IN THIS LIST

Outperformance in Equal-Weight Indices

Factor Performance Across Different Macroeconomic Regimes in India

How Smart Beta Strategies Work in the Hong Kong Market

Accessing China's Growth via Dividends

Limiting Risk Exposure with S&P Risk Control Indices

Outperformance in Equal-Weight Indices

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Craig Lazzara

Managing Director, Global Head of Index Investment Strategy

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Hamish Preston

Director, U.S. Equity Indices

INTRODUCTION

Equal-weight indices were among the first non-capitalization-weighted indices to emerge as templates for passive investments, or as benchmarks for the evaluation of active managers.1 Since their introduction, the concept has been extended to a wide range of markets and market segments, while products tracking equal-weight indices have attracted significant assets.

Exhibit 1 demonstrates one of the drivers of interest in equal-weight indices, namely their outperformance over their capitalization-weighted equivalents in a significant number of global equity markets.

This paper examines the sources of equal-weight index outperformance from various perspectives, including sectoral, factor-based, and constituentlevel analyses, and provides a guide to the potential applications of equalweighted investment strategies in a portfolio context. Highlights include the following.

  • We show how small size and (anti-) momentum biases typically arise in equal-weight equity indices, and we outline their respective impact on performance.
  • From a sectoral perspective, we show that—at least in the case of the S&P 500—a majority of historical outperformance was due to equal weighting within sectors, as opposed to differences in sector exposures.
  • We articulate an argument for equal weighting as a theoretically optimal strategy for return-seeking investors possessing limited stock-picking skills, and we examine the consequences of this perspective for active equity funds.
  • We illustrate the potential portfolio applications of equal-weight investments, particularly to complement either low-volatility or momentum-based strategies, or as a replacement for active funds.

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    Factor Performance Across Different Macroeconomic Regimes in India

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    Priscilla Luk

    Managing Director, Global Research & Design, APAC

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    Akash Jain

    Associate Director, Global Research & Design

    EXECUTIVE SUMMARY

    In response to increasing interest in smart beta strategies in the Indian equity market, this paper examines the performance of six factors—value, momentum, quality, low volatility, dividend, and size (small cap)—across different business cycles, market cycles, and investor sentiment regimes in India from October 2005 to June 2017.

    • Over the period studied, all six factor portfolios outperformed the S&P BSE LargeMidCap. The low volatility and quality factors showed reduced return volatility and the rest of the factors had more volatile return.
    • Quality and low volatility factors tended to be more defensive, while the dividend, value, and size factors displayed procyclical characteristics across different macroeconomic regimes.
    • Single-factor portfolios could potentially act as tools for implementation of active views, or alternatively they could be blended in multifactor porfolios that aim to deliver smoother excess return across business and market cycles.

    OBJECTIVE AND METHODOLOGY

    In the paper Factor Risk Premia in the Indian Market, we examined four factors—low volatility, momentum, quality, and value—in the Indian market based on quintile analysis and concluded that, historically, the low volatility and quality delivered factor risk premium. In this paper, we compared sector composition of factor portfolios and examined performance characteristics of factors in different macroeconomic regimes, including market cycles, business cycles, and investor sentiment regimes in India. Other than the low volatility, momentum, value, and quality factors that we examined before, we included two other commonly discussed factors, dividend and size (small cap), in this analysis.

    The analyses of low volatility, momentum, value, and quality are based on the S&P BSE Single-Factor Indices, while the studies on dividend and size are based on hypothetical portfolios that follow a rule-based stock selection and weighting methodology, as shown in Exhibit 2. Apart from the size portfolio, in which all S&P BSE LargeMidCap members are equally weighted, portfolios for all other factors consist of the 30 stocks with the highest factor scores drawn from the S&P BSE LargeMidCap universe after applying liquidity criteria and buffer rules. All portfolios are semiannually rebalanced, effective at the open of the Monday following the third Friday in March and September.

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    How Smart Beta Strategies Work in the Hong Kong Market

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    Priscilla Luk

    Managing Director, Global Research & Design, APAC

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    Liyu Zeng

    Director, Global Research & Design

    EXECUTIVE SUMMARY

    Since the launch of the Hong Kong-Mainland Stock Connect programs, there has been increasing interest in smart beta strategies within the Hong Kong equity market. Our analysis examined the effectiveness of six wellknown risk factors including size, value, low volatility, momentum, quality, and dividends in the Hong Kong equity market from June 30, 2006, to June 30, 2017.

    • Apart from small caps, the rest of the examined factors delivered higher absolute and risk-adjusted returns in their equal-weighted top quintile portfolio versus their respective bottom quintile portfolios.
    • The 50-stock high value and dividend portfolios delivered the highest excess returns, while those for the low volatility and quality showed reduced volatility compared to the underlying benchmark.
    • Our macro regime analysis showed that factor portfolios in Hong Kong are sensitive to both the local market cycles and investor sentiment regimes.
    • The distinct cyclicality in Hong Kong factor performance indicated its potential for implementation of active views on the local equity market.

