A Smarter Way to Build Factor Models
By Don Schreiber, Jr. - WBI Founder and CEO
(Printable PDF available below)
The evolution of investment vehicles made what we would consider a major leap in the 1990s with the introduction of the exchange-traded fund (ETF). Investors could now purchase a product that tracks an index, providing diversification on an exchange throughout the day in a more accessible and tax-efficient vehicle.* Over time, managers realized that the problem with these products was their returns mirrored the indexes they tracked, never better. In the hunt for better performance, the money management industry developed Smart Beta, factor models, and even actively managed products. While many of these next-generation products with catchy names can help investors capture return during bull markets, can they protect capital from large bear market losses? Or is there something that can do more? *relative to traditional investments
Smart beta has become the catch-all industry term for passive investment strategies that use alternative weightings to constitute and rebalance an index rather than using the traditional, market capitalization weighting found in most passive index products. Smart beta is still a passive product, but one that rebalances using a different security selection and/or weighting criteria other than capitalization. The first smart beta products were offered using equal weighting, which tends to improve performance over long periods of time by reducing concentration into the largest companies with the biggest capitalization weights.1
SINGLE FACTOR SMART BETA
Next came approaches that favored stock weightings based on single factors by grouping stocks with similar characteristics such as quality, size, momentum, dividends, low volatility, or value. While a single factor can lift return and provide modest risk reduction, they seem to have cycle bias and work well in market trends that favor a particular factor. This single factor weakness can expose investors to the possibility of long-term underperformance when market trends turn unfavorable for a particular single factor model.
An example of this would be a portfolio of stocks that exhibit a low volatility factor, which means they have less price volatility on average than other high volatility stocks. While stocks with low volatility characteristics tend to have less price volatility on average, they are likely to fall precipitously in a secular bear market.
MULTI-FACTOR SMART BETA
Failure to meet the hyped up loss protection benefit of single factor products could leave investors with larger losses than they are willing to tolerate based on our experience. Managers found you can improve investor outcomes by combining the most powerful factors together to build smarter security selection models that aim to control risk and elevate return.
There are virtually hundreds of different fundamental and technical factors you can use to build security selection models. While single factor models are an improvement over traditional passive indexes, we view multi-factor models as the future of smart beta product design and modeling. The number of factors used varies by manager or fund, but the idea is that by combining different factors, you can achieve better security selection.
CREATING MORE SUCCESSFUL OUTCOMES WITH WBI’S QUANTITATIVE MULTI-FACTOR APPROACH
WBI’s investment process is time-tested, helping protect clients’ capital through good and bad market cycles over the past 25 years. Integrating financial and technical factors into quantitative security selection models is part of our firm’s DNA. WBI’s research team has been enhancing our factor models that drive our quantitative security selection process for nearly three decades. We continually look for ways to refine our models and enhance performance by identifying the highest yielding dividend-paying stocks that are also highest ranked by our multi-factor fundamental, technical, and trend models.
COMBINING THE MOST POWERFUL SINGLE FACTORS INTO POWER FACTOR® MODELS
The goal of WBI’s quantitative security selection process is to identify the best candidates to buy each day. We have identified what we consider the most powerful factors to drive performance. When combined, these proprietary Power Factor models become what we believe are the “best-in-class” multi-factor solutions, giving us smarter security selection that helps to enhance price appreciation, increase dividend capture, and lower risk.
WBI’S DYNAMIC ACTIVE RISK MANAGEMENT OVERLAY
While we believe powerful security selection is paramount to achieving success, our research has shown that protecting capital from large bear market losses has been up to seven times more powerful than attempting to “buy and hold” passive index portfolios to maximize bull market returns.2 Albert Einstein said compounding is the eighth wonder of the world and the most powerful financial force in the universe.
The goal of WBI’s risk management process is to limit losses in bear markets to increase compounding efficiency by compounding on a larger sustained capital base. Components of our active risk management overlay are utilized across all of our products — whether passive or active — and can be applied in various ways. When return trends turn broadly negative in bear markets we believe the best strategy is to raise cash to protect capital. To facilitate this, we have no mandate to stay fully invested in most of our products. And when trends reverse and markets begin to recover, WBI’s Power Factor models take over to select the best opportunities to “buy low and sell high”.
We use risk management to define portfolio outcomes that can stay within a client’s risk and capital loss tolerance. Without active risk protection, clients tend to “buy high and sell low,” the exact opposite of what they need to do to be successful. Most importantly, WBI’s risk management process has met the “acid test”, protecting clients’ capital by curbing losses in the 2000 Dot-com bear market and 2008 Financial Crisis relative to the S&P 500. We believe the combination of our advanced factor security selection models with an overlay of dynamic risk management is a revolutionary leap forward in investment product development.
Past performance does not guarantee future results. The views presented are those of Don Schreiber, Jr. and should not be construed as investment advice. Don Schreiber, Jr. or clients of WBI may own stock discussed in this article. All economic and performance information is historical and not indicative of future results. This is not an offer to buy or sell any security. No security or strategy, including those referred to directly or indirectly in this document, is suitable for all accounts or profitable all of the time and there is always the possibility of loss. Moreover, you should not assume that any discussion or information provided here serves as the receipt of, or as a substitute for, personalized investment advice from WBI or from any other investment professional. To the extent that you have any questions regarding the applicability of any specific issue discussed to your individual situation, please consult with WBI or the professional advisor of your choosing. This information is compiled from sources believed to be reliable, accuracy cannot be guaranteed. Information pertaining to WBI’s advisory operations, services, and fees is set forth in WBI’s disclosure statement in Part 2A of Form ADV, a copy of which is available upon request. You are not permitted to publish, transmit, or otherwise reproduce this information, in whole or in part, in any format to any third party without the express written consent of WBI Investments, Inc.
Although a company may pay a dividend, prices of equity securities – including those that pay dividends – fluctuate. Investing on the basis of dividends alone may cause an investor to buy or sell certain securities when circumstances may or may not be favorable.
1 Picardo, Elvis, CFA. "A Pioneering Smart Beta ETF." Investopedia. 09 Sept. 2016. Web. 23 May 2018.
2 Schreiber, Don. The Ugly Truth About Buy and Hold. 2018.