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The Trump Rally – A Macroeconomic Perspective

Does Value Enhance Quality Investing in China's A-Share Market?

A Study of the Classics – Part 2

The Trump Rally – One Year Later

Tuition Inflation: Indexing the Rising Cost of College

The Trump Rally – A Macroeconomic Perspective

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Phillip Brzenk

Senior Director, Strategy Indices

S&P Dow Jones Indices

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As noted in a previous blog, The Trump Rally – One Year Later, the Domestic Revenue Portfolio underperformed the foreign revenue portfolio during the one-year period since the 2016 U.S election.  We showed that currency movements may have negatively impacted the performance of the Domestic Revenue Portfolio.

To better understand the currency risk of the portfolios beyond tracking relative performance and currency movements, we use the Northfield U.S. Macroeconomic Equity Risk Model to breakdown total portfolio risk.  This model gives us the ability to understand the macroeconomic risk exposures, including changes in the value of the U.S. dollar, of a portfolio.  Exhibit 1 breaks down the total risk (in variance terms) of the two portfolios between stock specific risk and systematic/factor risk.

The Foreign Revenue Portfolio had significantly higher stock specific risk than the Domestic Revenue Portfolio, which means the percentage of total risk that can be explained by U.S. macroeconomic factors present in the model is lower.

The highlighted factor in Exhibit 1, Exchange Rate USD, indicates how much of the total risk is caused by changes in USD value relative to other major trade currencies.  We can see that the currency risk of the Foreign Revenue Portfolio (7.58%) was much higher than the Domestic Revenue Portfolio (1.26%), which indicates that changes in USD will have a higher impact on the foreign portfolio than the domestic portfolio.  In other words, the Foreign Revenue Portfolio is more sensitive to weakening and strengthening of the U.S. dollar than the Domestic Portfolio.

As such, we look at the factor exposures and how those exposures in turn have affected the portfolios.  These figures show how the individual factors have performed over the 12-month period, as well as if the active factor exposures of the portfolios have contributed positively, or negatively, to total return.

For the 12-month period, the average monthly return for the Exchange Rate USD factor was -0.44%, meaning that holding the U.S. dollar versus holding other major trade currencies would negatively contribute to total return.  Relative to the S&P 500, the Foreign Revenue Portfolio is observed to have negative active exposure to the currency factor, while the Domestic Portfolio has positive active exposure.  The active exposures of the portfolios show that relative to the S&P 500, 1) the foreign portfolio is negatively related to changes in the USD value, and 2) the domestic portfolio is positively related to the USD value.  These results confirm the potential relationship we saw in the previous blog post.  The compounded factor impact shows the result of the active portfolio exposures to total return.

In a forthcoming blog, we will look beyond macroeconomic risk to sector-level performance attribution analysis of the portfolios.

 

[1]   The model provides a monthly-based analysis; therefore the start date is Oct. 31, 2016, as opposed to Nov. 8, 2016.

[2]   The model provides a monthly-based analysis; therefore the start date is Oct. 31, 2016, as opposed to Nov. 8, 2016.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

Does Value Enhance Quality Investing in China's A-Share Market?

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Liyu Zeng

Director, Global Research & Design

S&P Dow Jones Indices

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As discussed in my previous blog, quality investing has gained attraction in China, as high-quality stocks recorded remarkable performance in the first nine months of 2017.  As a result, the risk of paying too much for high-quality stocks has become a concern.  To address the issue, on Sept. 29, 2017 we launched the S&P China A-Share Quality Value Index, which is designed to measure the performance of the top 100 high-quality stocks with reasonable valuation, (see Exhibit 1).[1]

Historically, the S&P China A-Share Quality Value Index has outperformed the S&P China A BMI (the benchmark) on an absolute and risk-adjusted basis.  It is important to note that, after adding the value screen, the S&P China A-Share Quality Value Index recorded higher absolute and risk-adjusted returns with slightly higher return volatility and bigger drawdown than the hypothetical S&P China A-Share Quality 200 Portfolio without an additional value screen.[2]  This demonstrated the benefit of using the value screen to exclude those high-quality stocks with expensive prices (see Exhibit 2).

