Multi-factor ETFs

This is one of a series of articles discussing smart beta ETFs. Other smart beta articles you can read:


A multi-factor ETF is an ETF that follows an index that screens its potential holdings using two or more investment factors. For example, if an ETF follows a small cap, high dividend, low volatility index, it is considered to be a multi-factor ETF because it is screening on three factors: size, dividends and volatility.

Here is a count of the multi-factor ETFs in our database, by category:

CategoryETF Count
Alternatives 1
Global Equity102
Special Security Types5
US Equity229
US Fixed Income1

Smart beta and multi-factor ETFs have risen in popularity during the past ten years. Multi-factor ETFs continue to be launched at a high rate. Here is a count, by year of inception, of the multi-factor ETFs in our database:

Year of InceptionETF Count

Note that there were actually even more ETFs launched then this table shows, as we are only displaying the launch dates of ETFs still active in our database. There were more ETFs that were launched during these years that have since been closed down by their sponsor.

Multi-factor ETFs can track any number of investment factors. Here is a summary of the number of investment factors being used by the multi-factor ETFs in our database:

Number of Factors UsedCount

Multi-factor ETFs are complex

The number of different approaches is staggering

It is very difficult to compare multi-factor ETFs because they use an amazingly different combinations of factors. There are nine common investment factors:

This doesn't seem like a big list, but each multi-factor ETF is selecting from a different combination of these factors. So the number of possible combinations adds up quickly. In fact, the multi-factor ETFs in our database currently use 76 different combinations of factors! That's how different they are.

Not only do they use different combinations of factors but they also weight their holdings differently (equal weight versus fundamental weight versus market capitalization weighting). And they are selecting stocks from different capitalization sizes (large cap stocks versus mid cap stocks versus small cap stocks).

There also isn't any agreement on what the factors really are. The "quality" factor is one of the most commonly cited factors. But there is no agreement as to what makes up the quality factor. It usually measures how profitable a company is, but there are ten different approaches to measuring a company's profitability. Some indexes use net income, some use "operating earnings", some use return on equity, some use free cash flow, etc... So it is not an exaggeration to say that no two multi-factor ETFs are really alike!

No one is precisely following academic research

The most famous academic factor models, such as the Fama French 5 factor model, use a combination of factors that don't really match up against the combination of factors used by the multi-factor ETFs. Fama French used as factors size (small cap), value, high operating earnings and low investments (low growth in total assets on the balance sheet). We're not sure that any multi-factor ETFs match up to that. Similarly, Hou Xue and Zhang used as factors size (small cap), high return on equity, and low investments (low growth in total assets on the balance sheet). We're not sure that any multi-factor ETFs match up to that.

Does multi-factor investing work?

There are plenty of people who still question whether smart beta and multi-factor ETFs are really a good idea. The ETF industry has become very competitive, and as a result, the fees associated with many non-smart beta ETFs have become very low. You can buy an ETF that tracks the S&P 500 Index and pay very little in fees. For example, the fees associated with IVV, the iShares Core S&P 500 Index Fund ETF, are currently 0.04%. The low fees make it very tempting to just build a stock portfolio using IVV, or any of the other market-cap index based ETFs that have low fees.

It is also open for debate whether it is possible to build a multi-factor index that will successfully outperform the market over long periods of time. The only investment factor that clearly has a long-track record of outperformance is probably the size factor - i.e. small cap stocks generally outperform large cap stocks over long periods of time. But again, you can buy an ETF that tracks the S&P Smallcap 600 Index and pay very little in fees. The fees associated with IJR, the iShares S&P SmallCap 600 Index Fund ETF, are currently 0.07%.

So it is by no means an unreasonable position for long-term investors to ignore multi-factor ETFs and just buy a simple stock portfolio of IVV and IJR and pay very little in fees. There are no guarantees of course, but IJR will probably outperform most large cap, multi-factor ETFs over the next 15 years.

We tend to take a middle ground in the debate. We don't think investors should abandon cheap ETFs like IVV and IJR in favor of multi-factor ETFs, but we also think there are some multi-factor ETFs that are worth while.

Research Tools

We offer a variety of tools to help you research multi-factor ETFs. If you lean towards not wanting to rely on theoretical backtest data, you can look at our tool that shows ETFs that have outperformed SPY since inception. To get on this list, the ETF must be at least eight years old.

Our Picks

One thing we do at is give each ETF a rating for long term investors. Here are the multi-factor ETFs that has rated as an "editors choice", our highest rating:

SymbolDescriptionInception DateCategoryActions
PSJInvesco Dynamic Software ETF06/23/2005US EquityAnalyze
SPHQInvesco S&P 500 Quality Portfolio ETF12/06/2005US Equity Analyze
RPGInvesco S&P 500 Pure Growth ETF03/01/2006US Equity Analyze
CZAInvesco Mid-Cap Core ETF04/02/2007US EquityAnalyze
FDTFirst Trust Developed Markets Ex-US AlphaDEX ETF04/18/2011Global Equity Analyze
DVYEiShares Emerging Markets Dividend ETF02/23/2012Global EquityAnalyze
MOATMarket Vectors Morningstar Wide Moat ETF04/24/2012US EquityAnalyze
CAPEBarclays Shiller CAPE Index ETN10/10/2012US Equity Analyze
FNDESchwab Fundamental Emerging Markets Large Company ETF08/15/2013Global Equity Analyze
FNDCSchwab Fundamental International Small Cap Company Index ETF08/15/2013Global Equity Analyze
FLQEFranklin LibertyQ Emerging Markets ETF06/01/2016Global EquityAnalyze
XSHDInvesco S&P SmallCap High Dividend Low Volatility ETF11/29/2016US Equity Analyze
VSDAVictoryShares Dividend Accelerator ETF04/17/2017US Equity Analyze
EEMDAAM S&P Emerging Markets High Dividend Value ETF11/28/2017Global EquityAnalyze

You Have To Trust Theoretical Back-Test Index Data

Most smart beta indexes are fairly new, so when we are rating smart beta ETFs, we have no choice but to look at theoretical backtest data for the index prepared after the index was launched. We all know the limitations of such theoretical backtest data. Every investor has to form their own opinion about whether to trust such data.

We admit that many of the smart beta ETFs that we have rated as an "editor's choice" were given that rating primarily on the basis of a good looking index, often using theoretical backtest data. We evaluate each smart beta index to determine if its methodology seems to make sense given academic factor models and other research. But at the end of the day, an investor sometimes just has to make a gut call as to whether to accept theoretical back test data.

If you lean towards not wanting to rely on theoretical backtest data, you can look at our tool that shows ETFs that have outperformed SPY since inception. To get on this list, the ETF must be at least eight years old.

All data is a live query from our database. The wording was last updated: 12/21/2017.

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