Global equities had a strong start to the year as economic resilience and diminishing recession fears boosted risky assets overall. The S&P Global BMI surged 7.8% in the first quarter, led by developed markets; notably, the S&P 500^® finished the quarter up 10.6%, at a new record high. Shariah-compliant global benchmarks beat their conventional counterparts, with the S&P Global BMI Shariah and Dow Jones Islamic Market (DJIM) World Index generating an outperformance of 0.8% and 0.6%, respectively, during the quarter. The DJIM World Emerging Markets Index was a laggard, trailing behind the conventional benchmark as well as the developed market counterpart (see Exhibit 1).

MENA equities lagged along with emerging markets, with the S&P Pan Arab Composite posting a modest gain of 3.2%. Egypt was among the worst performers, with the S&P Egypt BMI falling 27.4% in U.S. dollar terms. The Egyptian pound shed over one-third of its value against the U.S. dollar during the quarter, as the country agreed on a USD 8 billion support program with the International Monetary Fund and let go of control on its currency in a bid for economic stability. GCC countries largely posted gains led by Kuwait (8.1%) and Bahrain (8.0%), while Qatar was an exception, with a 3.3% loss.

Drivers of Shariah Index Performance in Q1 2024

All sectors contributed positively to the S&P Global BMI Shariah in the first quarter. Extending the trend in 2023, Information Technology continued to be the largest contributor, accounting for 44% of the index return and generating an excess return of 1.3% versus the conventional benchmark. On the other hand, Financials contributed most negatively to the relative performance, with an excess return of -1.2%, due to its lower weightings as compared to the conventional benchmark (see Exhibit 2).

Global Sukuk Fared Better than Bonds in Q1 2024

The Sukuk market was largely muted, with a close-to-zero gain in the first quarter as measured by the Dow Jones Sukuk Index. The benchmark outperformed the regional MENA and GCC Bond & Sukuk benchmarks as well as the global iBoxx USD Overall, as shorter-dated securities generally outperformed longer-dated ones during the quarter.

This article was first published in IFN Volume 21 Issue 16 dated April 17, 2024.

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

Since the first publication of the S&P Indices Versus Active (SPIVA^®) U.S. Scorecard in 2002, S&P Dow Jones Indices has regularly reported on the relative performance of actively managed funds versus benchmark indices across an increasing number of global fund markets and fund categories.¹

The SPIVA Japan Scorecard has been tracking the performance of active funds offered in Japan since 2014, covering large-, mid- and small-cap segments, as well as international and global equity funds. Over these years, we found that a significant majority of active funds in Japan underperformed their assigned benchmark in each of our reported fund categories. Exhibit 1 summarizes the underperformance rate of active funds in Japan over the 1-, 3-, 5- and 10-year periods ending on Dec. 31, 2023, across different fund categories.

While 2023 marked an epic turnaround for Japanese equities with a reprieve from long-suffering deflation, it was a challenging year for Japanese active managers. 78% of Japanese domestic equity funds (All Japan Equity category) underperformed the broad-based S&P Japan 500 over the full year 2023. Furthermore, over two-thirds of equity funds underperformed their benchmarks in every reported category, posting underperformance rates worse than their 10-year averages in nearly all categories except for the U.S. Equity (see Exhibit 2).

What could explain last year's misfortune of Japanese active fund managers? Among many possible explanations, we found three market conditions that posed challenges for active managers.

1. Large-cap outperformance: The outperformance of large-cap companies was one of the key market trends in 2023. This was well publicized in the U.S. market with the so-called "Magnificent Seven," namely Apple, Amazon, Alphabet, Meta, Microsoft, Nvidia and Tesla, which contributed 58% of the S&P 500^®'s return in 2023. Similarly in Japan, the large-cap S&P/TOPIX 150 outperformed the S&P Japan MidSmallCap by 4% in 2023, resulting in increased market concentration (see Exhibit 3). This environment would have worked against active managers who searched for a source of outperformance among smaller, lesser-known names.
2. Falling dispersion: Dispersion,² the degree to which stocks differ from the average performance, measures the opportunity set for active managers to outperform through stock selection. Dispersion moved lower globally in 2023, though it remained elevated relative to its history (see Exhibit 4), which points to reduced opportunities for active managers overall.
3. Return distribution: Stating the obvious, when fewer stocks outperform the benchmark, it becomes less likely for managers to find them. In 2023, the percentage of constituents outperforming their benchmark fell well below 50% across domestic and global benchmarks amid a strong market rally. In Japan, the percentage of constituents outperforming the S&P 500 Japan dropped from 58% in 2022 to 44% in 2023 (see Exhibit 5).

