In This List

Indexing Risk Parity Strategies

Rotation Strategies and Their Role in the Australian Market

Earnings Revision Overlay on Fundamental Factors in Asia

Combining Low Volatility and Dividend Yield in U.S. Preferred Stocks

Measuring Indian Equities: The S&P BSE 500

Indexing Risk Parity Strategies

Contributor Image
Berlinda Liu

Director, Global Research & Design

Contributor Image
Phillip Brzenk

Senior Director, Strategy Indices

INTRODUCTION

Modern Portfolio Theory (MPT), introduced by Harry Markowitz in 1952, sets the framework for building optimal portfolios in which market participants can potentially maximize portfolio returns for a given level of risk. The theory introduces the notion of portfolio diversification by holding non-correlated assets. At the core, one should not view individual asset returns and volatilities in isolation; rather, one should take into account the co-movements, or correlations, of asset returns that comprise a portfolio.

The theory, along with the expectation that long-term asset class Sharpe ratios are similar (Dalio et al. 2015), act as foundational pieces of risk parity. Risk parity strategies propose that portfolio diversification, defined as achieving the highest return per unit of risk, can be maximized when a portfolio’s assets contribute equally to total portfolio risk.

Since the launch of the first risk parity fund—Bridgewater’s All Weather Fund—in 1996, many asset managers have offered their version of risk parity to clients. The risk parity industry has especially gained traction in the aftermath of the 2008 global financial crisis, growing to an estimated USD 150 billion-175 billion at year-end 2017 according to the IMF (Antoshin et al. 2018).

In the past, such strategies lacked an appropriate benchmark, leaving most investors to benchmark against a traditional 60/40 equity/bond portfolio. The issue with this approach is that a 60/40 portfolio reflects neither the construction nor the risk/return characteristics of risk parity strategies. Generally considered to be diversified in dollar terms, the reality is that nearly all of the portfolio risk arises from the 60% allocation to equities. When a portfolio is equal-risk weighted as opposed to equal weighted, it may lead to superior risk-adjusted return.

With the purpose of providing a transparent, rules-based benchmark for risk parity strategies, we introduced the S&P Risk Parity Index Series. These indices construct risk parity portfolios by using futures to represent multiple asset classes and attempt to reflect the risk/return characteristics of funds offered in the risk parity space. Cognizant of the fact that risk parity funds in the industry can have different volatility targets, the index series consists of three indices with different target volatility (TV) levels: 10%, 12%, and 15%.

In the first part of this paper, we cover the economic rationale for implementing a risk parity approach in a multi-asset portfolio construction. In the second part of the paper, we give an overview of the S&P Risk Parity Indices.

pdf-icon PD F DOWNLOAD FULL ARTICLE

Rotation Strategies and Their Role in the Australian Market

Contributor Image
Priscilla Luk

Managing Director, Global Research & Design, APAC

Sector allocation is one of the main pillars in equity portfolio management. In this paper, we examine how the sector price momentum strategy and the cyclical and defensive sector rotation strategy performed in Australia based on the S&P/ASX 200 Global Industry Classification Standard (GICS®) sector indices.

EXECUTIVE SUMMARY

  • As measured by the S&P/ASX 200, the Financials and Materials sectors have accounted for 50% of the Australian market since December 1989, but since sectors can fall in and out of favor, mimicking benchmark sector weighting may not be an optimal way to maximize portfolio returns.
  • Our study on sector price momentum shows that strong momentum sectors in recent months tend to outperform in coming months, and the opposite holds for the weak momentum sectors, suggesting that sector price momentum can be exploited in sector allocation.
  • An unoptimized portfolio with quarterly allocation to the top three sectors based on 12-month price momentum generated an annualized excess return of 4.5% compared with the market between December 1989 and June 2018.
  • Cyclical sectors in Australia represented 80% of the total market, but they underperformed defensive sectors on average over the entire period studied, and they only outperformed defensive sectors in 7 of the past 28 years.
  • Our study on cyclical and defensive sector performance across global and domestic economic cycles shows the global economic cycle is a stronger driver of relative performance of cyclical versus defensive sectors than the domestic economic cycle in Australia.
  • A dynamic allocation strategy that equal weights cyclical sectors during global economic up cycles and rotates to defensive sectors during global economic down cycles achieved an excess return of 5.2% per year compared with the Australian market.

