Public Quant Funds Aren't Always What They Seem
Quantitative equity strategies 1 are a fast-growing retail product. There is more than $150 billion in quant equity public mutual funds, and such ETFs are on track to top $1 trillion this year.
Unfortunately, there’s little agreement on what these funds are. The two most common definitions are “uses numbers to select stocks” and “follows a systematic selection process.” Neither is useful because almost all professional investors use numbers and have a process.
A better definition is, “picks stocks based on designated factors.” This highlights that quants regard a stock as a bundle of factor exposures. But it misses another point. Traditional investors use factors such as price-to-earnings ratios and earnings growth to select good stocks, while quant equity investors select stocks to get specified exposure to factors such as value and quality. To a traditional investor, anything can be a factor, and an input to the stock selection process. To a quant, there are only a few reliably documented factors, 2 and they are the outputs of the portfolio construction process.
For example, one of the oldest quant factors is size. 3 Small-capitalization stocks have consistently delivered better risk-adjusted returns than large-capitalization stocks. An investor could take advantage of this observation by buying a Russell 2000 index fund (a passive fund that buys only small capitalization stocks), an actively managed small-cap stock fund -- or an equally weighted S&P500 index fund or a smart beta size ETF. The latter two are normally considered quant portfolios.
No one has a trademark on “quant equity” and fund marketers can use the term however they like. But investors should appreciate the distinction between funds that select small-cap stocks and those that deliver exposure to the size factor.
The first three types of fund above, and most of the funds labeled “smart beta,” select small-cap stocks and should be benchmarked and managed the same way as traditional funds. They deliver a mix of factor exposures. Small-cap stocks usually have higher P/E ratios, faster growth, more volatility and beta, less debt and lower dividend yields than large-cap stocks. They are far more likely to have negative earnings; and they are concentrated in certain industries.
A true quant equity-size portfolio uses a composite measure to determine size, 4 and constructs portfolios with the same P/E ratio, growth, industry distribution and other parameters as the overall market. 5 That’s why you need a computer and researchers for quant equity; anyone can select small-cap stocks by hand. 6
Investing in a true quant equity portfolio is like investing in an asset class. You invest in stocks because theory and long-term evidence suggests that you earn a risk premium for doing so. Theory and long-term evidence also suggest you earn risk premiums by investing in factors such as size, momentum, value and quality.
In all cases, it is foolish to change allocations based on performance. 7 It’s also foolish to think quant equity funds will do well or badly as a group. 8 There will be periods (often multiyear periods) where some factors underperform or outperform, but investment in factor portfolios should be based on long-term faith rather than recent results.
Finally, you should think of fees differently from traditional active investment. Quant equity returns are beta returns, 9 returns from exposure to risk factors. Fees are higher than index funds not because the manager has any unique insight (alpha) but because the process has higher costs and turnover. Traditional active managers promise alpha. If you believe them, you should think of fees as payment for alpha, not as compensation for the expenses of running their process.
Quant equity offers investors attractive ways to harvest risk premiums at reasonable cost. But if you manage it like traditional active management -- benchmarking against the market, paying alpha fees for outperformance and dropping managers for underperformance -- you will not only miss the advantages, but likely underperform the market. You should also avoid the opposite mistake, paying more than index fund fees for funds labeled “quant equity” or related terms, that merely apply quantitative criteria to selecting stocks, without delivering calibrated exposure to recognized compensated factors.
Bloomberg Prophets Professionals offering actionable insights on markets, the economy and monetary policy. Contributors may have a stake in the areas they write about.
Disclaimer: The author recently retired from 10 years as risk manager to a large quant equity manager, AQR Capital Management. Nothing in this article should be taken as investment advice, or as endorsements of AQR’s funds or any other funds. The author invests in quant equity funds.
The best-known set of equity factors are those determined by Nobel laureate Eugene Fama and his long-time factor collaborator Kenneth French, who was somehow overlooked by the Nobel committee. The five “Fama-French” factors are the market (overall exposure to equities), size, value, robust and conservative. This leaves out momentum, which has solid academic and empirical support as well. Other people parse “robust” and “conservative” differently, using related factors such as quality and profitability. But these, and perhaps one or two others or variants of these, are the only ones generally accepted and supported by theory, decades of strong empirical evidence with both backtests and real money, in many different markets. Many products advertised as quant equity use either ad hoc factors such as dividend yield, perverse factors such as growth or factors supported only by proprietary backtests (sometimes called the “factor zoo”). This last group might include some useful factors that will be recognized in the future, but probably contains almost all random noise.
The seminal paper is, Banz, Rolf W. 1981. “The Relationship Between Return and Market Value of Common Stocks,” Journal of Financial Economics, 9, 3-18.
For example, size can be defined as market capitalization, but also by total assets, total revenues, enterprise value or other measures. All of these things can be measured using most recent data, or averages of past data or projections of future data or combinations. One important component of quant equity research is to determine a composite measure that gives the best pure indication of the size factor that is rewarded with a return premium.
Actually, some quant equity portfolios target different parameters than the market. For example, quant equity hedge funds are often run “market neutral,” meaning zero exposure to the market factor. Other quant portfolios are managed to a target volatility. The point is that quant portfolios have systematic processes to determine factor exposures.
I don’t think you can be a quant equity manager without a sophisticated computer algorithm, not just to select stocks but to optimize rebalancing and control trading. Some managers have algorithms so complex they can be described as “black boxes.” While this is certainly quantitative investing, and if the managers buy equities they have a legitimate claim to the term “quant equity,” it’s not what I’m discussing in this article. The quant equity algorithms I have in mind are conceptually simple without any advanced mathematics, though the implementation details can be very complex.
I don’t believe in factor timing at all. But many people disagree. What I am confident is foolish is simple factor timing such as buying the factors with good three-year performance and avoiding the ones with poor three-year performance; or buying all factors when factors as a whole have done well recently.
Some factor pairs are known to have positive correlation and some have negative; and in some cases different managers will use similar factors that have high correlation. But it’s never been true that all major factors go up or all go down at the same time.
Beta returns are paid by the market as compensation for passive exposure to risk factors, alpha returns are returns in excess of market due to unique talent. Index funds and quant equity funds give beta returns, which an investor should evaluate by fidelity to the index relative to costs. An investor should be willing to pay for alpha returns based on the size of the return rather than the costs of producing it. An investor should consider the alpha left to her after paying the manager’s fee; of course, it only makes sense to pay that if the investor is confident the manager can deliver the expected alpha in the future, it’s hard to tell past alpha from luck.
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