ETF

Should smart-beta ETFs have a spot in your investment portfolio?

The ETF industry has come a long way since 2000. From a measly $100 billion in ETF assets at the start of the century to a $4.7 trillion beast, as of March 2018. Over the next 5 years, ETF assets are projected to double.

For more information on the figures quoted above and the research behind it, refer to the attached white paper from Blackrock: Blackrock White Paper – Four Big ETF Trends

The proliferation of ETFs in the past decade has resulted in the rise of smart-beta ETFs in the fund industry. The ‘traditional’ ETFs are typically plain-vanilla ETFs that follow a ‘traditional’ index that gives investors a broad market exposure.

The methodology for the ‘traditional’ index/benchmark is based on weighted market capitalisation. That is, the securities’ weightage in the index/benchmark is based on the securities’ market capitalisation. The higher the security’s market capitalisation, the higher the allocated weight is for the said security in the index/benchmark.

Smart-Beta

Smart-beta ETFs follow a ‘smart’ index. Instead of selecting and weighting securities into a benchmark based on its market capitalisation, a ‘smart’ index incorporates investment subfactors such as the price-earnings ratio, sales projections and etc in its securities selection and weighting methodology.

These investment subfactors tend to revolve around investment factors such as value and growth.

Issues with smart-beta ETFs

The key issue with smart beta ETFs is that there is no consensus and consistency across index issuers on which investment subfactors constitutes as ‘smart’ for the same investment theme/factor. The reason is that every index issuers may take a different stance toward the same investment theme.

For example, consider the value theme. The objective of value investing is to look for stocks that trade for less than their intrinsic/book value. In order to look for such stocks, investors typically look at different investment subfactors such as price-earnings ratio, price-book ratio, etc.

During the construction of the index to reflect value, different index issuers view these investment subfactors differently. For example, some may view the price-earnings ratio as an insignificant factor to reflect value while some may view it otherwise. In this instance, who is correct? I am afraid there is no definitive way to suggest one is definitely better than the other.

To further illustrate my point, I have compiled the investment subfactors for a value benchmark from two different index issuers, CRSP and S&P Dow Jones Indices.

CRSP (The Center for Research in Security Prices)

The value index from CRSP is called the CRSP US Large Value Index. It consists of 5 investment subfactors as follows; 1) book to price, 2) forward earnings to price, 3) historical earnings to price, 4) dividend to price, 5) sales to price.

It adopts a multi-factor approach to the index weighting and selection methodology. An example of an ETF that tracks this benchmark is the Vanguard Value ETF (VTV). For more information on VTV, see: https://www.etf.com/VTV

S&P Dow Jones Indices

The value index from S&P is called the S&P 500 Value Index. It consists of 3 investment subfactors as follows; 1) book value to price, 2) earnings to price, 3) sales to price.

It adopts a market-cap approach to index weighting and a fundamental approach to index selection. An example of an ETF that tracks this benchmark is the Vanguard S&P 500 Value ETF (VOOV). For more information on VOOV, see: https://www.etf.com/VOOV

I believe by now, you can see the problem with this ‘smart’ approach towards index construction. Which investment subfactor will prevail over the long run? Nobody knows for sure.

For more information on CRSP benchmarks, see: http://www.crsp.com/products/investment-products/crsp-us-large-cap-value-index

For more informtion on S&P Dow Jones Indices benchmarks, see: https://us.spindices.com/indices/equity/sp-500-value

What actually is smart-beta then?

Smart-beta is a blend of passive and active investing, and in my opinion tilting towards active management. It is passive in the sense that an index mutual fund or ETF can be created to track the smart index, and it is active in the sense that the smart index incorporates investment factors into its security selection and weighting methodology.

Instead of using the ‘traditional’ weighted market capitalization to construct an index, smart-beta follows a systematic rule-based approach towards index construction. These rules are oriented within an investment theme but they can differ across different index issuers for the same investment theme. However, these rules while systemic can be subjective in nature, similar to a traditional active manager.

I guess the fund industry has managed to find a fancier term and may I say, a ‘smarter’ term for active management (smart Pun intended – super pun!!!).

Is smart-beta ETFs better than ‘traditional’ ETFs?

Let’s define better as having a higher NAV performance. For the purpose of this performance comparison, I have select two smart-beta ETFs from two different investment themes (growth and value) and compare them against a broad market ETF.