¹ See SPIVA Around the World and SPIVA Fixed Income Around the World for the latest results of equity and fixed income funds across all covered markets.

² See Tim Edwards and Craig J. Lazzara, "Dispersion: Measuring Market Opportunity," S&P Dow Jones Indices LLC, 2014

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

Commodity markets remain on top of the asset class leader board with inflation drawing the ire of the Fed and other asset classes. The upside surprise in U.S. inflation spotlights the potential benefits of commodities as a diversification tool. The S&P GSCI, the leading indicator of broad commodity performance, has produced double-digit returns in 2024, currently up 12.8% following the uptick in consumer prices. Gold continues to reach all-time highs, surpassing USD 2,344 per troy ounce while cocoa is the best-performing commodity, nearly tripling over the past year. Both components are included in the S&P GSCI, helping produce a diversified exposure to the broad commodity market. For perspective, bitcoin has captured sizable flow into ETFs, and the S&P Bitcoin Index is "only" up 140%, less than half of what cocoa has done in the same period. The S&P GSCI has benefited from holding gold and cocoa, but oil is the largest component and has delivered the strongest historical sensitivity to inflation. The petroleum sector within the S&P GSCI is up 21.4% YTD, with precious metals up 13.2%. In this post, we review the last half century of commodity performance, which covers inflationary regimes and central bank responses.

Commodities have done well when inflation remains elevated, and the Federal Reserve maintains a defensive posture. Breaking inflation into low, medium and high inflationary environments, commodities have experienced double-digit annual gains when inflation exceeds 2%. The average one-year return when inflation measures between 2% and 4% is 13.3%. Exhibit 1 shows the breakdown by inflationary tiers.

Another way to measure commodity performance is when the Fed maintains a restrictive stance, defined by the Fed Funds Effective Rate exceeding target inflation of 2%. Again, going back the full history of the S&P GSCI to 1970, we measure the annualized returns during such periods and compare that with accommodative environments. The S&P GSCI achieved average annualized returns of 10.6% over the 39 years when the Fed Funds Effective rate was above 2%. This compares favorably to 0.9% average annualized returns during the 16 years the Fed held the effective rate below 2%. We recently covered this in a blog post, and updated the data through April in Exhibit 2.

A broad basket of commodities has historically helped provide diversification and inflation protection. Unlike traditional asset classes such as stocks and bonds, commodities have unique risk and return characteristics that are often uncorrelated with other investments. The S&P GSCI's 10-year correlation to the S&P 500^® is 0.4, while its correlation to the S&P GSCI Gold component is zero and it has a negative correlation of -0.16 to the S&P U.S. Aggregate Bond Index. Including commodities could help reduce overall volatility and enhance risk-adjusted returns by spreading risk across different asset classes. Additionally, commodities have historically exhibited a positive correlation with inflation, making them a possible hedge against rising prices. As prices for commodities tend to rise during inflationary periods, broad-based commodity indices like the S&P GSCI have demonstrated low correlation to other asset classes as well as positive performance correlation to persistent inflationary environments.

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

S&P Dow Jones Indices launched a consultation in May 2023 proposing certain methodology changes to the S&P/BMV IPC with the overall goal of reducing single-stock concentration and simplifying rather complex eligibility and selection criteria.

After receiving feedback from market participants, a revised version of the proposal was approved in September 2023 and a two-phased implementation was announced starting with the March 2024 rebalance and concluding in June 2024 (see Exhibit 1 for a summary of the changes).

The main objective of these changes was to improve diversification by reducing stock concentration in the index. Exhibit 2 shows how the top five stocks represented about 53% of the index's weight on average over the past five years and the impact of the first phase of the implementation during the March 2024 rebalance.

The decrease in concentration is achieved by reducing the weight caps for single stocks to 15% and the aggregate weight of the top five stocks to 45%. Additionally, a new rule to limit the weight of relatively illiquid stocks was introduced to address the potential for higher weightings of less liquid securities.

The additional changes in the eligibility and selection criteria were made in order to provide flexibility under different market conditions and to simplify the methodology.

