Chapter 11. And following the tech implosion in the early 2000s, there were plenty of those losers to go around.
My experience has been that finding such mega-winners is really, really hard--not to mention really, really risky. Indeed, if you like to put your clients in blue chips, you'll rarely catch twentybaggers by fishing in that pond. The companies are simply too large to generate the type of earnings and revenue growth necessary to catapult a stock from $20 to $200.
And you aren't likely to find twentybaggers among the mutual funds or ETFs you put into clients' portfolios, either.
No, to find huge winners, you have to look in scarier areas of the market, where an eye-popping return carries a commensurate expected level of risk. And what advisor likes to venture into those minefields?
The fact is that you know that you'll probably never hit a giant home run for your client. His investment time-horizon and your typical holding period aren't long enough, and the types of investments you buy for clients just aren't conducive to those gains. That's okay. Good advisors don't have to be great stock pickers. What they do have to be competent at, however, is the one side of the investment equation that oftentimes is underappreciated by clients-- keeping junk out of portfolios.
Just look at your own portfolio for a minute. What you'll probably see--and this is likely the case with most investors--is the following (assuming a 10-investment portfolio for example purposes):
?Two investments that have done well. They may not be twentybaggers, but they have produced solid returns.
?Five investments that are average holdings. These have probably generated returns plus or minus a few percentage points relative to the benchmark.
?Three investments that have been losers, where you rode them down 30 percent or 40 percent and are in that "no-man's land"--too late to sell and too early to buy more.
Now it would be nice to have more big winners. But keeping junk out of portfolios is easier than finding huge winners and potentially, just as rewarding for clients. And one reason it has become easier is the emergence of quantitative investing.
Quantitative investing, of course, is the process by which investments are bought and sold based on evaluating such measurable characteristics as revenue, earnings, profit margins, valuation and finances. Underlying most quantitative approaches is a computer-driven model that evaluates universes of stocks based on a variety of metrics. What usually falls out of the model is a strict "rules-based" methodology for stock selection.
Quantitative investing offers a number of potential advantages as compared to traditional active investment management:
A disciplined, consistent approach. The biggest problem I see with most investors (and some advisors) is that they don't adhere to a consistent approach when buying and selling investments. They tend to be influenced by whatever style is in fashion at that time. Such a reactive approach, oftentimes driven by emotions and not investment fundamentals, usually results in lousy performance. One of quantitative investing's strengths is that its "by-the-numbers" approach leaves no room for the reactive type of emotions--fear, greed, hope--that lead to stupid decisions. This discipline is especially important on the sell side, which is arguably the hardest thing to get right in an investment program. Because most quantitative methodologies consist of a scoring system that ranks stocks, quant investors have an invaluable tool for ongoing evaluation and ranking of portfolio investments--particularly helpful when determining whether to sell an investment.
Increased pool of potential profit opportunities. Successful investing is about maximizing your potential investment opportunities while minimizing mistakes. There are more than 5,000 stocks traded in the U.S. Searching through this vast universe for opportunities is virtually impossible without an efficient and powerful tool to evaluate companies in a consistent way. That's why active managers tend to focus on a small slice of the universe. However, by limiting your starting universe, you limit your potential opportunity pool, and that's a mistake. The economies of scale available with a quant approach enhance investors' ability to exploit opportunities in the market, regardless of where they may be hiding. In other words, quant strategies have no "capacity restraints" and can work well across virtually any size or style segment--large cap or small, value or growth, foreign or domestic.
Addition by subtraction. This is one of the more underrated benefits of quant investing. By using a strict methodology based on fundamental investment criteria, quant investing increases your odds of keeping out stocks with poor fundamentals. This notion of "addition by subtraction" underlies "enhanced indexing," the idea of improving the results of an index by eliminating the worst stocks.
