Smart Beta Performance Report by Scientific Beta

Introduction

Recent years have seen the development of numerous smart beta indices whose weighting schemes differ from those of cap-weighted indices. Smart beta indices may be obtained by tilting economic factors, such as book-to-market, size or volatility, or by introducing greater diversification into the index, as illustrated in multi-strategy indices. The positive performance of smart beta indices over the long term has been largely documented in the literature. However, these indices are exposed to risk factors that are different from those of cap-weighted indices and that may cause variations in performance over short periods. As a result, the presentation of long-term performance is not enough for investors, who are also demanding performance figures over recent and shorter periods. The present report gives a complete picture of smart beta index performance with both long-term and short-term figures that illustrate the variations in performance over the different time periods, as well as the variations in performance between the various strategies. As a result, combining the various smart beta strategies makes it possible to obtain more robust performance.

Performance for smart factor indices exposed to risk factors known to be well rewarded over long periods remains strong with annual performance in excess of broad cap-weighted indices ranging from 1.03% to 3.11% since inception for the Developed universe. Over shorter periods, the strategies are exposed to fluctuations depending on variations in market conditions. For investors willing to take tactical bets, ERI Scientific Beta offers sixteen smart factor indices.

This month, the best performing index among those smart factor indices is the SciBeta Developed Low Liquidity Diversified Multi-Strategy index, with a relative return of 1.10% compared to the broad cap-weighted index, while the SciBeta Developed High Liquidity Diversified Multi-Strategy index posts the lowest relative return (0.03%).

Scientific Beta Multi-Beta Multi-Strategy (MBMS) indices associate an effective choice of weighting scheme, in terms of diversification, with an allocation to well-rewarded smart factors, to prevent indices from being too concentrated in one factor and to reduce their specific risks. Over the past ten years, the SciBeta Developed Multi-Beta Multi-Strategy EW (Equal Weights) index and the SciBeta Developed Multi-Beta Multi-Strategy ERC (Equal Risk Contribution) index post strong annual relative returns of 1.93% and 1.82%, respectively, compared to cap-weighted indices. This month, the SciBeta Developed Multi-Beta Multi-Strategy EW index and the SciBeta Developed Multi-Beta Multi-Strategy ERC index post relative returns of 0.62% and 0.58%, respectively, compared to cap-weighted indices. Looking at MBMS indices for various regions, we note that this month the best performing indices are the SciBeta Developed United States Multi-Beta Multi-Strategy indices, with a relative return of 1.22% for the EW scheme and 1.19% for the ERC scheme compared to the broad cap-weighted index, while the worst performing indices are the SciBeta Developed Europe ex-UK Multi-Strategy indices, with a relative return of
-1.07% for both the EW and ERC schemes compared to the broad cap-weighted index.

This month, all four factors that make up the MBMS indices, namely value, momentum, high volatility and mid capitalization, performed better than the regional broad cap-weighted indices in the United-States and Developed regions, and contributed positively to the relative performance of the corresponding MBMS indices. In the Developed Asia Pacific ex-Japan and the Developed ex-USA regions, relative MBMS performance was positively driven by the relative performance of the high momentum and mid-cap factors and negatively driven by the relative performance of the value and low volatility factors. In the UK and Japan, three factors out of four – value, momentum and mid-cap in the UK; momentum, low volatility and mid-cap in Japan – performed better than the broad regional cap-weighted indices and contributed positively to the relative MBMS performance of the MBMS indices, while the relative performance of the fourth factor – high volatility in the UK and value in Japan – contributed negatively. Not surprisingly, the developed Europe ex-UK region, where we observed the poorest relative performance this month compared to the broad regional cap-weighted index for the MBMS indices, is also the only one for which we observe negative relative performance for three factors out of four, namely momentum, low volatility and mid-cap.

Performance Overview for Smart Factor Indices for the Scientific Beta Developed Equity Universe and Long-Term US Data Series

Tables 1a and 1b display the performance of SciBeta Developed Diversified Multi-Strategy indices. The eight tilts selected – book-to-market, dividend yield, size, liquidity, volatility, momentum, investment and profitability – are the common tilts documented in the literature as liable to produce outperformance compared to cap-weighted indices. The tables present performance statistics for both high and low stock selections by factor tilt. All these indices serve to create a diversified portfolio of the relevant stocks. In particular, they draw on different smart beta weighting schemes[1], which we refer to as a diversified multi-strategy index. In addition, these indices offer investable proxies for smart beta factor indices. These indices allow investors to be both exposed to a specific risk factor (beta) and to have good diversification of other risk factors, leading to an attractive Sharpe ratio associated with the factor tilt. Table 1c displays the performance of long-term US data series based on the same factor selection and weighting scheme, the initial reference universe of these long-term US data series being the 500 largest market-cap US stocks.

