In This List

The Impact of the Global Economy on the S&P 500®

Corporate Carbon Disclosure in Europe, the Middle East, and Africa

Fixed Income Update: Unveiling the Hidden Cost of Retail Bond Buying & Selling March 2018

Global Application of S&P 500® Sectors

Carbon Risk Integration in Factor Portfolios

The Impact of the Global Economy on the S&P 500®

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Phillip Brzenk

Senior Director, Strategy Indices

SUMMARY

In this paper, we examine the geographic revenue distribution of the S&P 500 and see what, if any, impact foreign economies and geographically driven market events may have on overall index performance.

We examine a recent market event, the 2016 U.S. election, as a case study. To aid in the analysis, we use two stylized portfolios based on geographic revenue data. The time period studied is from Election Day (Nov. 8, 2016) to year-end 2017, a period of robust performance and record highs for the S&P 500.

We review the performance of companies in the index through the lens of geographic revenue information. To decompose the performance, we first investigate the potential impact that currency movements may have using the U.S. Dollar Index performance and the Northfield U.S. Macroeconomic Risk Model. We then take a closer look at the individual GICS® sectors and run sector-driven performance attributions of the stylized portfolios.

INTRODUCTION – THE S&P 500 HAS GLOBAL EXPOSURE

The S&P 500 is widely considered to be one of the best single gauges for the U.S. equity market. Composed of 500 companies that are domiciled in the U.S., the index captures approximately 82% of the total U.S. equity market value. An index of U.S. companies may lead one to initially assume that the index is exclusively dependent on the health of the U.S. economy. In reality, the index is more global than one may think. Many U.S. corporations have a global presence, with assets and revenues in or from foreign countries. Therefore, certain global events can have a material effect on S&P 500 companies and overall index performance.

To better understand where S&P 500 companies’ revenues are coming from, the FactSet Geographic Revenue Exposure (GeoRevTM) dataset was used. This dataset gives a geographic breakdown of revenues for all companies with available data. This data showed that nearly 71%3 of S&P 500 revenues came from the U.S., while the remaining came from foreign markets. Internationally, the largest individual countries by total revenue percentage included China (4.3%), Japan (2.6%), and the UK (2.5%).

Given the data shown in Exhibit 1, it is evident that the S&P 500 has material exposures to foreign economies. As such, domestic and global events or policies that change the dynamic between the U.S. and foreign markets can potentially have an effect on the performance of the S&P 500. In the next section, we investigate how the global market exposure of the S&P 500 has affected index performance.

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Corporate Carbon Disclosure in Europe, the Middle East, and Africa

More EMEA firms quantify supply chain risks, set science-based targets, and implement internal carbon pricing.

EXECUTIVE SUMMARY

Trucost, part of S&P Dow Jones Indices, assessed the trends in corporate disclosure of carbon emissions to see how companies are managing risks in three important areas: quantifying supply chain carbon emissions, setting meaningful emission reduction targets, and pricing carbon to understand the current and anticipated financial implications of impending regulatory and policy measures.  The headline findings include the following.

  • In 2017, Europe, the Middle East, and Africa (EMEA) businesses continued to expand their carbon reporting. However, this reporting varied greatly in terms of depth and breadth.
  • Many corporations, particularly in the health care and financials sectors, do not fully track the carbon sources that are most material to their business activities.
  • EMEA companies surpass global companies in setting science-based targets that will cut emissions in line with international efforts to limit global warming to 2 degrees Celsius.

Nearly 40% of EMEA companies currently have or plan to set an internal price on carbon to help understand the risks and opportunities of the transition to a low-carbon economy.

INTRODUCTION

Trucost analyzed environmental data submitted by companies to the CDP annual climate change questionnaire.  Trucost compared data for 2017 with previous years to identify trends in carbon management and reporting, focusing on companies in the EMEA region.  The analysis covered emissions from company operations and use of electricity (scopes 1 and 2, respectively), as well as value chain emissions (scope 3), as classified in the Greenhouse Gas (GHG) Protocol.[1]

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Fixed Income Update: Unveiling the Hidden Cost of Retail Bond Buying & Selling March 2018

  • Smaller block trades, versus larger dealer block trades, have higher transaction costs, in relative terms to the face value of bonds trading as markups are applied on both the purchase and sale of bonds to and from individual market participants.
  • Municipal bond retail investors incur higher markups and therefore have higher transaction costs than retail investors buying or selling corporate bonds.
  • As a result of these markups, buying and selling retail-size bond lots is demonstrably less efficient than buying or selling shares of an exchange-traded fund (ETF) or a mutual fund, which can buy and sell bonds with larger block sizes and lower markups.
  • In a low-yield environment, retail transaction costs can be a significant cause of erosion of potential returns.

WHAT’S THE CATCH?

Owning individual bonds has its risks and rewards.  However, buying a bond entails an unseen transaction cost, which may not always be clear to retail investors.  This transaction cost exists because bonds are not typically sold with a commission.  Instead, a markup is built into the bond price.

This report offers a transparent look at these hidden transaction costs for U.S. municipal and corporate bonds.  To determine these costs, we used the investment-grade bonds tracked by the S&P National AMT-Free Municipal Bond Index, the S&P AMT-Free Municipal Series, high-yield municipal bonds tracked by the S&P Municipal Bond High Yield Index, investment-grade corporate bonds tracked by the S&P 500® Investment Grade Corporate Bond Index, and high-yield corporate bonds tracked by the S&P 500 High Yield Corporate Bond Index, in conjunction with bond transaction data provided by the Municipal Securities Rulemaking Board (MSRB) and the Financial Industry Regulatory Authority (FINRA).  Based on this data, we have determined the average implied transaction cost of municipal bonds since May 2011 and that of corporate bonds since July 2011.  This information can help market participants compare the cost of buying individual bonds to the cost of investing in bond alternatives, such as mutual funds and ETFs.