SECTOR DIVERSIFICATION IN THE AUSTRALIAN MARKET

In a previous paper, “Is There Value in Asia Ex-Japan Sector Rotation Strategies?”, we examined how sector allocation based on price momentum and economic cycles performed in Asia, excluding Japan, and we concluded that these two strategies delivered better returns than the benchmark. In this paper, we will study how these two strategies performed in the context of Australian sectors.

Our study focuses on the 11 broad sectors classified by GICS: Energy, Materials, Industrials, Consumer Discretionary, Consumer Staples, Health Care, Financials, Real Estate, Information Technology, Telecommunication Services, and Utilities. The analysis covers the period between December 1989 and June 2018. We use the S&P/ASX 200 and S&P/ASX 200 GICS sector indices to represent the Australian market and sector performances, respectively, since March 2000, which is when the S&P/ASX 200 GICS sector returns data history begins. For dates before the beginning of the S&P/ASX 200 GICS sector index return data, we use S&P Australia BMI and S&P Australia BMI GICS sector index data.

As of month-end June 2018, the S&P/ASX 200 was diversified into 11 GICS sectors, and some of these sectors can be traded through exchangetraded funds (ETFs; see Appendix for full list of S&P/ASX sector ETFs). Financials was the largest sector in the index by weight (33.1%), consisting of 26 stocks with a combined value of more than AUD 2.2 billion traded daily. Utilities was the smallest sector in the index, weighing merely 2.0% and containing five stocks with a combined value of AUD 114 million traded daily.

pdf-icon PD F DOWNLOAD FULL ARTICLE

Earnings Revision Overlay on Fundamental Factors in Asia

EXECUTIVE SUMMARY

In this research paper, we explore the effectiveness of overlaying earnings revision strategies on traditional fundamental value and quality factors across seven Pan Asian markets—Australia, China, Hong Kong, India, Japan, South Korea, and Taiwan—between March 31, 2006, and March 31, 2018.

HIGHLIGHTS

  • The earnings revision-screened factor portfolios outperformed their respective comparable factor portfolios across the majority of Pan Asian markets for the value and quality factors.
  • Our screening approach did not introduce a large increase in portfolio turnover or strong sector or size biases to the fundamental factor portfolios historically.
  • Among various Asian markets, the earnings revision overlay generated the most significant excess return in Australia and Hong Kong for a majority of fundamental factors.

INTRODUCTION

In our previous research paper “Do Earnings Revisions Matter in Asia?, we concluded that stock prices tended to move in the same direction as their earnings revisions in the majority of Pan Asian markets, and the earnings revision strategies delivered excess returns in a majority of the markets.  Due to the high portfolio turnover of this strategy, using earnings revision as an overlay to fundamental factors may be more practical.  

The goal of this research is to evaluate the effectiveness of earnings revision strategies over the fundamental factor portfolios.  We overlaid two earnings revision screens (EPS change and EPS diffusion) on the fundamental value and quality factor portfolios, respectively.  Specifically, we examined if the earnings revision screens were historically effective in generating return alpha or reducing the risk of the factor portfolios by filtering out the stocks with relatively poor earnings revisions from the factor portfolios.1 

pdf-icon PD F DOWNLOAD FULL ARTICLE

Combining Low Volatility and Dividend Yield in U.S. Preferred Stocks

Contributor Image
Hong Xie

Senior Director, Global Research & Design

Contributor Image
Aye Soe

Managing Director, Global Head of Product Management

INTRODUCTION

Preferred stocks are hybrid securities that sit between common stocks and bonds in a company’s capital structure, therefore exhibiting blended characteristics of both asset classes. They have been favored by incomeseeking investors due to the higher yields they offer in comparison with common stocks and corporate bonds.