    FACTOR-BASED INVESTING IN THE HONG KONG EQUITY MARKET

    Smart beta strategies have gained significant attention in the asset management industry, and the exchange-traded products tracking factor indices have experienced significant asset growth since the end of 2008. Factor-based investing shares some common characteristics with passive investing such as rules-based construction, transparency, and costefficiency, and it also shares features of active investing by aiming to enhance return and reduce risk compared to market-cap-weighted indices.

    Single-factor indices are constructed explicitly to capture a specific risk factor and exhibit distinct cyclicality in response to a changing market environment, which also makes them ideal tools for implementation of active views. Index-linked products in low volatility (minimum variance) and multi-factor categories witnessed the strongest asset inflows among smart beta products in recent years.

    In Hong Kong, the adoption of factor-based investing by local market participants is far behind the U.S. and other Asian markets like Japan. However, since the launch of the Hong Kong-Mainland Stock Connect programs, there has been increasing demand for factor-based index-linked products within the Hong Kong equity market. Due to the sluggish Chinese economy, potential renminbi depreciation, and the tight control on QDII quota, the stock connect programs have become favorable channels to facilitate offshore diversification for many mainland Chinese asset managers.

    In this paper, we examined the effectiveness of six well-known risk factors (size, value, low volatility, momentum, quality, and dividend) in the Hong Kong equity market and their investability in practice, as well as the behavior of these factors under different market regimes.

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    Accessing China's Growth via Dividends

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    Tianyin Cheng

    Senior Director, Strategy Indices

    The Chinese government appears to be committed to continuing structural reforms and supporting economic growth. Initiatives with these goals in mind are generally viewed as positive and may put China on a more sustainable growth trajectory in the long run. However, current reforms may be accompanied by volatility in the country’s economy and capital markets. In such an environment, a focus on growing and sustainable dividends can offer a relevant approach to investing in China’s equity markets. This could provide the opportunity to get a slice of the region's structural growth and its potential outperformance throughout the cycle.

    This paper gives an overview of the current status of dividend payouts by Chinese companies, the unique features of dividend policies by stateowned enterprises (SOEs) and family-run businesses, and the dividendrelated policies and regulations issued by the Chinese authorities. It then reviews the S&P China A Share Dividend Opportunities Index, which is designed to offer a transparent, rules-based, and investable strategy for market participants looking for exposure to China’s growth via dividends.


    DIVIDEND PAYOUTS BY CHINESE COMPANIES

    How China Has Evolved

    In recent years, with the release and implementation of a series of dividendencouraging policies issued by Chinese authorities, the amount of dividends issued by companies listed in China’s equity markets has gradually increased. Furthermore, the total amount of dividends and the proportion of companies that issue dividends are increasing as well.

    Exhibit 1 illustrates these improvements from 2011 to 2016. According to the 2016 financial reports and interim reports, there were 1,570 companies in the S&P China A BMI that declared dividends, representing 68% of the S&P China A BMI universe, much higher than the 54% reported in 2009. The size of the total dividend pool for companies in the S&P China A BMI was USD 94 billion in 2016, nearly four times the size of the dividend pool in 2009. The dividend payout ratio was 33.7% in 2016, 7.4% higher than in 2009.

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    Limiting Risk Exposure with S&P Risk Control Indices

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    Tianyin Cheng

    Senior Director, Strategy Indices

    INTRODUCTION

    The volatility seen during the global financial crisis in 2008 broke the calm that was present in financial markets from 2004 to early 2007. Most asset classes experienced significant pullbacks, the correlation between asset classes increased significantly, and markets became volatile. The S&P 500® lost about 56% of its value between the October 2007 peak and the March 2009 trough. Portfolio construction based on the backward-looking correlation model failed, as the expected diversification benefit was eliminated precisely when it was needed the most.

    In recent years, institutional market participants with long-term investment horizons have responded with aversion to this volatility by considering a number of risk control strategies. The risk control strategies use dynamic asset allocation (based on an index and cash) to target a stable level of volatility in all market environments by taking advantage of the negative relationship between volatility and return, as well as the persistence of volatility. For institutional market participants with long-standing liabilities, which can range from defined benefit plans to variable annuities offered at insurance companies, a risk control strategy may provide a smoother path of asset returns and could more closely align the performance of the institution’s assets to the characteristics of its liabilities.

    S&P Dow Jones Indices has developed a risk control framework through a series of risk control indices, which seek to measure various underlying equity- or futures-based indices at set risk levels. S&P Dow Jones Indices’ risk control indices feature:

    • Globally accepted, independent underlying indices like the S&P 500 and the S&P BRIC 40;
    • Transparent methodology based on the underlying index’s historical volatility;
    • Measurements of risk, based on volatility, to help market participants control risk at a predefined level; and
    • Utilization of the same constituents as the underlying index.

    S&P Dow Jones Indices has created a suite of risk control indices based on a large number of equity and thematic indices, along with the S&P GSCI® and the other commodity indices in its series.

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