For 2017, the average implied transaction cost of buying an individual municipal bond of investmentgrade quality was 0.90% for retail investors.  The average implied transaction cost for high-yield municipal bonds was 1.66%.  Investment-grade corporate bond transaction costs were lower, at 0.64%, and high-yield corporate bonds had an implied transaction cost of 1.17%.


Global Application of S&P 500® Sectors

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Hamish Preston

Associate Director, U.S. Equity Indices

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Craig Lazzara

Managing Director, Global Head of Index Investment Strategy

EXECUTIVE SUMMARY

This paper examines the applications of U.S. sector indices in a portfolio context, from the perspective of both international and domestic investors. We shall:

  • Outline the Global Industry Classification Standard (GICS®) classifications of sector and industry groups;
  • Illustrate the importance of sectors in determining portfolio returns, in relative and absolute terms;
  • Demonstrate the importance of the U.S. market in accessing global industries and sectors, and illustrate the growth in related products;
  • Illustrate the potential applications of sectors in achieving diversification goals;
  • Indicate how sectoral groupings help connect broader trends to their market effects;
  • Compare the effectiveness of sector-selection and stock-selection strategies;
  • Show that—in a multi-asset context—the impact of changing the mix of equity sectors can be comparable to the impact of adjusting stock and bond allocations; and
  • Provide a long-term perspective on the sectoral composition of the U.S. market.

The first few sections summarize the importance and classification of sectors, offer basic examples of international applications, and highlight the growth of related products. Readers interested in more advanced topics related to tactical sector rotation strategies will find them addressed in the later sections.

GICS DEFINITIONS AND INDICES

Sectoral benchmarks have a long history. Indeed, when the Dow Jones Industrial Average® was first published in 1896, its developer Charles Dow had been publishing an 11-stock “Railroad Average” for over a decade. Ever since, industry-specific indices have been used to assess particular market segments or to anticipate nascent economic developments.

It is useful to have different degrees of granularity, for purposes of comparison: an investment in a railroad stock might be compared to the performance of a railroad index, or to a broader transportation index, or even yet to the entire industrial sector or the whole market. Over time, sector and industry indices serving the needs of both granular and broad market benchmarking purposes were developed by index providers such as S&P Dow Jones. However, the definitions of the various equity groupings remained subjective, along with the classifications of each company. We may disagree, for example, as to whether the corporate owners of an internet search engine should be classified as a technology company, or—supposing they make the majority of their revenues from advertising—as a media company. Historically, a smorgasbord of different sectoral taxonomies emerged, leading to a wide range of good-natured disagreement over which classification system was most appropriate. In August 1999, two of the leading index providers, S&P Indices (a predecessor of S&P Dow Jones Indices) and MSCI joined forces to produce the Global Industry Classification Standard (GICS). This provided a shared method that unified definitions across the two companies’ indices.

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Carbon Risk Integration in Factor Portfolios

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Bill Hao

Director, Global Research & Design

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Aye Soe

Managing Director, Global Head of Product Management

INTRODUCTION

In the past, discussions on carbon risk would typically involve scientific arguments regarding climate change and whether existing evidence supported market participant action for carbon-awareness investing. In recent years, climate change policy and knowledge have progressed to the point where many large institutions across the globe have already begun to incorporate varying degrees of carbon risk integration into their investment process.

Concurrent to the low-carbon investing trend has been the adoption of factor-based asset allocation by institutional investors. Institutional investors who are implementing factor-based investing into their core equity allocation and who wish to align their entire investment process with lowcarbon initiatives may need a total portfolio management approach, in which metrics related to carbon risk are integrated with signals from traditional risk factors. As such, there is a clear need in the market for studies that examine the impact of carbon risk integration with traditional factor portfolios.

Therefore, the debate at this juncture centers more on how imminently carbon risk is priced and thus to what degree market participants should position their existing portfolios. As a starting point for carbon-awareness investing, knowing the carbon footprint of a given portfolio is required. However, carbon footprint measures only part of the carbon-pricing risk and is not forward looking1 in providing a complete estimate of carbon risk exposure.

For various reasons, including data availability and history, as well as the focus of the paper being to demonstrate portfolio implications of incorporating carbon-related metrics, our paper adopts a simpler approach by examining carbon risk through a carbon-efficiency lens.

In this paper, we argue that a pure, unconstrained, carbon-efficient portfolio outperforms a carbon-inefficient portfolio, as well as the underlying benchmark, on an absolute return basis, but underperforms on a riskadjusted basis due to the portfolio having higher volatility. Moreover, we discuss how the carbon-efficient portfolio exhibits unintended sector and factor biases. Using the correlation of carbon intensity with style factors, we demonstrate a stylized framework in which carbon-efficient portfolios (both unconstrained and sector relative) can be combined with traditional risk factors to lower carbon intensity while maintaining the target factor exposure.

Through this analysis, we merge two powerful trends that are shaping the investment industry, and we provide a framework that can be used by institutional investors who wish to be sustainability-driven while focusing on achieving risk/return profiles that are specified in their investment mandates. We show that carbon-efficient factor portfolios can be a meaningful part of the core equity strategic and tactical asset allocation process.

The framework we have provided in our paper is by no means exhaustive. There are numerous ways to achieve decarbonized factor portfolios, each with its own tradeoffs and unique characteristics. Hence, in subsequent papers, we intend to explore additional case studies and provide stylized examples through which advantages and disadvantages of each approach can be further understood.

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