Real-Time Data Uncovers Large-Cap Volatility, Geopolitical Stress Amplifies It
Large cap stocks have long been considered the less volatile segment of the equity market, especially in developed markets. End-of-day (EOD) data largely supports this view, but real-time index data has told a different story.1
When we rank size segments using real-time index levels, U.S. large caps were the most volatile segment almost 40% of the time, nearly four times the frequency observed based on EOD data. In EAFE and emerging markets (EM), large caps ranked as the most volatile over 80% of the time. Both EAFE and EM regions, being more directly exposed to geopolitical shocks and oil supply disruption, have seen the average daily real-time volatility spread between large caps and small caps widen since the onset of U.S. and Israeli strikes on Iran.
End-of-day data misses the full picture
Investors relying solely on EOD volatility may underestimate the intraday risk of large cap stocks, particularly during geopolitical stress.2 Whether pricing intraday derivatives, calibrating Value-at-Risk models or sizing hedges, using only EOD data risks underestimating large cap volatility precisely when it matters most.
Volatility rank distribution for the MSCI Large Cap Index, Mid Cap Index and Small Cap Indexes in USA, EAFE and Emerging Markets using real-time and EOD index levels, sampled monthly. Period: June 30, 2010 to Feb. 28, 2026. Average daily volatility spread between MSCI Large Cap and Small Cap Indexes, YTD (Dec. 31, 2025 to Feb. 27, 2026) vs. since the onset of U.S. and Israeli strikes on Iran in USA, EAFE and EM using real-time data.
The authors thank Abhishek Gupta for his contributions to this quick take.
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1 Over July 2010 to February 2026, the MSCI USA Large Cap Index represented the least volatile size segment most of the time, while the MSCI USA Small Cap Index was the most volatile at 85%. Volatility rankings are based on MSCI regional size segment indexes (Large Cap, Mid Cap, Small Cap) using daily USD Gross index levels and their real-time equivalents sampled at 60-second intervals over July 2010 to February 2026. For each calendar month, realized volatility was calculated from daily (EOD) or intraday (real-time) index levels within that month and size segments were ranked from most to least volatile. The rank distributions reported reflect the share of months each segment held a given rank over the full sample period.
2 Range-based estimators using open-high-low-close (OHLC) data, such as the Parkinson or Yang-Zhang approaches offer a middle ground but do not capture the full intraday picture.
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