The traditional choices: active vs. passive
For the past 35 years, investors have had two choices. If they believed markets were largely efficient, they chose to invest through capitalization-weighted index funds. If they believed markets were inefficient, they picked active management.
But both approaches are inherently flawed
Both approaches have their problems. Cap-weighted equity index funds tend to overweight overvalued securities and underweight undervalued ones, creating a 2% return drag in developed markets and more in less efficient ones, according to our research. Active management is not transparent, comes with high fees, and tends to underperform the benchmark over long time periods.
Traditional bond index investing is also flawed
Bond indices give the biggest weights to the biggest debtors; this situation is particularly acute for sovereign bonds, where some developed market nations have sought to drive down yields, creating inefficiencies in the market and failing to reward investors for the risks they are taking.Overview
Smart beta strategies offer a third choice
Smart beta strategies, such as non-price-weighted indices, offer a third choice. These strategy indices retain the benefits of traditional capitalization-weighted indices, such as broad market exposure, diversification, liquidity, transparency, and low cost access to markets. At the same time, they offer the opportunity to achieve superior performance over the cap-weighted benchmark.
Smart beta strategies can be simple or complex
Smart beta strategies fall into two camps: 1) heuristic-based weighting strategies, which are based on simple and sensible rules, and 2) optimization-based weighting strategies, which are complex and subject to problems with estimating returns and covariances.
Heuristic based vs. optimized strategies
Popular heuristic-based weighting schemes include equal weighting, fundamentals weighting, risk-clusters equal weighting (equal weights risk clusters instead of individual stocks), and diversity weighting (combines equal weighting and cap weighting). Popular optimized strategies include minimum variance, maximum diversification, and risk efficient indices.
Strategies outperform the cap-weighted benchmark
All of these smart beta methodologies produce excess returns compared to the cap-weighted benchmark over long periods of time, based on a simulation in a 2011 paper by Chow, Hsu, Kalesnik and Little. They conclude that each of these strategies shares the same investment insights of a naïve equal weighted strategy—they all break the link between market prices and index weights. Seen from another perspective, the smart beta strategies inherently have value and small size tilts relative to cap-weighted benchmarks. Thus, investors should look closely at implementation costs, such as excess turnover, reduced liquidity, and decreased investment capacity, in choosing a strategy.
Low volatility stocks: a different take on risk
Another recently popular smart beta strategy is to create a portfolio of low volatility stocks. Like other smart beta strategies, it breaks the link between price and weight. All “pure” low volatility portfolios should earn a return premium of about 2% in the United States with about 25% less absolute risk than the benchmark. However, these strategies tend to have high tracking error.
High tracking error vs. low downside risk
The challenge for investors is to figure out whether they are more concerned about “relative risk,” which is measured by tracking error, or more concerned about “absolute return,” focused on avoiding sharp declines in returns regardless of benchmark performance. Research shows that in an ideal world, investors should prefer to invest 100% in low volatility strategies, but most portfolio managers run their portfolios with an eye on the benchmark.
Creating the core portfolio
It is very difficult for a single portfolio to provide both a relative risk and an absolute risk approach. The more one wants to shift from a relative approach to an absolute one, the more one will have to disregard large portions of the market and accept greater tracking error. Investors who are willing to take some tracking error risk, but are not willing to go all in, can pursue a combination of absolute risk and relative return strategies.