Indexology^® Blog

After political turmoil pushed it down in 2024,¹ South Korea recovered and was the best-performing equity market globally in 2025 (as measured by the S&P Korea BMI), and it has continued to outperform as of August 2026 (up 78.7% YTD versus 14.8% for the S&P Global BMI). The performance of the stock market has fluctuated over the years, but one debate has remained constant: South Korea’s market classification. Whether South Korea is classified as a developed market or an emerging market can materially affect country weights in an index. A 2020 Indexology^® Blog post² explored how the inclusion of South Korea in emerging market indices could crowd out less-developed countries. Six years later, what has changed?

To answer that, it helps to revisit South Korea’s classification. Since 2001, S&P Dow Jones Indices (S&P DJI) has classified South Korea as a developed market, a decision reaffirmed over the years based on feedback from a wide range of market participants. Since 2020, the South Korean economy has remained healthy, with GDP growing an average of 2.3% annually³ and its GDP per capita holding steady alongside the levels of other developed markets (see Exhibit 1).

Consistent with this, the float-adjusted market capitalization (FMC) of the S&P Korea BMI went from USD 0.91 trillion on Dec. 31, 2024, to USD 2.98 trillion as of Aug. 31, 2026. Even as the amount of foreign capital entering the stock market has grown,⁴ the government has released a series of reforms aimed at further enhancing its accessibility and liquidity.⁵, ⁶, ⁷ Still, not all index providers share the same classification perspective, reflecting different market expectation frameworks. Let’s look at how South Korea’s inclusion impacts the composition of indices.

Amid the outperformance of South Korean equities, the market’s footprint on global benchmarks has increased. As of the end of August 2026, South Korea represented 2.7% of the total FMC of the S&P Developed BMI, up from 2.2% in December 2020. However, its weight has grown even more sharply when placing it within an emerging market classification. In the S&P Emerging Plus AllCap Index, which includes South Korea, the country’s weight went from 14.3% to 18.6% over the same period. As South Korea’s weight has increased, so has its crowding-out effect (see Exhibit 2). When including South Korea in emerging market indices, weight in other less-developed countries is reduced.

The soaring of South Korean equities can mainly be attributed to the hardware and semiconductor industries, which have outperformed in the country amid growing interest in companies central to the AI revolution.⁸ From December 2024 to August 2026, the S&P Korea BMI had a cumulative performance of 341.2%, with the main contributors to performance being Samsung (388.7%), from the Technology Hardware, Storage & Peripherals GICS^® industry, and SK Hynix (862.7%), classified under the Semiconductors & Semiconductor Equipment GICS industry,. While the crowding-out effect of the semiconductors industry has remained modest at less than 1.0%, the impact has been more pronounced in the hardware industry, where the weight jumped from 2.8% to 8.8% when South Korea is included, largely due to Samsung’s dominant presence (see Exhibit 3). When South Korea was included in emerging market indices, Samsung and SK Hynix crowded out other industries.

Recent developments in the South Korean stock market and economy are consistent with S&P DJI’s developed market classification. Its inclusion in emerging market indices, however, has shown the potential to crowd out weights in less-developed countries and certain industries. S&P DJI offers indices that reflect a range of different perspectives, providing alternative lenses through which global equity markets can be viewed and measured.

¹ River Akira Davis and Jason Karaian, “South Korea’s Already Shaky Markets Further Rattled by Political Turmoil,” The New York Times, Dec. 3, 2025.

² John Welling, “Is South Korea Crowding Your Emerging Markets Allocation?” S&P Dow Jones Indices LLC, Nov. 23, 2020.

³ World Bank, GDP Growth, Republic of Korea.

⁴ “Foreign ownership of S. Korean stocks reaches highest in nearly 6 years,” The Korea Herald, Jan. 25, 2026.

⁵ Cynthia Kim, “South Korea starts 24-hour trading of dollar-won,” Reuters, July 5, 2026.

⁶ Ying-Shan Lee, “South Korea ends its longest short-selling ban after systemic reforms,” CNBC, March 30, 2025.

⁷ Heejin Kim and Jihoon Lee, “S. Korean President Lee vows more stock market reforms, triggering share rally,” Reuters, March 18, 2026.

⁸ Nick Didio, “Choppy Chips,” S&P Dow Jones Indices LLC, July 16, 2026.

Explore the structural forces shaping African sovereign debt markets and how they differ from their LatAm and APAC peers. 

Private credit has become one of the fastest-growing asset classes within global capital markets. In the first half of 2026 alone, private credit fundraising reached USD 190 billion, which is on pace to surpass the 2025 full-year total of USD 240 billion (see Exhibit 1).¹ Direct lending has driven much of private credit’s growth, having multiplied roughly sixfold between 2016 and 2024.² It is now the largest segment within private credit and an increasingly important source of financing for middle-market companies in the U.S. and Europe.

