What is a smart beta ETF?

Although not all ETFs track an index, ETFs are primarily associated with the concept of index investing. As shown in this table, most ETFs today track an index:.

Investment StyleETF Count
5
Actively managed350
Buys and sells commodity futures on a set pattern11
Follows a set investment pattern3
Other84
Passively tracks an index1,872
Physically owns a precious metal13
Tracks price of currency exchange rates12
Total2,350

The original idea behind index investing was that since it is very difficult to "beat the market", an investor should just "own the market". So the original ETFs that were launched during the late 1990s and early 2000s were based on well known broad market indexes like the S&P 500 Index (large cap stocks) or the Russell 2000 Index (small cap stocks). These indexes were market capitalization weighted indexes, which made sense if you wanted an index to track the market. You can read more about indexes in our introductory educational article called what is an index?.

In the year 2000, iShares launched the first ETFs that tracked indexes that were designed to outperform the market, rather than just mirror the market. At that time, the primary way that investors thought they could outperform the market was to own either "value" stocks or "growth" stocks. So iShares launched a series of ETFs that were either value ETFs or growth ETFs.

The value ETFs that were launched were fairly straight-forward, as they selected stocks that were "inexpensive" using measures like market value compared to book value. The growth ETFs were a little more complicated to understand, because they were using a variety of methods to select "growth stocks", including fundamental factors about a company such as sales growth, but also technical factors about the stock like price momentum.

Each of the major index providers (MSCI, S&P, Morningstar, Russell, etc...) had their own method of creating a "growth index", as we will discuss below. But they all generally followed a similar framework. The idea was to classify all stocks into one of three buckets: growth stocks, value stocks, and stocks that were "neither". The "neither" group of stocks was alternately referred to as "core" stocks, or "blend" stocks.

The growth indexes were the most complicated to understand. Lets look at a few examples. IVW, the iShares S&P 500 Growth ETF,which was launched in 2000, tracks the S&P 500 Growth Index, which measures growth using three factors: sales growth, the ratio of earnings change to price, and momentum. As another example, VUG, the Vanguard Growth ETF, which was launched in 2004, tracks the performance of the CRSP U.S. Large Cap Growth Index. CRSP classifies growth securities using the following factors: future long-term growth in earnings per share (EPS), future short-term growth in EPS, 3-year historical growth in EPS, 3-year historical growth in sales per share, current investment-to-assets ratio, and return on assets.

So these older style "growth" indexes were actually selecting stocks using several "investment factors". An investment factor is any fact or statistic about a company that might explain why the company's stock performs either well or poorly.

For about ten years, this notion of everything being a growth stock or a value stock prevailed. As time went by, and more and more research was done into investment factors, the investment community began to think more and more in terms of "investment factors" rather than just value stocks versus growth stocks. Index providers began to develop indexes that were selecting stocks using a variety of investment factors, besides just value versus growth.

At some point, ETF providers coined the term "smart beta ETFs" to refer to ETFs that are tracking an index designed to outperform the market. Morningstar uses the term "strategic beta" ETFs. Some ETF providers also use the term "factor ETFs" when talking about smart beta ETFs.

With today's terminology, the older "growth ETFs" would be labeled as "multi-factor ETFs", since most growth indexes are selecting stocks using multiple factors like quality and momentum. Regardless of the terminology, the goal is the same: can you build an index that outperforms the market? Throughout StockMarketMBA.com, we use the term "smart beta ETF" to reference any ETF that is based on an index that is not simply passively tracking a well known index like the S&P 500 or the Russell 2000.

We should note that not all smart beta ETFs are designed to outperform the market. Some smart beta ETFs, such as those that are dividend focused, are merely trying to achieve a higher dividend yield with less volatility, even if that means a slight under-performance compared to the market.

We should note too that the framework from the 1990s that all stocks should be classified between growth, value and blend continues to exist, and you will still see references to it all the time. Throughout our website, we use the newer terminology of talking about stocks using factors. For example, the older ETFs that track old style "growth" indexes are referred to as "multi-factor" smart beta ETFs.

