Measuring Concentration Risk in Equity Markets Through HHI and Gini Metrics

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Concentration risk arises when too much exposure is tied to a single firm, sector, or asset. If one company, or a handful of large players, becomes too big in a portfolio or market, their failure can drive outsized losses. In essence, concentration risk is the danger of being undiversified: the success or failure of just one exposure can disproportionately affect overall performance.

In the banking sector, credit portfolio managers often use indicators such as the Herfindahl–Hirschman Index (HHI) or the Gini coefficient to measure and manage concentration risk. Reference [1] extends this approach to equities, examining how equity index concentration affects stock market performance in the S&P 500, NASDAQ 100, and STOXX Europe 600. The authors pointed out,

By extending the research to the factor analysis using the Carhart four-factor model, we can confirm that industry-level concentration also negatively affects alpha and predicts elevated idiosyncratic volatility beyond systematic factors. We also conclude that the excess returns of the S&P 500 are affected by firm-level concentration through factor exposures, and possibly temporary overvaluation which reverses in the long-term. Moreover, the finding of short-term positive effect on returns of the NASDAQ 100 on the firm-level is explained by factor exposures, and the long-term effect could be explained by the relatively different index composition consisting of tech giants. While the STOXX 600 exhibits immediate negative effects on alpha, this could potentially be explained by the relatively smaller role of passive investment in Europe, differing investor sentiment, and the larger and more diversified nature of the index. Additionally, we find that while some increased volatility especially in the U.S. indices could be explained by factor exposures, concentration increases idiosyncratic volatility beyond systematic factors, possibly due to temporary overvaluations, increased price pressure resulting from passive flows, and lower effective number of stocks.

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In short, the study finds that industry concentration leads to lower alpha and higher idiosyncratic volatility beyond systematic factors.

Let us know what you think in the comments below or in the discussion forum.

References

[1] Timi Oksanen, Niko Ollila, Concentration in Equity Indices: Implications for Returns and Volatility, Aalto University, 2025

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