Regarding the implementation, all changes except for the updated constituent weighting rules were implemented in full at the March 2024 rebalance. Changes to the constituent weighting caps will be implemented in two phases.

The first phase applied a 0.5 factor to the weight reduction of the capped stocks, with the resulting weight redistribution among the rest, for the March 2024 rebalance, with the intent of incorporating approximately half of the weight changes under the new rules (see Exhibit 3 for the new constituent weights in this first phase).

The final phase of implementation will be conducted at the June 2024 reweighting, where the changes in constituent weightings will go into full effect.

In summary, the methodology changes will contribute to improving diversification and flexibility in the S&P/BMV IPC, while at the same time, simplifying the methodology for the benefit of market participants.

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

Launched in February 2019, the S&P 500^® GARP Index was the first transparent benchmark tracking growth companies that are identified as being higher quality with lower valuations. Given the success of this index, we launched the S&P MidCap 400^® GARP Index and S&P SmallCap 600^® GARP Index to expand the available toolkit. Since their launches in 2023, these two indices have outperformed their corresponding benchmarks by a wide margin (see Exhibit 1). For market participants seeking to diversify their mega-cap exposures, the S&P MidCap 400 GARP and S&P SmallCap 600 GARP Indices may provide two alternatives. In this blog, we investigate the index's design, performance, characteristics and attribution. Rationales and Index Design

The S&P GARP Index Series strives to select companies with top earnings and sales growth, strong earnings power, solid financial strength and reasonable valuation. To meet the index objective, the S&P GARP Index Methodology uses a two-layer sequential filtering approach to select its constituents (Exhibit 2).

In the first step (filter 1), stocks are ranked by their growth z-scores (three-year earnings per share [EPS] and sales per share [SPS] growth), with the top 30% of the universe stocks remaining eligible for constituent inclusion. In the second step (filter 2), the eligible stocks are ranked by their quality and value (QV) composite z-scores and one-half of the top-ranked stocks are selected.¹ The QV score is based on the average of two quality factors (return on equity and financial leverage ratio) and one value factor (earnings-to-price ratio).

The selected constituents are weighted proportional to their growth exposure, subject to the maximum individual weight of 5% and sector weight of 40%. This approach seeks to provide high growth exposure and limit concentration risk.

Performance Comparison

Historically, the S&P GARP strategies have outperformed their corresponding benchmarks over the short and long term with respect to total return and risk-adjusted return (see Exhibit 3). Additionally, they have tended to exhibit growth characteristics, as evidenced by a higher participation ratio in up markets and a similar participation ratio to their benchmarks in down markets.

Balancing Growth and Value

The S&P GARP Indices seek to strike a balance between growth and value. Historically, they have outperformed their corresponding growth and value strategies over the short and long term with respect to total return (see Exhibit 4a and 4b) in both S&P MidCap 400 and S&P SmallCap 600 universes.

Sector Exposure

We next explore the relative sector exposures² of the S&P GARP strategies versus their corresponding underlying universes (S&P MidCap 400 and S&P SmallCap 600). As seen in Exhibit 5, GARP strategies historically have had a significant overweight in Consumer Discretionary (close to +10%) relative to their corresponding benchmarks, with a large underweight in Financials (about -5.5%) and Utilities (about -3.5%).

Factor Exposure

Exhibit 6 shows the factor exposure of the S&P GARP strategies versus their corresponding benchmarks in terms of the Axioma US Risk Model Factor Z-scores. In line with their design objectives, the S&P GARP strategies demonstrated strong growth, quality and value tilts versus their corresponding benchmarks. Specifically, the S&P GARP strategies had higher exposures to EPS and sales growth, profitability and value factors, with a lower exposure to leverage ratio than their corresponding benchmarks.

¹ Please refer to the methodology for more details. The indices apply a 20% selection buffer according to the following process: 1. Rank the top growth z-score stocks by QV composite z-score. Select automatically the top 80% highest ranking stocks for index inclusion. 2. Select current constituents ranked within the top 120% by QV composite z-score for index inclusion in order of QV composite z-score until the target QV count is reached. 3. If, at this point, there are not enough constituents selected to meet the QV count, select non-constituents based on QV composite z-score ranking until the target count is reached.

² Relative sector weight = GARP sector weight - corresponding benchmark sector weight

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