Mike Akins heads up the exchange-traded fund division for ALPS Advisors and serves as the lead portfolio manager for the ALPS ETF Trust. We recently sat down with Akins, who will be speaking at our 2nd Annual Smart Beta Strategies Summit(Oct. 26 – Boston) and got his views regarding creating a mix of factor strategies designed to fit an investor’s market assumptions, risk tolerances and investment needs.
Financial Advisor magazine: In your opinion, how many smart beta factors are there?
Mike Akins: To start, as with most of our colleagues in the industry, at ALPS we believe “smart” beta is not the best way to define factor-based strategies. That said, there is clear academic evidence supporting six broad factors that have delivered alpha over full market cycles (Quality, Low Volatility, Value, Dividend Payers, Momentum and Size). To this extent, we believe there are six basic factor “categories;” however, there are several different factors or combinations of factors to gain access to these categories.
Further, the level of conviction (Active Share), weighting methodology and implementation (rebalance frequency) that each strategy utilizes can significantly change the outcome. For these reasons, I would answer this question by saying that factors are nearly endless but should aim to result in a strategy that fits within the one of the six academic supported alpha factor categories.
Which strategy used by investors should be determined based on their individual risk tolerance and desired investment outcome.
FA: Can factor cyclicality be used to generate alpha?
Akins: Short answer is yes, but this has historically proven to be extremely difficult. It is not about timing the market, but more about your time in the market. At ALPS, we believe that multiple factors should be used to design a portfolio, which meets the investment objectives of each investor or group of investors and rebalance along the way. For example, an aggressive investor may choose to equally allocate to high conviction value and momentum, rebalancing based on set thresholds in an effort to achieve max outperformance over a full market cycle.
On the other hand, a retired investor who has less risk tolerance and greater need for income may choose to blend Quality, Low Volatility and Dividends in an allocation that best meets his or her drawdown risk and income needs.
This does not mean that tactical over or underweighting can’t be implemented successfully based on market assumptions, relative valuations or other observations. Rather, we believe the best use for most investors is a more stable allocation target designed to their unique investment objectives.
FA: How do you link factor-based strategies to outcomes?
Akins: The previous two answers broadly answered this question but will try to elaborate more. One of the greatest benefits, in our opinion, of rules-based factor strategies is the abundance of data, which can be analyzed across varying market cycles. This combined with the consistency and transparency of rules-based strategies provides investors the ability to create a mix of factor strategies designed to fit their market assumptions, risk tolerances and investment needs.
This is why we believe ETFs are best described as tools and while some tools are better than others, what really matters is properly selecting the best tools for the job at hand.