ETFs
How to Measure Risk in Digital Economy ETFs
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Deciding what a proper definition of risk is is a central question in finance. This is because the risk of financial loss determines not just financial returns, but also finance professionals’ career prospects, systemic risks for the economy, etc. To reduce risk, a central tenet of modern finance is to embrace diversification, reducing the dangers coming from a single stock.
A technology used to diversify a portfolio, and so in theory reduce risks, is Exchange Traded Funds (ETFs). By integrating many stocks into one single, easily tradable security, ETFs provide the possibility to diversify a portfolio while keeping complexity and fees low.
But spreading investment over hundreds or even thousands of companies with ETFs is not a guarantee of eliminating risks. For example, a thematic ETF will still expose investors to concentrated thematic risk, with all the stocks of a given sector likely to move in synchronized fashion in reaction to industry-wide trends.
A recent study by Chinese researchers at Beijing Foreign Studies University, Henan Industry and Trade Vocational College, and Guangxi University has investigated how digital-economy ETFs can still experience persistent volatility clustering and potentially asymmetric reactions to market shocks. It provides investors with insights and practical guidance for model selection and tail risk monitoring in thematic ETF portfolios.
They published their findings in the International Review of Economics & Finance1, under the title “Investing in digital economy: Evidence from volatility and risk management”.
Diversification & Risk
In the past decades, digital economic activities (data, networks, ICT, and then AI) have started to dominate developed economies: “the digital economy of 47 major economies accounted for 43.7% of their aggregate output in 2020.”
But systematic evidence on broader, equity-based digital economy exposures remains limited in academic economic research. While the study discussed here mostly focuses on China, it offers a useful example that could be expanded to a broader set of developed economies, where data are abundant and states support the development of digital activities.
“China’s National Bureau of Statistics released the Statistical Classification of Digital Economy (2021), which provides an official benchmark for defining digital economy activities and supports the development of thematic indices and investment products.”
This support concentrates capital flow into related ETFs and can amplify sensitivity to policy announcements and technology-cycle news.
Measuring Digital ETFs
Gathering Data
The researchers gathered data on the quantity and value of China’s ETFs related to the digital economy (keywords such as “digital economy,” “information technology,” “5G”, etc.), from January 1, 2014, to April 30, 2022.
They then selected two representative ETFs that satisfy theme representativeness and market relevance: Information Technology ETF (512330.SH) and the 5G ETF (512228.SH).
The researchers applied several GARCH-family models to estimate changing market volatility. They then used those volatility forecasts to calculate Value at Risk, or VaR, at confidence levels of 95%, 97.5%, and 99%. VaR estimates the loss threshold that a portfolio should exceed only a specified percentage of the time.
Volatility In ETFs
Despite their intention to reduce risks and spread out any single event, thereby reducing volatility, these 2 digital ETFs are still showing strong peaks in volatility.
In large part, this was due to external shocks to the broader economy, but also to industry-side effects, like the strong pressure on tech stocks in 2015 specific to Chinese markets.
“The 2015 breaking of the bull market asset bubble, trade frictions in 2018 and 2019, the COVID-19 outbreak in early 2020,3 the Russia–Ukraine conflict in 2022, and the impact of COVID-19 on the supply chain in 2022 are all negative shocks. During this period, the Information Technology ETF’s volatility is significant.”
Models Vs Assumptions
A finding useful for investors and economists is that the assumed return distribution can matter more than the specific GARCH model used.
This means that conventional normal-distribution models may understate extreme losses, leading to unexpected bad surprises not forecasted by risk models. In contrast, Student-t and generalized error distributions (“heavier-tailed specifications”) produced more conservative tail-risk estimates.
Why Value At Risk Is Not Enough
Value at Risk estimates a loss threshold, but it does not indicate how severe losses could become once that threshold is crossed. Expected Shortfall addresses this limitation by estimating the average loss within the worst portion of outcomes.
Across both ETFs, the study found that Expected Shortfall produced larger loss estimates and fewer exceedances than VaR. This makes the two measures complementary. VaR can indicate where unusually bad performance begins, while Expected Shortfall provides a better indication of how damaging those tail events could become.
Investors Takeaways
Thematic ETFs have been a great way for investors, especially retail investors, to get access to much-needed liquidity and diversification by providing exposure to hundreds or even sometimes thousands of different stocks in one low-fee transaction.
However, the very nature of thematic ETFs leaves them exposed to higher risks than a highly diversified ETF like one based on the S&P500 or a selection of global stocks. This is because the concentration on one industry naturally increases the chance of all the components of the ETF starting to move in the same direction at the same time, for good or bad.
Another important takeaway from this study is that historical returns or sector narratives are not enough information for ETF selection. Downside modelling, concentration, liquidity, and stress behaviour are equally important.
Finally, investors should always remember that while many financial models use normal distribution to model risk, most financial markets are “fat tailed” and will experience extreme volatility much more often than expected. Therefore, building a truly diversified portfolio is essential, and so is avoiding unwanted concentration through thematic ETFs that are too few or too closely related.
Investing In ETF Technology
MSCI Inc.
As ETFs have become the world’s most popular tool for financial diversification, the creators of such ETFs and the indexes that underlay them have immensely benefited.
MSCI is a world-class provider of financial instruments for both domestic & international investors through its various indexes and rating systems.
So while it is not producing the ETF directly, it sells the measurement, risk assessment, indexes, and disclosure infrastructure that institutional capital increasingly needs before allocating money.
Source: MSCI
Approximately $21 trillion in assets was benchmarked to MSCI indexes as of December 31, 2025, including $13.7 trillion in actively managed assets and $7.3 trillion in indexed assets.
This means the company’s 6,300+ employees are trusted by 6,700 institutional clients worldwide in 100+ countries.
Asset managers make up the majority of the company’s customers, followed by banks and asset owners. 45% are from the Americas and 38% from EMEA (Europe, the Middle East, Africa).
Source: MSCI
While often not perceived as one, MSCI is a full-fledged FinTech company, with 1,900 APIs across all product lines of 1,000+ data products covering 18 million different securities daily.
The company’s revenues are very stable, with 97% or higher of revenues recurring. Revenues grew at an 11% CAGR and free cash flow at a 13% CAGR between 2021 and 2026.
Source: MSCI
Overall, MSCI is a good stock for investors seeking exposure to the “piping” of the financial system, providing investors with highly valuable indexes, portfolio analytics, and multi-asset risk-management tools.
This makes it a pick-and-shovels investment angle, allowing the financial industry and investors to construct, measure, and stress-test thematic portfolios.
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(You can also read more about MSCI in our investment report dedicated to the company)
Latest MSCI Inc. (MSCI) Stock News and Developments
Study Referenced
1. Xiaolei Yan, Yuanchen Zhao, and Lingyu Huang. Investing in digital economy: Evidence from volatility and risk management. International Review of Economics & Finance. December 2026. Article: 105852. Volume 112. 10.1016/j.iref.2026.105852
