(December 17, 2013) – Ever wondered which smart beta strategies perform best in the short and long term? ERI ScientificBeta, a venture from the EDHEC-Risk Institute, has compared and contrasted more than 2,000 indices with some surprising results.
Comparing the performance of smart factor indices first—those that abandon market cap weighted indices in favour of factor-weighted indices, such as liquidity or volatility—ERI ScientificBeta found that all diversified multi-strategy indices outperformed market cap weighted ones over the long term.
In its November Smart Beta Performance Report, strategies using book-to-market (a ratio used to find the value of a company by comparing the book value of a firm to its market value), dividend yield, size, liquidity, and volatility were all compared over a one month, year-to-date, and long term (since 1970) track records.
The highest performing indices were the small cap index, and the high book-to-market index, which produced 2.75% and 2.73% returns over the long term. The high book-to-market index also exhibited the highest information ratio.
When assessing the year-to-date returns, some of the strategies experienced losses, although the authors of the report pointed out this was expected, as these strategies tend to experience return fluctuations in accordance with the variation in risk premiums associated with these factor tilts.
In addition, some of the indices experienced larger return spreads than others: volatility indices displayed the biggest spread with returns of 5.28% since the start of 2013 for the high volatility index compared to a loss of 2.03% for the low volatility index.
Next, ERI ScientificBeta compared the more vanilla, plain diversification strategies, including diversified a risk parity strategy and an efficient maximum Sharpe ratio strategy.
Again, over the long term (here, since inception in 2002), all diversification schemes posted positive returns. The best performance was delivered by the efficient minimum volatility index, with a Sharpe ratio of 0.66. However, this strategy was also the one with the largest tracking error, meaning it had the lowest information ratio.
When considering the information ratio, which measures the risk-adjusted relative performance, a diversified risk parity strategy takes the lead, with a Sharpe ratio of 0.97.
Over a shorter period—year-to-date—only the efficient minimum volatility strategy made a loss. The best performing over the past 11 months was the maximum decorrelation strategy, posting a return of 1.64%.
Finally, ERI ScientificBeta considered how much of an impact the geographical location of investors’ money made. The short answer is: not much.
When considering the best and worst performing indices since inception—taking into account 2,442 of ERI ScientificBeta’s indices—all of the top three performers and two of the bottom three performers were based in the Asia-Pacific (ex-Japan) region, suggesting that the right strategy matters more than where you invest.
The top three strategies since inception were the Developed Asia-Pacific (ex-Japan) value maximum decorrelation index (sector neutral), the same region’s value efficient maximum Sharpe ratio index, and the value maximum decorrelation from the same region.
The worse performing indices were a high-volatility efficient minimum volatility index from the same Asia-Pacific (ex-Japan) region, followed by a high-volatility efficient maximum Sharpe ratio index. The third worst performer was a developed Europe strategy, also using a high volatility efficient maximum Sharpe ratio index.
However, over the past year, the tables are reversed, and it’s the high volatility maximum deconcentration and decorrelation strategies which are the top performers, primarily across Japan and the Eurozone.
The poorest performers in the past year were efficient minimum volatility strategies. This, the report said, was driven by the recent bull run in equities—minimum volatility strategies perform best in bear markets.
Earlier this year, EDHEC challenged investors to think about smart beta in a “2.0” way, recommending that the choice of systematic risk factors for smart beta benchmarks should be explicit, and made by the investor, not the index promoter.