From June 30, 2006, to Sept. 29, 2017, the S&P China A-Share Quality Value Index outperformed the benchmark and the S&P China A-Share Quality 200 Portfolio in 9 and 8 out of 12 periods, respectively.

Exhibit 3 shows the performance of quality portfolios in up and down markets.  Compared to the quality portfolio without value screen, the S&P China A-Share Quality Value Index had more balanced performance with more than 50% of win ratios and positive excess returns in both up and down markets, without much sacrifice in downside protection.

Exhibit 4 shows the performance of the S&P China A-Share Quality Value Index versus the hypothetical quality portfolio and value portfolio[3] across different China A-share equity market cycle phases, defined with respect to the S&P China A BMI’s (BMI’s) performance trends (three bearish and four bullish cycle phases).  The S&P China A-Share Quality Value Index outperformed the benchmark in six out of seven market cycle phases, while the value portfolio and quality portfolios only outperformed the benchmark in five and four out of the seven phases, respectively.  With the aid of the value screen, the S&P China A-Share Quality Value Index exhibited more consistent outperformance than purely value or quality screened/weighted portfolio.

As we expected, the S&P China A-Share Quality Value Index exhibited cheaper valuation with some sacrifices in quality features (see Exhibit 5).  It is interesting to note that it had higher dividend yield than the quality portfolio without additional value screen, due to the lower valuation of stocks.

Historically, most of the constituents of the S&P China A-Share Quality Value Index were from the industrials and consumer discretionary sectors.  Compared to the broad China A-share market, most of the time, it was overweight in consumer discretionary and underweight in real estate and financials.

[1]   For detailed index methodology, please see https://spindices.com/indices/strategy/sp-china-a-share-quality-value-index-cny.

[2]   The S&P China A-Share Quality 200 Portfolio is a hypothetical portfolio that consists of 200 high-quality stocks before the value screening, with eligible criteria, weighting method, and rebalancing schedule following the S&P China A-Share Quality Value Index methodology.

[3]  The S&P China A-Share Enhanced Value Portfolio was constructed based on the same parent indices with the same size and liquidity criteria.  The top 100 stocks with the highest value scores in the eligible universe are selected, subject to 20% rebalance buffer by number of stocks.  The value score is measured as the average z score of earnings-to-price, sales-to-price, and book value-to-price ratios.  Constituents are weighted by score-tilted market cap, subject to security and sector constraints such that the weight of each security is between 0.05% and the lower of 5% and 20 times its float-adjusted market-cap weight in the eligible universe, and the maximum weight of any given GICS sector is 40%.  The portfolio is rebalanced semiannually on the third Friday in June and December.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

A Study of the Classics – Part 2

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Jamie Farmer

Chief Commercial Officer

S&P Dow Jones Indices

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This scene came to mind after I recently posited a few indexing milestones.

My intent was to opine on watershed moments in design, those individual indices that marked advancement, a change in approach, or increased utility.  Almost immediately, I received “Yeah, but what about…?” communiques.

So forthwith I complete my all-too-brief, original list with the expectation of eventually correcting a few glaring omissions.

Dow Jones Sustainability Index (1999): Today, we take for granted that ESG—environment, social, and governance factors—are important considerations for corporations and market participants alike.  In 1999, however, the concept was nascent at best.  The Dow Jones Sustainability Indices were the first benchmarks to focus exclusively on companies that adhered to “best-in-class” sustainable practices.  Since that time, the S&P ESG suite has developed into a fast-growing and comprehensive framework that includes such dynamics as carbon emissions, environmental impact, corporate citizenship, and human capital development, among others.  As ESG matures as an investing discipline, it has become clear that individual perceptions can vary on highly granular dimensions, so such a framework is necessary in order to construct indices to meet bespoke needs.

