ETF Trading and Informational Efficiency of Underlying Securities

Lawrence Glosten is the S. Sloan Colt Professor of Banking and International Finance at Columbia Business School. Suresh Nallareddy is an Assistant Professor at Duke University’s Fuqua School of Business. This post is based on a recent paper by Professor Glosten, Professor Nallareddy, and Yuan Zou.

The asset management industry has witnessed a tremendous growth in exchange-traded funds (ETFs). As a result, roughly 30% of U.S. equity trading volume is attributable to ETFs (Boroujerdi and Fogertey, 2015). [1] Regulators and academics have found evidence that ETFs have distorted the capital markets as a whole, leading to increased volatility, co-movement, and systemic risk, as well as affecting real managerial decisions (see Wurgler (2010) for a review). Despite these findings, there is scant systematic evidence on the relation between ETF trading activity and the informational efficiency of underlying securities. We find that ETF trading increases the informational efficiency of underlying securities by improving the link between fundamentals and stock prices. Specifically, firms with more ETF trading reflect incrementally more earnings news in their current stock returns.

Using a large cross-section of ETF holdings data from January 2004 to December 2013, we document that an increase in ETF trading is accompanied by an increase in price informational efficiency of the underlying stocks, as reflected in the increase in the relation between stock returns and earnings news. The effect of ETF trading on information efficiency should be conditional on the information environment and the degree of capital market competition. Consistent with expectations, when we conduct the information efficiency tests within different segments of the market, we find significant and improved informational efficiency among small firms (firms with market capitalization below the NYSE 50th percentile), stocks with low analyst following (firms with analyst following below the 75th percentile), and stocks with imperfectly competitive equity markets (number of shareholders below the 75th percentile). In contrast, we are unable to document such improvement for big firms, stocks with high analyst following, and for stocks with perfectly competitive equity markets.

Next, we expect systematic information that affects a basket of securities will result in ETF trading, as traders have little benefit to trade on firm-specific information by buying an ETF. Therefore, if ETF trading results in increased informational efficiency for underlying stocks, then the increase in informational efficiency should be attributable to systematic information rather than idiosyncratic information. We find evidence consistent with this conjecture. We decompose earnings into its systematic and firm-specific components, and find that the commonality component of earnings explains the increase in information efficiency but not the idiosyncratic firm-level earnings. This evidence is consistent with the conjecture that ETF trading results in prices that reflect systematic information in a timely manner, resulting in increased informational efficiency.

Finally, employing Russell 1000/2000 index reconstitution as an identification strategy, we investigate the effects of ETF trading on the information efficiency of underlying securities. Russell 1000/2000 index reconstitution offers an identification in which firms with similar characteristics have significant variation in ETF ownership. Specifically, Chang, Hong, and Liskovich (2015) document that small market capitalization change around a market capitalization rank of 1000 (cutoff rank for Russell 1000 index and the next 2000 ranked stocks constitute Russell 2000 index) moves a stock between Russell 1000 and 2000 indices, while the firms close to this rank are similar in terms of firm characteristics. However, as indexes are value-weighted, if a smallest (based on market capitalization) stock of Russell 1000 index switches to Russell 2000 index, ETF ownership of the stock increases significantly. Using this identification and difference-in-differences design, we find that the change in informational efficiency for firms moving to Russell 2000 from Russell 1000 is positive and significantly greater than the change in informational efficiency for firms moving to Russell 1000 from Russell 2000 index. Further, increases in informational efficiency is significantly greater for the firms with weak informational environment and imperfect capital market conditions when these firms are switched to Russell 2000 index relative to those that are switched to Russell 1000 index.


Boroujerdi, R., and Fogertey, K., 2015. ETFs: The Rise of the Machines, Goldman Sachs Equity Research., April 10, 2015.

Chang, Y.C., Hong, H. and Liskovich, I., 2015. Regression discontinuity and the price effects of stock market indexing. Review of Financial Studies 28:212-46.

Wurgler, J., 2010, Challenges to Business in the Twenty-First Century: The Way Forward. Chap. On the Economic Consequences of Index-Linked Investing (American Academy of Arts and Sciences).

1For example, the assets under management by ETFs have grown from a total value of $416 billion in 2005 to $2.5 trillion as of September 2014 (Economist, 2014). Further, during the last decade, ETF inflows grew by more than 25% per year. In contrast, traditional mutual funds grew by -3% per year (Boroujerdi and Fogertey 2015).(go back)

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