However, the rapid growth of private credit has prompted increased scrutiny, reflecting concerns about the asset class’s inherent opacity, volatility and valuation uncertainty. These concerns have been reinforced by recent headlines focusing on valuation practices, liquidity risk, redemption pressures and credit quality. As private credit continues to grow in scale and significance, market participants looking to understand and measure these changing dynamics need transparent and trusted benchmarks, but are often limited by lagged, manager-reported fund-level data. So, how can benchmarks keep pace and offer market participants the insights needed to effectively monitor this fast-evolving space?

Going Beyond Headline Performance

Private credit benchmarks have existed for years, but many are built on fund-level performance rather than on the underlying loans. This has created an incomplete picture of risk and volatility. Unlike public credit benchmarks that are supported by more timely and readily available data sources, reporting practices, data availability and calculation standards vary across private credit managers. The result is often a fragmented view of the market that makes constituents harder to compare and private credit more difficult to assess alongside public markets.

Closing this benchmarking gap requires richer fund- and asset-level data, along with a common framework for translating that information into standardized market measures comparable to those used in public markets. Frequent valuations and deeper data are also key for ensuring market participants have access to timelier information, which is particularly important during periods of market uncertainty when visibility becomes even more critical.

Loan-level data provides transparency into credit quality, yield, maturity profiles and portfolio concentrations across industries, seniority bands and borrower EBITDA segments. This information enables investors to better understand the underlying drivers of performance and identify evolving risks that top-line performance measures cannot.

Credible loan-level data, however, is only one part of the solution. The next generation of private credit benchmarks should combine asset-level information with consistent methodologies, trusted calculations and robust index governance. That combination creates a common reference point for evaluating performance and risk across managers, constituents and markets over time.

Building the Foundation for Better Measurement

Developing an enhanced benchmarking infrastructure increasingly requires collaboration across the private credit ecosystem. Many leading industry specialists have access to data that has historically been difficult to aggregate, while index providers contribute the methodology and governance needed to make it comparable. Together, these capabilities can help transform fragmented observations into reliable market benchmarks.

The S&P Lincoln Senior Debt Index Series, developed by S&P Dow Jones Indices (S&P DJI) in collaboration with Lincoln International, a global investment banking advisory firm, combines Lincoln’s private loan valuation data with S&P DJI’s transparent rules-based index methodology and governance framework. It measures illiquid senior debt facilities issued primarily to private-equity-sponsored companies in the U.S. and Europe, using granular loan-level insights to provide a systematic view of direct lending. This index series offers subscribers a rich set of credit metrics—including returns, fair value movements, yields, coupon spreads, leverage and borrower characteristics by firm size, sector and time period—that enable users to analyze how yields and spreads change over time, how risk differs between borrowers and how credit conditions vary across sectors (see Exhibit 2).

Better measurement will not erase the structural differences between private credit and public markets. It can, however, provide a clearer lens into performance, risk and market dynamics. As private credit continues to evolve, benchmarking infrastructure needs to evolve alongside it, helping the market move toward a new generation of benchmarks that offer greater transparency, comparability and possibility.

Learn more about the S&P Lincoln Senior Debt Index Series to see how we’re helping market participants assess performance and risk with greater transparency.

¹ “Private Credit Fundraising H1: Market on Course for Record Year,” With Intelligence by S&P Global, Aug. 12, 2026.

² Source: S&P Global, CapIQ. Data from Dec. 31, 2016, to Dec. 31, 2024, as presented in Exhibit 1 of S&P DJI’s “Measuring Direct Lending: Building Transparency in Private Credit Markets,” April 1, 2026.

As digital assets become more institutional, the need for a clear way to define, measure and compare them is becoming more pressing. Without relevant, and credible, benchmarks, fund managers can struggle to explain performance, and allocators their risk, when comparing strategies against the wrong reference point.

This is not just a theoretical challenge. It is already shaping how strategies can be evaluated and how capital is allocated among digital assets. Segmented benchmarks that provide clear definition and comparability can serve as effective tools for understanding and measuring the ecosystem.

Understanding the Investable Universe

As the first and largest digital asset, Bitcoin has been used by many fund managers and allocators as a rough proxy for market beta. While it can be useful as a first-pass comparison point, it is often not representative of the entire crypto market. There are now thousands of digital assets, and even among the top percentile and investable universe there are important nuances to consider.

Bitcoin, as a cryptocurrency, is widely considered a store-of-value asset. Therefore, its performance is largely tied to supply and demand. Bitcoin’s performance profile differs from other digital assets—such as ecosystem layers like Ethereum and Solana.

This highlights an opportunity for segmented benchmarks that provide a suitable, comparable reference point for the digital asset strategy being analyzed.