TIE – Dow Jones U.S. Select Dividend Index (2003) and S&P 500® Dividend Aristocrats® (2005): Since 1926, dividends have contributed approximately one-third of the total return of the S&P 500.  Few, then, would suggest that investing with an eye toward optimizing that income was uncharted territory.  In 2003, however, President George W. Bush signed tax law changes that offered more favorable treatment of dividends and the stage was set for the introduction of the Dow Jones U.S. Select Dividend Index.  With components weighted according to indicated dividend yield, “Select Div” pioneered the category of dividend indexing and is often considered among the first wave of smart beta indices.  Two years later, the S&P 500 Dividend Aristocrats offered a different take on dividend exposure by encapsulating shares with consistent records of increasing payouts.  These two index series remain early testimony to the idea that there are always catalysts for new index development.

S&P 500 Low Volatility Index (2011): Finally, if one accepts that weighting components according to dividend yield can be considered the earliest appearance of smart beta, then the S&P 500 Low Volatility Index truly established the concept in the indexing firmament.  This index was the first genuinely successful entry into the factor-based space, which seeks to amplify or attenuate the drivers of investment performance (cap size, value versus growth, momentum, etc.).  At its heart is the somewhat counterintuitive, though heavily documented, notion that lower volatility stocks can offer superior risk-adjusted returns over time.  By indexing what was once solely the province of quantitative active managers, these strategies democratized and lowered the cost of access for all market participants.

So, there you have it—seven major milestones on the timeline of index development.  Invitation to (further) dissent in 3, 2, 1…go.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

The Trump Rally – One Year Later

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Phillip Brzenk

Senior Director, Strategy Indices

S&P Dow Jones Indices

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The results of the 2016 U.S. presidential election, which were widely considered surprising, had many market participants believing that the proposed economic policies of Donald Trump, “Trumponomics”, would be swiftly implemented.  During his campaign run, Trump called for tax cuts, reduced corporate regulations, increased foreign trade tariffs, and increased defense and infrastructure spending.[1]  Initial expectations held by many were that his policies would be a boon to the overall U.S. economy in the short term.  In particular, companies and industries most closely tied to the U.S. economy and economic proposals would reap the majority of the benefits.[2][3]

Given that we are at the one-year mark since the election, we wanted to see how things have played out since.  This will be the first installment in a series of posts that reviews performance since the 2016 U.S. election.

If the hypothesis is that companies most tied to the U.S. economy would benefit the most under the new presidential regime, we can test as such by forming two portfolios based on geographic revenue data.  The S&P 500® Focused U.S Revenue Exposure Index (Domestic Revenue Portfolio) comprises the top 25% of companies in the S&P 500 that receive the highest proportion of their total revenue from the U.S., while the S&P 500 Focused Foreign Revenue Exposure Index (Foreign Revenue Portfolio) holds the top 25% of companies most exposed to foreign economies.  With the creation of these portfolios, we are able to test the hypothesis by tracking their performance since the election relative to the S&P 500.

As projected, for the immediate months following the election, the Domestic Revenue Portfolio outperformed the Foreign Revenue Portfolio and the S&P 500 by a meaningful margin.  But as 2017 approached spring, a reversal occurred, and the foreign portfolio began to outperform the domestic portfolio—a trend that continued through the end of October 2017.  As of Oct. 31, 2017, the foreign portfolio had an excess return of 7.14% versus the S&P 500, while the domestic portfolio underperformed the S&P 500 by 7.31%—a difference of 14.45%.

To discover why this occurred, we first look at the potential impact that currency movements had on the portfolios.  Intuition would say that a portfolio focused on companies with revenues coming from the U.S. would have little direct, or indirect, exposure to foreign currency movements.  Conversely, a portfolio focused on companies with foreign revenues would be exposed to foreign currency movements as the companies translate foreign currency revenues back to USD.

The U.S. Dollar Index, which is designed to track the relative value of the U.S. dollar to a basket of other major world currencies, is overlaid on the performance chart (plotted to the secondary axis).  Conceivably reflecting the bullish views of the expected future growth of the U.S. economy, the index rose over 4% by the end of 2016.  By early 2017, the U.S. Dollar Index started to decline and trend downward through the end of October, in similar magnitude as the domestic portfolio.  The foreign portfolio saw relative performance versus the S&P 500 and the domestic portfolio rise as the U.S. dollar dropped in value.  The results, therefore, potentially indicate a positive relationship between the domestic portfolio and U.S. Dollar Index and a negative relationship between the foreign portfolio and the U.S. Dollar Index.

