How To Approach Factor Investing

While it’s folly to try to time factors, it’s really hard for investors to stick with them.

Reviewed by: Dave Nadig
Edited by: Dave Nadig

[Editor's Note: If you’re interested in smart-beta and factor Investing, check out our upcoming webinar series that kicks off this Friday on understanding and using factor strategies. Register here.]

The proliferation of quant-finance-based ETF strategies has definitely left investors with a lot of options.

Back when I started in the business, Wells Fargo Nikko Investment Advisors (which became BGI, then BlackRock, through acquisitions), used to sell a very popular strategy to institutions called “Tilts & Timing” which, if launched today, would simply be another “smart-beta ETF.” That was in 1992.

The question for investors is not whether a factor-based approach to investing can work—of course it can. The challenge is in predicting which factors are going to be in or out of favor in a given market environment, and increasingly, understanding what your exposures even are, relative to a more common vanilla alternative.

Is Timing Everything?

One of the age-old questions most investors are aware of is the growth-versus-value conundrum. Over the long haul (the very long haul), investing in the value factor seems like just the easiest call ever, as does skewing your portfolio away from large-caps.

As Larry Swedroe and Andy Berkin point out in their excellent book on factor investing, the odds of underperforming the market in any random 20-year period by being invested in small-caps from 1927 to 2015 was just 14%. And if you invested in value, the chance of getting it wrong drops to 6%.

And yet, if you really get it wrong, the market can crush you for a very long time indeed:


Small-Cap Value Drawdowns

Time PeriodNo. of
During the Period (%)
in Post-
Period (%)
Jan 1929 - June 193242-8.9230.6
Nov 1971 - Dec 197326-19.067.1
July 1989 - Aug 199126-27.544.5



So how do you know when it’s time for what? Well, the simplest and most naive way is to simply look at charts.

For instance, you might look at the historical relationship between growth and value right now (proxied here by the iShares S&P 500 Growth (IVW) and the iShares S&P 500 Value ETF (IVE) below):



If you believed that, over time, these two indexes should revert to the mean, you might look at the recent run in growth and think, “Well, value is due for a comeback; just look at this year!”



Or, alternatively, you could think, “Wow, growth is running; time to pile in!”

I’d argue that both of these are somewhat woolly-headed approaches to investing, but I’ve met countless investors who use language like “due” and “running” to make short-term decisions. For factors, however, that kind of short-termism is a bad approach to take.


RAFI’s New Sandbox

If you really want to think about timing your factor investments—which is inherently risky, to be sure—I can’t point to a better tool for understanding the relationships between different factors than the one recently launched by Research Affiliates right here.

It lets you play with various factor data in a completely interactive format that can be a touch overwhelming, but there’s real insight to be gleaned. For instance, based on RAFI’s valuation metrics, here’s what the current state of the most common factors is:



The vertical bands represent historical valuations; the circles are the current valuations. A quick glance would suggest that:

  • Low beta (another way of saying “low volatility”) small-cap stocks are very expensive.
  • High-profitability (another measurement of quality) small-cap stocks are very cheap.
  • Both large- and small-cap value are below median in terms of valuation, but not exactly bargains.

You can go further, and actually look at fully simulated investment strategies to get an expected five-year return model for commonly used approaches:



In this case, their model would suggest that a “quality” based approach would eke out 3.45% excess returns over a market benchmark, with a beta of just .9. (A beta of below 1.0 implies less-than-market risk)

Just A Starting Point

The RAFI tool is a great step forward in helping investors get their heads around the smart-beta ETF landscape, but it’s just a learning tool. The heavy lifting, unfortunately, still needs to be done by advisors and investors.

The theoretical portfolios analyzed by RAFI aren’t real-world ETFs—they’re just proxies for common ways of slicing and dicing the market. And of course, all the shiny data in the world is never a guarantee of what happens tomorrow.

For more approaches to developing a factor-based approach, we’re doing a three-part webinar series starting on Sept. 29. I hope you’ll join me and my panelists for a deeper dive into the space. Financial professionals can register here.

At the time of writing, the author held no positions in the securities mentioned. Contact Dave Nadig at [email protected].


Prior to becoming chief investment officer and director of research at ETF Trends, Dave Nadig was managing director of Previously, he was director of ETFs at FactSet Research Systems. Before that, as managing director at BGI, Nadig helped design some of the first ETFs. As co-founder of Cerulli Associates, he conducted some of the earliest research on fee-only financial advisors and the rise of indexing.