Indexology^® Blog

The International Monetary Fund (IMF) recently released its World Economic Outlook, October 2018, with estimated global trade tension scenario impacts on GDP.  Overall, the IMF states that recent tariffs will hurt GDP and that additional tariffs will weaken it further.  In the long term, according to the IMF’s scenario analysis (on p. 21,) the U.S. GDP will be 0.9% lower and China’s GDP will be 0.6% lower as a result from the trade tensions.  However, in 2019, the disruption caused by an escalation of trade restrictions could be particularly large with GDP losses of more than 0.9% in the U.S. and over 1.6% in China.

Based on the IMF estimates and the historical sensitivity of stock markets to GDP growth, if the trade tensions escalate, some countries may be impacted more than others.  This can be measured globally by starting with the total U.S. dollar market capitalization of the S&P Global BMI (Broad Market Index) by country.  The United States is the largest in the world, representing 53.5% of the total market cap worth $27.8 trillion as of Oct. 11, 2018.  South Korea is the smallest country of the top ten by size, and has an index weight of 1.7% that includes about $902 billion.  In total, the top ten biggest countries by market value include 86% of the world’s $52 trillion total market value.

Next the historical sensitivities of each country’s stock market to GDP growth is measured.  For example, for every 1% of U.S. GDP growth, the U.S. stock market value increased 3.79% on average (using year over year data from 1993-2017.)  South Korea was most sensitive with a 9.35% stock market value increase on average per 1% of U.S. GDP growth, while Japan was least sensitive on average gaining just over 2% on average per 1% of U.S. GDP growth.  The greater the percentage of its output a country exports to the U.S., the bigger the influence U.S. GDP growth has on that country’s stock market since the U.S. growth is so heavily driven by consumer spending.  Overall, the stock market sensitivity was far greater to U.S. GDP growth than to China’s.

After measuring the historical stock market sensitivity of the ten biggest countries in the S&P Global BMI to each U.S. and China GDP growth, the decreased GDP as estimated by the IMF can be applied as one possible scenario to understand how stock market values may be reduced.  In total, if the U.S. and China GDP were to drop in 2019 by 0.9% and 1.6%, respectively (as estimated in a five-layer simulation by the IMF,) the global stock market value may lose $2.17 trillion or 4.9% of its value from the top ten countries under this scenario.  A total market value loss of about $1.49 trillion and $687 billion, all else equal, may be attributed to the GDP reduction in the U.S. and China, respectively, in this case.  While the total dollar market value loss in the U.S. would be biggest with a magnitude of $1.39 trillion under this scenario, the greatest percentage declines in market value might impact South Korea and China more with respective 12.4% and 8.2% losses.

“Data! Data! Data!” he cried impatiently. “I can’t make bricks without clay.”

– Sherlock Holmes (in “The Adventure of the Copper Beeches”)

Despite yesterday’s hand wringing loss for equity markets— the S&P 500 dropped 3.3%—the index is still up 5.8% year to date 2018. Nevertheless, losing in one day a third of what the equity market achieved in 9 months can, justifiably, cause alarm. In the not too distant past, the market experienced a similar trauma. Then, as now, volatility ticked up. But we also pointed out that in the broader context, the volatility jump in February 2018 was not too significant. Yesterday’s increase was even less so.

Breaking down volatility into its contributing components offers even more reassuring insight. The dispersion-correlation map offers a look at the two factors that drive volatility. The chart below maps the daily rolling 21-day dispersion and correlation levels since the beginning of August. The jump in both dispersion and correlation on October 10 was quite precipitous, but the levels are still lower than those we saw in February.

However, as the chart below reflects, from a broader context, yesterday’s market took us to above average levels for correlation, but dispersion is still under its 27-year average. This may seem striking given the particularly sleepy year in 2017, but these levels are still quite far from those in the tumultuous years of the technology bubble deflation and the financial crisis.

High dispersion does not guarantee weak markets, but in our data no severe market pullback has occurred in the absence of high dispersion.

Yesterday’s decline in the U.S. and global stock markets is striking not simply because of its magnitude but also because it represents a radical reversal of factor returns from the first three quarters of 2018.

Readers of our quarterly factor dashboard will recognize this graph, which shows the total return of the S&P 500 and a set of factor indices derived from it for the 12 months ended September 30, 2018:

Momentum and Growth dominated the rankings for the first nine months of 2018 (as they had done in calendar 2017 as well).

