Will ETFs Destroy Factor Investing? Nope.

One of the popular investing truisms is the following (inspired by Bill Sharpe):

For somebody to beat the market (win) someone else has to lag the market (lose).

This becomes an even more daunting (efficient market) statement when changed to the following:

For someone to consistently beat the market (win) someone else has to be consistently willing to lag the market (lose).

This correctly implies that it is very hard to consistently beat the market and that in aggregate, it’s impossible.

Recent research (including this article by Wes) shows that the statement above doesn’t always hold…although its still true the majority of the time.

However, what interests me isn’t the minutia about how “passive” passive investors really are, but important questions like the following:

How can value investing work if everyone already knows about it and there are now a plethora of ETFs and mutual funds that follow that investing style?

I am not alone in asking this question, as none other than investing legend Cliff Asness asks and answers the same question here.⁽¹⁾

Cliff provides some good insights, but doesn’t get down into the weeds by looking at who, if anyone, is volunteering to be on the losing team by being consistently short value, momentum, low volatility or size.

Perhaps we may never know…that is until I stumbled across this interesting paper by David Blitz that directly looks at the flows into the various factors.

Will ETF Factor Investing Destroying the Efficacy of Factors?

What David finds is that across the large ETF universe–400+ funds with at least 3 year track records–don’t have any meaningful factor exposures other than a beta of nearly 1.0 to the Mkt-Rf risk factor.

Looking further into the weeds, David divides the 400+ ETF universe into “smart beta” funds that explicitly look to target a risk factor (value or HML, momentum or WML, small or SMB and low volatility or LV-HV) and everyone else.  He includes fundamental weighted ETFs, equal weighted ETFs and dividend ETFs in the “smart beta” group.

He finds that when the ETF universe is divided in this way, there are roughly 100 “smart beta” funds and 300+ ETFs that are not “smart beta”.  The “smart beta” ETFs, in aggregate, have large and positive exposures to HML, SMB and LV-HV, but not WML (there aren’t many ETFs that target momentum and the ETFs that did have a positive factor loading on WML were sector funds which were likely caused by performance over the measurement period and not a targeted exposure to WML).  This is a good finding for the ETF owners as they are (in aggregate) getting exposure to the “smart beta” risk factors.

Here is a picture of the fund universe “HML” value factor loadings:

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index.

Note that in aggregate there really isn’t a specific movement strongly in favor or against value.

Here is a picture of the fund universe “WML” momentum factor loadings:

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index.

Momentum is really not exploited by ETFs, either directly, or in aggregate. This is pretty interesting, given momentum is arguably the strongest market anomaly.

The non “smart beta” ETFs have negative exposures to HML, SMB and LV-HV, but don’t show a meaningful negative exposure to WML.  This shows that there are (large) groups of investors who knowingly or unknowingly maintain negative exposure to “smart beta” factors.

There are several other interesting findings from this paper:

• David found that many of the ETFs classified as “value” didn’t have strong loadings to the HML factor.  This highlights how important index and ETF portfolio construction are when trying to target a specific factor.
• David found that the best HML factor loadings were from Energy and Financials sector ETFs.  This may be surprising at first, but HML is constructed using Price/Book Value and Energy and Financials typically have the lowest Price/Book Value of the sectors.
• David found that (generally) ETFs that stated that they targeted the SMB or LV-HV factors generally had some of the largest factor loadings to those factors.

Note: If you’re new to factor investing, here is a good overview piece.

Are Exchange-Traded Funds Harvesting Factor Premiums?

• David Blitz
• A version of the paper can be found here.
• A published version of the paper is here.

Abstract:

Some exchange-traded funds (ETFs) are specifically designed for harvesting factor premiums, such as the size, value, momentum and low-volatility premiums. Other ETFs, however, may implicitly go against these factors. This paper analyzes the factor exposures of US equity ETFs and finds that, indeed, for each factor there are not only funds which offer a large positive exposure, but also funds which offer a large negative exposure towards that factor. On aggregate, all factor exposures turn out to be close to zero, and plain market exposure is all that remains. This finding argues against the notion that factor premiums are rapidly being arbitraged away by ETF investors, and also against the related concern that factor strategies are becoming ‘overcrowded trades’.