For the growth theme, I have selected VUG, for the value theme, I have selected VTV and for the broad market ETF, I have selected IVV. As of 11 September 2019, the 10 years annualised NAV performance for IVV stood at 13.46%, VUG comes in at 14.67% and VTV at 12.33%.

VUGVTVIVV

Based on the performance of VUG/VTV/IVV, growth theme (VUG) seems to be outperforming the broad market (IVV) and the value theme (VTV) for the past 10 years, by an annualised 1.21% and 2.34% respectively. 

Note that the value theme (VTV) seems to be underperforming the broad market (IVV) for the past 10 years, by an annualised 1.13%.

Sector bias in growth theme

One common characteristic in the growth theme is the sector tilt to the technology sector, i.e. growth theme ETFs holds more technology stocks than the broad market and value theme ETFs. For example, as at 11 September 2019, technology allocation in VUG stands at 45.06%, IUSG at 34.77%, MGK at 48.54%, VOOG at 35.82%.

Whereas, technology allocation in the broad market and value theme seems to be trailing far behind. For the same period, technology allocation in IVV (broad market) stands at 26.91%, VTV at 8.65%, IUSV at 16.09%, MGV at 9.04%.

Unless you have been living under a rock, you would have known that technology companies such as Google, Amazon, Microsoft, Facebook and etc, have been delivering above-market returns for the past few years. This would explain the outperformance of the growth theme as compared to the value theme and the general market.

Note that the above comparison is not extensive to conclude that growth is the real winner here. Furthermore, this outperformance may not persist in the future as there is no real way of telling which investment theme/subfactors will prevail over the long run. Past performance is not an indicator of future performance.

For more information on IVV, see: https://www.etf.com/IVV

For more information on the growth ETFs listed above, see:

https://www.etf.com/VUG

https://www.etf.com/MGK

https://www.etf.com/VOOG

https://www.etf.com/IUSG

For more information on the value ETFs listed above, see:

https://www.etf.com/VTV

https://www.etf.com/IUSV

https://www.etf.com/MGV

Types of investment factors

The common types of investment factors/themes used to construct indexes are growth, value, momentum, quality, size and low volatility. Each of these investment factors has its own investment objective. The investment objective of a smart-beta ETF will be similar if not the same as the factor’s investment objective. For example, if an ETF is tracking a value index, the ETF would have the same investment objective as value investing.

Multifactor ETFs

All the ETFs listed above are single-factor ETFs which, as the name implies, looks at only one investment factor/theme.  Multifactor ETFs, on the other hand, tracks benchmarks that look at multiple investment factors/themes.

For example, the Goldman Sachs ActiveBeta U.S. Large Cap Equity ETF (GSLC) tracks the Goldman Sachs ActiveBeta U.S. Large Cap Equity Index. The index looks at four different subindexes that track 4 different investment factors. The 4 investment factors are as follows: value, momentum, quality and low volatility.

For more information on GSLC, see: https://www.etf.com/GSLC

For more information on the index, see the attached methodology paper from Goldman Sachs: Goldman Sachs – ActiveBeta Index Methodology

Should you invest in smart-beta ETFs?

Yes to some extent.

If you are going to take an active view on the market, using ETFs will be a more cost-effective approach to do so than using mutual funds especially when it comes to the more popular themes such as value and growth. For example, if you want to invest in the growth theme, you can invest in VUG for as little as 0.04%. Furthermore, the range and granularity of smart-beta ETFs are getting wider and finer. There is an ETF for everyone who wants to take on a very specific theme.

There are ETFs for every imaginable theme: marijuana, space, disruptive technologies, medical, gaming, shipping, water, triple leveraged, etc. Heck, there is even an ETF targeted towards the Millenials (check out: https://www.etf.com/MILN)

Conclusion

A word of caution, in general, the more exotic the ETF, the more expensive it is to invest and the trading volume tends to be lower as well for the more exotic ETFs. This would drive up your overall total cost of investment. Exotic ETFs also tend to be less diversified than the broad market ETFs.

While smart-beta ETFs offer a very compelling proposition for investors to take on a ‘unique’ exposure, it does not necessarily mean that you should invest in one. While fads come and go, a broad market ETF should always have the highest priority in your portfolio.

As always, take personal responsibility of your financial well-being and do your own due diligence.

 

 

Disclaimer: This article does not constitute a solicitation to buy/sell any securities that may be mentioned in this article. At the time of writing and publication, the author does not hold any position in any of the securities mentioned in this article. I am writing in my personal capacity and my views do not represent that of any organisations.  

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