Since the beginning of October, however, there has been an amazingly-abrupt (less than two weeks!) reversal of fortune, as today’s daily dashboard shows:

The winners so far in October were the first three quarters’ laggards, with previously-high flying momentum and growth names falling behind.  We pointed out several months ago that Momentum is uniquely self-reinforcing – until it suddenly isn’t.  And when the worm turns, Momentum’s underperformance can be particularly striking:

Will defensive factors assume market leadership while Momentum and Growth have a well-deserved respite?  Ten days do not a trend make, but what we see so far in October represents such a potential regime shift.

Sales of new and existing single-family homes have fallen since their recent high in November 2017 while pending home sales are flat to down so far this year.  Starts of new single-family homes are volatile but also remain below the peak seen at the end of 2017.  Recent press reports of declining activity in several major markets including Seattle, San Francisco and New York City confirm the statistics.

One factor depressing home sales is rising prices. The S&P CoreLogic Case-Shiller Home Price indices show prices rising at a 6% annual rate over the last year and a half. The pace may be welcome news to selling homeowners, but it is pricing buyers out of the market. Compared to 6% price gains, inflation is about 2% and wage gains are approaching 3%, squeezing some potential buyers out of the market. Mortgage interest rates are also creeping upward, raising monthly mortgage payments.  The recently passed Federal tax law adds further pressure. The cap of the deductibility of property tax could raise the cost home ownership.

The slowdown in housing is not good news for the economy. While residential construction is a small portion of GDP, sales and remodeling of existing homes affect large sections of the economy. Further, signs that future homebuyers are being priced out of the market will dampen consumer sentiment. Traditionally housing and auto sales follow similar patterns; auto sales are down for much of 2018 though they rebounded in September.

A positive note to end with is the first mortgage default data from the S&P/Experian Consumer Credit Default indices – defaults are lower now than before the financial crisis.

The S&P Indices Versus Active (SPIVA) Europe Mid-Year 2018 Scorecard is often cited for its latest headlines surrounding the active vs. passive debate. But beyond the SPIVA headlines, there is an extensive offering of insightful data that has been carefully measured and presented to help readers dig deeper.

Let’s look at just one example from the latest SPIVA Europe Scorecard and discuss the treasure trove of information that can be gleaned from the report.

Headline: 59% of active pan-European equity funds (euro-denominated) failed to beat the S&P Europe 350 from June 2017 to June 2018.

1. Appreciating the Longer-Term Trends

First, how does this headline figure compare to its track record over longer time periods and to other fund categories?

The proportion of funds in the category failing to beat the same benchmark rose to 87% over the 10-year period. While these figures may appear high, European active funds investing in U.S., global, or emerging market equities appeared to do markedly worse.

2. Assessing Fund Category Performance

Contrary to what the headline may suggest, active funds investing in pan-European equities collectively outperformed the S&P Europe 350 over the one-year period. The average asset-weighted return for the active fund category was 4.02% from June 2017 to June 2018 (equal-weighted return was 3.75%). In comparison, the S&P Europe 350 one-year return was 3.46%.

Asset-weighted returns may be considered a better indicator of fund category performance compared to equal-weighted returns, since they reflect the returns of the total money invested in that particular category with more accuracy. When asset-weighted returns are higher than equal-weighted return calculations, then we know larger funds typically did better.

See how the returns compared to other fund categories in the one-year period and over longer time periods in Exhibit 2.

3. Investigating the Distribution of Fund Returns

We already know there must be a skew in the returns across the funds in this category, since the average fund return beat the benchmark while the majority did not. Put another way, the mean was higher than the median return. The quartile breakpoint report (Report 5 in the SPIVA Europe Mid-Year 2018 Scorecard) takes this analysis one step further by giving the performance of the actual fund, which sits at the 25^th, 50^th, and 75^th percentile by rank.

For our headline category, the third quartile fund had a performance of 0.47% in the year; nearly 3% lower than the benchmark. The first quartile fund had a performance of 5.6% in the year; just over 2% better than the benchmark. This imbalance suggests that relatively few funds may have done particularly well.

4. Analyzing the Survivorship Rates

How does the survivorship rate compare to other fund categories and, more importantly, how consistent is it through time?

The survivorship report in the SPIVA Europe Scorecard tells us there were 1,101 funds used to calculate this headline figure. These funds represent the opportunity set available at the beginning of the period in this category. If we were to calculate the figures using only surviving fund data then any conclusions could be biased by excluding funds that would have liquidated or merged due to poor performance.

Since the headline figure counts the funds that survived and beat the benchmark index, it is also useful to see the survivorship rate in isolation. In this case, 96% of the 1,101 funds survived the one-year period of analysis. Over the 10-year period, the survivorship rate drops to just 45%. As can be seen in Exhibit 3, this is widely typical across all fund categories.

To take a look at more headlines and all of the related reports that help our readers see the full picture, please see the latest SPIVA Europe Mid-Year 2018 Scorecard.