What Smart Beta Can’t Do

October 14, 2015

The growth of assets in Smart Beta ETFs is staggering. From Michael Batnick:

Investors have become enamored with alternative ways to slice and dice the indices. According to Morningstar, “Strategic Beta” now accounts for 21% of total industry (ETP) assets, up from under 5% in 2000. As assets have exploded, so too has the number of strategic-beta ETPs, which have grown from 673 to 844 in the past year, while assets grew 25% to $497 billion.

While much of the focus is on the nomenclature- “smart” vs. “factor” vs “strategic,” perhaps the most important aspect is being overlooked; like all things investing, the product won’t to be drive returns as much as your behavior will.

growth 1 What Smart Beta Cant Do

growth 2 What Smart Beta Cant Do

To demonstrate this point, I chose five popular strategies that differ from the traditional plain vanilla cap-weighted index: Nasdaq US Buyback Achievers Index, S&P 500 Equal Weight Index, Nasdaq US Buyback Achievers, MSCI USA Momentum Index and the S&P 500 Low Volatility index.*

Every one of these Smart Beta strategies has outperformed the S&P 500 from 2007-today**. The problem investors run into, as you can see below, is that very often the best performing in each year lagged the S&P 500 in the prior year. Myopia is a huge impediment to successful investing as much of our “discipline” is driven by “what have you done for me lately?”

quilt What Smart Beta Cant Do

Each of these five strategies has outperformed the S&P 500 over the previous eight years.

Had you chased the prior year’s best strategy, you would have compounded your money at just 3.5%, less than the 6% you would have earned if you invested in the prior year’s worst strategy. This goes to show that mean reversion is a powerful force for a proven, repeatable process.

Interesting. There are all kinds of studies showing that when it comes to individual stocks, buying last year’s winners works great (click here for just one of the white papers written on this topic). However, Batnick is arguing that buying last year’s winning Smart Beta ETF is not effective (at least in this short sample) when it comes to investment factors.

This has important implications for building an asset allocation that includes a variety of Smart Beta factors: You may well be better off simply seeking to identify those factors that are likely to outperform over time (we like momentum and value in particular) and make passive allocations to those factors rather than trying to time your exposure to them.

Smart Beta has, in our view, been a tremendous positive for investors. However, it won’t keep performance-chasing investors from hurting themselves if they fail to allocate money to them in a prudent way.

Past performance is not indicative of future results. Potential for profits is accompanied by possibility of loss.

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When Theory Meets Reality

October 14, 2015

Ben Carlson’s concise evaluation of mean-variance optimization:

One of the students asked for my thoughts on the efficient frontier and mean-variance optimization. I told them that the general idea behind these theories has been very helpful to the portfolio management industry in a number of ways. Diversification and the idea that adding together investments that behave differently in a portfolio is an important concept.

But you can’t take these types of models literally. Correlations and market relationships are constantly changing. Nothing is stable and the past isn’t a perfect window into what’s going to happen in the future. The efficient frontier shows you the best risk-adjusted returns from a historical data set. It can’t tell you what the perfect asset allocation will be in the future.

Models and textbook theories can play a role in building your knowledge base, but they never tell the whole story. Many people make the mistake of taking them at face value without thinking through the real world implications. No model is perfect, so the majority of the time what really matters is the interpretation by the end user.

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High RS Diffusion Index

October 14, 2015

The chart below measures the percentage of high relative strength stocks (top quartile of our ranks) that are trading above their 50-day moving average (universe of mid and large cap stocks.) As of 10/13/15.

diffusion High RS Diffusion Index

The 10-day moving average of this indicator is 54% and the one-day reading is 65%.

This example is presented for illustrative purposes only and does not represent a past recommendation. The performance above is based on pure price returns, not inclusive of dividends or all transaction costs. Investors cannot invest directly in an index. Indexes have no fees. Past performance is not indicative of future results. Potential for profits is accompanied by possibility of loss.

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