Table 1a: Short-Term Performance Overview for Smart Factor Indices for the Scientific Beta Developed Equity Universe

Diversified Multi-strategy Index for Past month (as of 31/03/2015) Year-to-date (as of 31/03/2015)
Absolute Return Relative Return compared to tilted cap-weighted Relative Return compared to broad cap-weighted Absolute Return Relative Return compared to tilted cap-weighted Relative Return compared to broad cap-weighted
High/low stock selections by High Low High Low High Low High Low High Low High Low
Book-to-market -1.24% -0.54% 0.42% 0.52% 0.10% 0.80% 2.80% 4.53% 1.71% 0.45% 0.13% 1.85%
Dividend Yield -1.29% -0.36% 0.55% 0.19% 0.05% 0.98% 2.45% 5.36% 0.72% 1.18% -0.23% 2.68%
Size -1.21% -0.36% 0.32% -0.12% 0.13% 0.98% 3.04% 4.30% 0.71% -0.29% 0.37% 1.63%
Liquidity -1.31% -0.24% 0.26% 0.02% 0.03% 1.10% 2.93% 4.41% 0.68% -0.24% 0.26% 1.73%
Volatility -0.73% -0.80% 0.45% 0.64% 0.61% 0.54% 4.36% 3.20% 0.44% 1.30% 1.69% 0.52%
Momentum -0.46% -1.24% 0.61% 0.40% 0.88% 0.10% 4.32% 3.12% 0.89% 1.26% 1.64% 0.44%
Investment -0.68% -1.02% 0.48% 0.49% 0.66% 0.32% 4.37% 3.32% 0.52% 1.70% 1.69% 0.65%
Profitability -0.77% -0.98% 0.76% 0.12% 0.57% 0.37% 4.54% 2.56% 1.12% 0.81% 1.86% -0.11%

The history of Scientific Beta Index returns begins on 21/06/2002. The statistics are based on daily total returns (with dividend reinvested). All statistics are annualised and performance ratios that involve the average returns are based on the geometric average, which reliably reflects multiple holding period returns for investors. ERI Scientific Beta uses the yield on Secondary Market US Treasury Bills (3M) as a proxy for the risk-free rate in US Dollars. All results are in USD.

Table 1b: Long-Term Performance Overview for Smart Factor Indices for the Scientific Beta Developed Equity Universe

Diversified Multi-strategy Index for Since Inception: From 21/06/2002 to 31/03/2015
Absolute Return Relative Return compared to tilted cap-weighted Relative Return compared to broad cap-weighted Volatility Sharpe Ratio Maximum Relative Drawdown Outperformance Probability (1Y)* Outperformance Probability (3Y)*
High/low stock selections by High Low High Low High Low High Low High Low High Low High Low High Low
Book-to-market 10.84% 9.87% 2.33% 1.59% 2.62% 1.65% 16.32% 14.69% 0.58 0.58 5.79% 6.08% 71.9% 70.9% 80.1% 96.2%
Dividend Yield 10.47% 10.17% 2.21% 1.99% 2.25% 1.95% 14.84% 15.99% 0.61 0.55 5.22% 8.32% 68.7% 70.4% 94.0% 94.3%
Size 9.81% 11.09% 2.02% 0.28% 1.59% 2.87% 15.52% 15.40% 0.54 0.63 3.58% 6.77% 80.6% 77.9% 93.7% 87.7%
Liquidity 9.87% 11.00% 2.18% 0.60% 1.65% 2.78% 16.39% 14.59% 0.52 0.66 4.37% 6.67% 74.7% 72.3% 90.4% 93.2%
Volatility 9.67% 10.86% 2.11% 2.30% 1.45% 2.64% 18.67% 13.18% 0.44 0.72 16.94% 9.20% 55.5% 63.2% 34.4% 94.8%
Momentum 10.74% 9.94% 1.84% 2.01% 2.52% 1.72% 15.13% 16.22% 0.62 0.53 12.00% 8.82% 72.6% 54.5% 77.9% 54.6%
Investment 9.56% 11.29% 2.15% 2.25% 1.34% 3.08% 16.14% 14.76% 0.51 0.67 8.23% 6.69% 58.5% 80.6% 58.7% 100.0%
Profitability 11.33% 9.25% 1.80% 2.62% 3.11% 1.03% 14.85% 16.06% 0.67 0.49 6.35% 11.10% 81.7% 45.3% 98.1% 9.3%

* Outperformance Probability 1Y and 3Y are computed over the latest 10-year period.

The history of Scientific Beta Index returns begins on 21/06/2002. The statistics are based on daily total returns (with dividend reinvested). All statistics are annualised and performance ratios that involve the average returns are based on the geometric average, which reliably reflects multiple holding period returns for investors. ERI Scientific Beta uses the yield on Secondary Market US Treasury Bills (3M) as a proxy for the risk-free rate in US Dollars. The tilted cap-weighted indices are obtained based on the same selection of assets as each of the smart factor indices. All results are in USD.

Table 1c: Performance Overview for Long-Term US Data Series

Diversified Multi-strategy Index for Long-Term US Track Records since 01/01/1974 (as of 31/12/2013): 40 years