To further investigate the relationship between currency movements and portfolio performance, in the next blog we will look at the overall macroeconomic risks of the portfolios.

[1] https://www.nytimes.com/2016/08/09/us/politics/donald-trump-economy-speech.html

[2] http://www.imf.org/external/pubs/ft/weo/2017/update/01/

[3] https://www.nytimes.com/2016/11/10/business/dealbook/stock-markets-election.html

The posts on this blog are opinions, not advice. Please read our Disclaimers.

Tuition Inflation: Indexing the Rising Cost of College

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Jodie Gunzberg

Managing Director, Head of U.S. Equities

S&P Dow Jones Indices

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Costs associated with college tuition and fees have far outpaced general U.S. inflation, so for individuals saving for college, the ability to accurately measure and potentially keep pace with tuition inflation is important. 
Recently, in this video, S&P Dow Jones Indices joined with Enduring Investments to discuss the newly launched S&P Target Tuition Inflation Index.  Below is a summary of the questions and answers discussed in the interview that may be interesting for college savers:
What are the economic underpinnings and thinking behind the strategy?
In designing a strategy and index to track college tuition inflation over time, it is important to understand how college tuition is set.  Colleges are producing a product just like any other business, but the product is education.  Just as in any business they have expenses and revenues so understanding what are driving those expenses and revenues is an important part of understanding how to build such an index.  On the expense side colleges have mostly labor costs, but they have a number of other things that are that go into creating the educational product, and collectively those things act like general inflation.  Though, on the revenue side, colleges have really two sorts of revenues – internal revenues and external revenues.  The internal revenues are government appropriations if it’s a public university, or the endowment returns if it’s a private university.  The external revenues come from college tuition.  So understanding how college tuition varies depending on how the appropriations or the endowment returns behave is where the rubber meets the road in terms of getting this index to target college tuition inflation.
How does the index design help capture the thesis behind the strategy?

Again, the key is in understanding the relationship on the revenue side between the  endowment returns and appropriations versus the tuition inflation growth.  Recognizing that there’s this large spread of tuition inflation that’s above the general inflation as measured by the CPI is the starting point.  Using the CPI as the base and measuring the driver of that spread can be done by knowing something about the relationship of the revenue components.  What the research behind the index shows is that tuition inflation is a function of the real return plus a break-even inflation, plus a corporate spread, minus an equity risk premium.  This combination has grown in-line with the tuition inflation that is inverse to the endowment or appropriation growth, so that’s the mix that make the mechanics work.

Source: S&P Dow Jones Indices. S&P Target Tuition Inflation Index Methodology. http://us.spindices.com/documents/methodologies/methodology-sp-target-tuition-inflation-index.pdf?force_download=true

How does the index data track tuition inflation compared to a more traditional 60/40 mix?

The 60/40 mix is really designed for optimal diversification in most risk-adjusted return portfolios, but the idea of a college liability is not taken into account in a 60/40 mix.  Since there is a relatively short time frame for college savings, the 60/40 mix may be very volatile, so at moments there is a high chance that tuition inflation is not met.  By moving to the S&P Target Tuition Inflation Index, the probability of tracking tuition inflation increases, and even more so the longer the holding period.

Hypothetically, the S&P Target Tuition Inflation Index is within 2% of the BLS College Tuition and Fees U.S. City Average Inflation more often than the 60-40 mix of stocks and bonds.

In which economic environments might the strategy track tuition inflation most closely?
The index design intends to track college tuition in many different economic environments.  Since any economic environment may be predominant when a child goes to college, it is important to understand that means that the index itself varies with the drivers of fundamental drivers of college tuition inflation.  When overall inflation is accelerating, and the stock market is falling, it is likely endowments aren’t doing very well, so the costs of the university are going up a little faster.  That is when the index is expected to also rise faster.  Conversely, if the stock market has been doing very well for a while, so that endowments are flush, and yet overall inflation is low, then college tuition may not be going up as much.  Therefore, the index may not go up as much either.  Again, the idea for success is for the index to perform over the long run in a comparable way to the college tuition inflation.

The posts on this blog are opinions, not advice. Please read our Disclaimers.