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:
|Special Security Types||5|
|US Fixed Income||1|
|Year of Inception||ETF 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 Used||Count|
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:
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.
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.
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.
One thing we do at ETFAnalyst.com is give each ETF a rating for long term investors. Here are the multi-factor ETFs that ETFAnalyst.com has rated as an "editors choice", our highest rating:
|PSJ||Invesco Dynamic Software ETF||06/23/2005||US Equity|
|RPG||Invesco S&P 500 Pure Growth ETF||03/01/2006||US Equity|
|CZA||Invesco Mid-Cap Core ETF||04/02/2007||US Equity|
|FDT||First Trust Developed Markets Ex-US AlphaDEX ETF||04/18/2011||Global Equity|
|DVYE||iShares Emerging Markets Dividend ETF||02/23/2012||Global Equity|
|MOAT||Market Vectors Morningstar Wide Moat ETF||04/24/2012||US Equity|
|FNDC||Schwab Fundamental International Small Cap Company Index ETF||08/15/2013||Global Equity|
|FNDE||Schwab Fundamental Emerging Markets Large Company ETF||08/15/2013||Global Equity|
|FLQE||Franklin LibertyQ Emerging Markets ETF||06/01/2016||Global Equity|
|XSHD||Invesco S&P SmallCap High Dividend Low Volatility ETF||11/29/2016||US Equity|
|VSDA||VictoryShares Dividend Accelerator ETF||04/17/2017||US Equity|
|EEMD||AAM S&P Emerging Markets High Dividend Value ETF||11/28/2017||Global Equity|
|CAPD||iPath Shiller CAPE ETN||11/21/2018||US Equity|
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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