Smart Beta Approaches Today

There are currently three different approaches to creating a smart beta index that will (hopefully) outperform the market:

There are quite a few smart beta ETFs that do nothing more than change the weighting method of the index to something other than market capitalization. RSP, the Guggenheim S&P 500 Equal Weight ETF, tracks the S&P 500 Equal Weight Index, which is an index of every stock in the S&P 500 Index, but weighted equally rather than by market capitalization. RSP has a long track record of outperforming the S&P 500 Index:

Investment Factor Definitions

What investment factors cause one stock to outperform another stock over long periods of time? There isn't necessarily a standard set of definitions. On our website, we have classified every smart beta ETF by the types of factors the index is using to select stocks. Here are the factor definitions that we are using:

Note that these factors are sometimes referred to as sources of "Alpha". When analyzing the performance of a portfolio, someone came up with the formula that the return of a portfolio is attributable to two factors: 1) "Alpha" - what the portfolio manager did to outperform the market; and 2) "Beta" - the return of the market itself. So some people refer to investment factors as sources of "Alpha".

Academic Factor Research

Over the past 30 years, academic researchers have attempted to develop scientific models to explain the performance of the stock market over long periods of time. What factors cause one particular stock to do well compared to another? With 100 years of stock market history, researchers can run complex regression and statistical models to determine which measurable factors allow one stock to outperform another.

This research is generally performed by constructing sample portfolios. Using data on 3,000+ stocks, mostly from the last 30 years or so, researchers generally construct sample portfolios by sorting the data on the 3,000+ stocks using different criteria, or factors, like the size of the company, the profitability of the company, the price of the company's stock relative to earnings, etc... They then measure which of these sample portfolios perform better than the market as a whole.

For example, what happens if you construct a portfolio of the 100 stocks with the highest dividend yield? Does it perform better or worse than the market? If it performs better than the market, the researcher then applies advanced statistics to determine if the excess performance was statistically significant, or meaningful. Perhaps the excess performance was random luck.

The analysis gets more complicated because researchers have to form portfolios using multiple factors. What happens if you construct a portfolio of 100 stocks with the highest dividend yield and the lowest price to earnings ratio? What happens if you construct a portfolio of 100 stocks with the highest dividend yield, the lowest price to earnings ratio, and the lowest volatility? The statistics quickly get very complex.

Read our article on academic factor models for more information on this research.

Smart Beta ETFs Today

There are 776 smart beta ETFs in our database, out of the 1,392 equity ETFs that track indexes, or 56%. Here is a breakout of how many factors these ETFs are using:

Factors UsedNumber of ETFs%
016611.93%
128420.40%
21238.84%
31077.69%
4876.25%
570.50%
610.07%
710.07%
Total1,392

The industry continues to launch smart beta ETFs:

Year of InceptionCount
200017
20013
20035
200414
200531
200671
200741
20089
20096
201029
201136
201235
201334
201438
201584
201676
201774
201862
201976
202035
Total776

Despite the number of newly launched smart beta ETFs, smart beta ETFs have not yet captured a huge market share. ETFs that track passive indexes continue to dominate trading volumes:

Number of factorsAverage VolumePercentage
01,057,164,07793.22%
142,742,4093.77%
214,182,6591.25%
312,127,4711.07%
47,664,2400.68%
5132,2020.01%
6690.00%
734,4390.00%
Total1,134,047,566100%

Is this a good idea?

The number and complexity of smart beta ETFs is starting to be overwhelming. They are using a wide variety of approaches, and you have to carefully study the fine print. Most are using indexes that were just recently invented, and many do not have theoretical backtest data showing how the index would have performed in the past. As a result, there are some newly launched smart beta ETFs where it is impossible to know whether they will be a good ETF or not.

One simple reason the ETF industry has grown is because there are too many actively managed mutual funds (8,000+), and it is difficult to filter through them to figure out what to buy. Smart beta ETFs are starting to become the same way. It takes so much research to figure out what they are doing that there are definitely times when it does not seem worth the effort.

Investors have to decide if smart beta ETFs are worth it. There are still many true believers in passive index investing. It is hard to argue too much with an investor who constructs a simple portfolio of three or four low cost ETFs. You can easily and cheaply own the world's stock market by buying three ETFs:

The one fact that most people tend to agree with is that over long periods of time, small cap stocks tend to outperform large cap stocks. So if you want to overweight your portfolio towards small cap stocks, you can inexpensively buy an ETF that tracks the S&P Smallcap 600 Index, such as IJR, the iShares S&P SmallCap 600 Index Fund ETF.

So not everyone would agree that you have to buy into the smart beta ETF mania. Nevertheless, there are some smart beta ETFs that seem compelling. We have tried to analyze each smart beta approach in a series of articles describing and analyzing each approach. Please read them.

Do smart beta ETFs have higher fees?