Historically, dividends have been a dominating driver for the total return of preferred stocks. Therefore, many preferred strategies seek to capture the benefit of higher-dividend-yielding preferred stocks.

However, as with any income-oriented strategy, it is important to avoid falling into a yield trap. In particular, our research in equity dividends has shown that securities in the top quintile of the yield-ranked universe have higher volatility and lower risk-adjusted returns than those in other quintiles.1 Similarly, this paper shows that higher-dividend-yielding preferred stocks also tend to exhibit higher volatility, and therefore an income strategy may require some form of volatility management for prudent portfolio construction.

Against that backdrop, we applied the low volatility factor, which is popular in equity investing, to preferred stocks. The low volatility effect refers to the finding that, historically, stocks with low volatility have tended to outperform their high volatility peers on a risk-adjusted basis. It has been extensively studied in equities by academics and practitioners alike and stock investment vehicles linked to low volatility strategies have grown significantly. Our analysis shows that the low volatility factor can be overlaid with a high-dividend strategy in preferred stocks to manage volatility while maintaining attractive yield levels.

The remainder of this paper is organized as follows. The first section explores a high-dividend investment strategy and extends the study of the low volatility effect in U.S. preferred stocks. The second section introduces the methodology of the S&P U.S. Preferred Stock Low Volatility High Dividend Index. The third and fourth sections present back-tested performance and characteristics of the index, respectively.

HIGH-DIVIDEND INVESTING AND LOW VOLATILITY EFFECT IN PREFERRED STOCKS

Preferred Stock Total Return Analysis

Preferred stocks exhibit blended characteristics of stocks and bonds. They represent ownership in companies, but they do not come with voting rights. Given their junior position to bonds in capital structure, preferred stocks generally offer higher yield than senior bonds, and higher stable dividends than common stocks, and therefore are popular instruments for incomeseeking investors.

Historically, dividend income contributes significantly to preferred stock total return. To illustrate, Exhibit 1 compares the price returns and total returns of the S&P U.S. Preferred Stock Index and S&P 500® . From its inception in 2003 until May 31, 2018, the S&P U.S. Preferred Stock Index generated a cumulative total return of 114.8%, while its price return was -22%. This is in contrast with the S&P 500, for which total return followed price return closely, and price return contributed 64% of the total return since 2003.

pdf-icon PD F DOWNLOAD FULL ARTICLE

Measuring Indian Equities: The S&P BSE 500

The S&P BSE 500, which launched in 1999, is one of the most popular broad benchmarks of India’s capital market.  With a rich history of more than 18 years, the index has captured all major events—from heightened activity seen during numerous bull and bear runs, including the information technology boom and then bust in 2001, the bull market rally ending in 2007, the 2008 global financial crisis, and later the regional shocks seen globally.

This paper discusses the construction and attributes of the S&P BSE 500 and compares it with other popular equity indices in the Indian market.

EXECUTIVE SUMMARY

  • Interest in Indian equities should continue to grow, as the International Monetary Fund (IMF) projects a growth rate of 7.4% in 2018 and 7.8% in 2019 for the Indian economy, putting it among the fastest-growing global markets of its size.[1]
  • The S&P BSE 500 is designed to measure the performance of the leading 500 Indian companies, and it covers more than 88% of India’s listed equity market capitalization.
  • The S&P BSE 500 has historically exhibited low correlation to global markets, providing a potential diversification opportunity.
  • The index offers diversified exposure to all GICS® The large-cap stocks account for nearly 79% of the index weight.  The combined weight of constituents having individual derivative trading is 87%, which facilitates the hedging of the index portfolio.  Thus, the S&P BSE 500 reflects a complete picture of India’s economy.
  • Over the period studied, the S&P BSE 500 outperformed the S&P BSE 100 and S&P BSE 250 SmallCap Index, while it underperformed the S&P BSE 150 MidCap Index on an absolute and risk-adjusted basis over the long term.
  • The financials sector, which constituted the highest average index weight over the past three years, contributed the most (nearly onethird) of the total returns of the S&P BSE 500.

pdf-icon PD F DOWNLOAD FULL ARTICLE

Processing ...