To be sure, quant investing is not perfect. In fact, many quants have had a fairly rough go of it over the last 12 months or so. One reason is that most quant models have a bias toward value. That's not surprising since many quant models are constructed based on what has worked well historically, and value metrics have historically worked quite well when picking stocks. However, markets go through cycles, and during periods when value investing is out of favor, quant returns may suffer.
Quant investing also lags during periods when the "pigs are flying"--when the most speculative stocks are doing well. Think Internet stocks in the late '90s, for example. That period was a challenging one for many quant models since quant strategies generally focus on buying quality stocks (as measured by investment fundamentals) at decent valuations and ignoring those with little or no profits and limited operating histories.
Despite the many positive attributes of quant investing, historically it has not been an easy strategy to bring to client portfolios. One reason is that, as much as you would like to build your own "black box" quant model, you barely have enough time to service your clients. Also, quant investing strategies--especially enhanced indexing--may require portfolios of 200 or more securities, and that tends to be a bit daunting for clients, let alone potentially expensive from the standpoint of trading fees.
Fortunately, the advent of exchange traded funds now makes it easy and efficient to include quant-based strategies in any client portfolio.
Now I'm not talking about ETFs based on fundamentally-weighted indices (where components are weighted based on such things as dividends or revenue and not on market cap), although I suppose that is a form of quant investing. Rather, for purposes of this article I'm focusing more on ETFs that are enhanced indices where the fund consists of a basket of stocks whittled down from a much larger universe via quant methods.
For example, one of the earliest quantitative ETFs was the iShares Dow Jones Select Dividend Index (DVY). This ETF has a fairly simple quantitative methodology for stock selection. The starting universe is the Dow Jones U.S. Index, which covers approximately 95 percent of U.S. market capitalization. Stocks are eliminated if they don't meet certain trading-volume requirements. Also, companies with payout ratios above 60 percent and negative five-year dividend records are eliminated. The remaining stocks are ranked and selected based on dividend yields. This ETF's focus on dividends and disciplined quantitative methodology proved appealing to investors, who shoveled nearly $3 billion into the ETF in a matter of months following its introduction in November 2003.
Since then, the number of quant ETFs has grown dramatically--especially over the last 18 months. Two ETF sponsors that have embraced the quant approach are First Trust and PowerShares. The table on page 50 lists, by investment sector, a number of quant ETFs provided by these two firms. The table also lists a possible benchmark ETF for that group.
PowerShares is perhaps the leader in quant ETFs. The company's line of more than 40 "Dynamic" quant ETFs uses the "Intellidex" quant model for selection purposes. Intellidex, in turn, uses 25 quantitative factors across such categories as value, growth, risk and momentum to identify stocks that are likely to outperform.
First Trust, with its AlphaDEX model, is a relative newcomer to quant-based ETFs, but has been building out its line of quant products.
How have these quant-based ETFs performed? Thus far, performance has been fairly sketchy. Some of PowerShares' Dynamic portfolios have done a decent job since their inception--a number have been around since 2005--although more recent returns have been sluggish. Recent returns have also been mixed for First Trust's quant ETFs.
On the other hand, many quant funds have been around for less than 24 months, which is probably too short a period for a fair evaluation. And as for the recent lackluster results, it is not surprising since many of the value metrics employed by quant models have lagged badly over the last year. For example, such value metrics as price/book value and price/free cash flow, which have historically worked well when picking stocks, have been just brutal of late.
Still, while quant ETFs may have some growing pains, I continue to be optimistic that as a group, they will give a reasonably good account of themselves over entire market cycles. Areas where quant investing should be especially effective are the less efficient areas of the market, where the discrepancy between the best and worst stocks (based on investment fundamentals) is huge. For that reason, advisors should give special consideration to style boxes outside the large-cap space when considering quant ETFs.
Chuck Carlson is chief executive officer of Horizon Investment Services and the author of Winning With The Dow's Losers (HarperBusiness). David Wright, CFA, provided research assistance for this article.