A first blush, smart beta ETFs don't seem to necessarily have higher fees than average. Average fees per our database:

CategoryFactors UsedETF CountAverage Expense Ratio
Global Equity04270.55%
Global Equity1940.50%
Global Equity2430.48%
Global Equity3260.47%
Global Equity4350.57%
Global Equity520.37%
US Equity 03550.52%
US Equity 11900.35%
US Equity2800.41%
US Equity 3810.42%
US Equity 4520.42%
US Equity 550.26%
US Equity 610.25%
US Equity 710.35%

This is a little bit deceiving however. The ETF industry has gotten very competitive, pushing fees lower and lower. ETFs based on broad market indexes like the S&P 500 and the S&P Small Cap 600 Index have gotten very cheap. So smart beta ETF fees are definitely higher than the fees associated with these well-known market indexes.

Historically, which ETFs have outperformed?

We all know that past performance does not guarantee future returns. But if you look at the data on U.S. equity broad market ETFs with at least an eight year history, the evidence seems to definitely show that small and mid cap stocks outperform large caps over the long term. Use our tool ETFs that have outperformed SPY since inception to analyze the data yourself.

In addition to small and mid cap stocks, other clear "winners" from this data seem to be:

Here are the smart beta ETFs that we have given a rating of "editor's choice", our highest rating:

SymbolDescriptionInception DateCategoryActions
CAPEBarclays Shiller CAPE Index ETN10/10/2012US Equity Analyze
CZAInvesco Mid-Cap Core ETF04/02/2007US EquityAnalyze
DLSWisdomTree International SmallCap Fund ETF06/16/2006Global Equity Analyze
DVYEiShares Emerging Markets Dividend ETF02/23/2012Global EquityAnalyze
DWPPFirst Trust Dorsey Wright Peoples Portfolio ETF08/29/2012US Equity Analyze
EEMDAAM S&P Emerging Markets High Dividend Value ETF11/28/2017Global EquityAnalyze
EESWisdomTree SmallCap Earnings Fund ETF02/23/2007US Equity Analyze
EZMWisdomTree MidCap Earnings Fund ETF02/23/2007US EquityAnalyze
FBTFirst Trust NYSE Arca Biotechnology ETF06/19/2006US EquityAnalyze
FDTFirst Trust Developed Markets Ex-US AlphaDEX ETF04/18/2011Global Equity Analyze
FLQEFranklin LibertyQ Emerging Markets ETF06/01/2016Global EquityAnalyze
FNDESchwab Fundamental Emerging Markets Large Company ETF08/15/2013Global Equity Analyze
FNDCSchwab Fundamental International Small Cap Company Index ETF08/15/2013Global Equity Analyze
FPXFirst Trust US Equity Opportunities ETF04/12/2006US Equity Analyze
IDLVS&P International Developed Low Volatility ETF01/13/2012Global EquityAnalyze
IPKWInvesco International BuyBack Achievers ETF02/24/2014Global Equity Analyze
MOATMarket Vectors Morningstar Wide Moat ETF04/24/2012US EquityAnalyze
MTUMiShares MSCI USA Momentum Factor ETF04/16/2013US Equity Analyze
PKWInvesco Buyback Achievers ETF12/20/2006US EquityAnalyze
PSJInvesco Dynamic Software ETF06/23/2005US EquityAnalyze
PTLCPacer Trendpilot 750 ETF06/12/2015US Equity Analyze
PTMCPacer Trendpilot 450 ETF06/12/2015US EquityAnalyze
PTNQPacer Trendpilot 100 ETF06/12/2015US Equity Analyze
QTECFirst Trust NASDAQ-100-Technology Sector ETF04/19/2006US Equity Analyze
RPGInvesco S&P 500 Pure Growth ETF03/01/2006US Equity Analyze
SPHQInvesco S&P 500 Quality Portfolio ETF12/06/2005US Equity Analyze
SPLVS&P 500 Low Volatility Portfolio ETF05/05/2011US Equity Analyze
SZNEPacer CFRA-Stovall Equal Weight Seasonal Rotation ETF07/23/2018US Equity Analyze
VSDAVictoryShares Dividend Accelerator ETF04/17/2017US Equity Analyze
XMLVInvesco S&P 400 Low Volatility ETF02/12/2013US EquityAnalyze
XSHDInvesco S&P SmallCap High Dividend Low Volatility ETF11/29/2016US Equity Analyze


All data is a live query from our database. The wording was last updated: 04/10/2020.

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