The Fund Manager Dilemma

In traditional asset classes, the relationship between a strategy and its benchmark is generally well understood. In digital assets, that relationship is still developing. Fund managers often struggle to find benchmarks that match what they invest in. A strategy focused on smaller, emerging, sector-specific or a diversified set of assets is very different from one centered on large-cap assets such as Bitcoin or Ethereum. This can present challenges for fund managers who are assessing and promoting their strategies.

For example, using a Bitcoin benchmark to measure the performance of an actively managed strategy containing multiple mid-cap cryptocurrencies and digital assets may lead to inaccurate conclusions. If Bitcoin does well in a particular market cycle, but the underlying strategy contains assets that did not, it may appear the fund is not providing alpha relative to the benchmark. However, the underlying risk characteristics and performance drivers are not similar and, therefore, the comparison may not be suitable.

A multi-asset benchmark can solve this dilemma. In the prior scenario, a benchmark that contains a mix of mid-cap digital assets can establish a clear definition of what is being measured and serve as an unbiased, comparable reference point. Fund managers can use this to right size how their strategy has performed through market cycles and promote accordingly.

Allocators Want More Clarity

Allocators face a similar challenge as fund managers when using Bitcoin as a standalone benchmark. When they compare active managers to it, investors are looking for whether outperformance is due to security selection, asset allocation or market timing. If they mistake broad market exposure for manager skill and stay invested, that may be a missed opportunity for investors to find true alpha-generating opportunities. In those cases, allocators could leverage a range of indices to meet their exposure needs.

This has real implications for institutional allocators who are deploying sizeable asset bases and managing tight fee budgets.

Designing Benchmarks to Meet Institutional Needs

To help solve both sides of the fund manager and allocator challenge, benchmark providers are creating methodologies that segment the digital asset market. Benchmarks can be designed for different use cases to include constituents by market cap, excluding large-cap assets, or to diversify through equal-weight approaches and a range of weighting scheme.

For those with a focus on income-oriented opportunities, using derivatives or combining cryptocurrencies with other asset classes like equities can be another approach to diversification. Each approach offers a different lens and can help align definition and measurement more closely with investment intent.

As the market continues to mature, having the right benchmark in place becomes increasingly important. It allows both managers and allocators to better understand performance and make more informed decisions about where to invest capital.

Explore how different benchmark approaches can be used to track the evolving digital asset market with S&P DJI’s digital asset benchmarking capabilities.

Volatility-controlled indices (VCIs) have become a cornerstone of indexed insurance product design, helping insurers navigate volatility while maintaining exposure to growth assets. S&P Dow Jones Indices recently published the paper Indexed Insurance: Embracing Volatility-Controlled Indices in Next-Generation Products, in which we explore the growth in popularity of VCIs, their performance across market environments and their evolution. The paper also examines how volatility-control strategies have adapted to support the growing indexed insurance market and the changing needs of modern market participants. Recent market performance demonstrates how quickly risks can emerge and evolve in today’s environment—highlighting the important role that VCIs may play in turbulent markets, as well as the inherent tradeoffs such strategies represent.

2025 and 2026 saw markets characterized by periods of heightened uncertainty, sharp market selloffs and rapid rebounds—all of which created a challenging backdrop for VCIs. Compared with broad equity benchmarks, VCIs generally helped mitigate drawdowns during periods of market stress, although their volatility-management frameworks also resulted in more muted participation during subsequent recoveries.

However, evaluating VCIs solely through the lens of short-term relative performance may not capture their broader role within indexed insurance products. Due to the nature of indexed insurance products, characteristics like rolling returns and rolling volatility may better reflect the potential value of VCIs as complements to benchmark indices in these products. As seen in Exhibit 2, both the S&P 500^® Daily Risk Control 15% Index and S&P 500 Dynamic Intraday TCA Index exhibited a narrower range of rolling one-year performance than the S&P 500, illustrating how a volatility-control mechanism may smooth the experience across different market environments.

A narrower distribution of rolling one-year performance suggests that the risk-control mechanisms may help reduce extreme outcomes and mitigate fat-tail risk, resulting in a more balanced performance distribution while preserving exposure to long-term equity growth. In particular, the S&P 500 Dynamic Intraday TCA Index was able to achieve higher rolling one-year performance than the S&P 500 and the traditional volatility control index.

While rolling performance highlights outcome consistency, realized volatility provides a direct measure of risk management effectiveness. As shown in Exhibit 3, both volatility-controlled indices generally maintained lower realized volatility than the S&P 500. The dynamic intraday approach further reduced realized volatility than traditional daily risk-control methods, highlighting the evolution of volatility-control technology.

VCIs can reflect the trade-off between downside protection and upside participation, but their characteristics extend beyond raw index performance. Recent market conditions have reinforced that VCIs are generally not designed to outperform in every environment. Rather, they seek to provide a more stable risk profile.