Abstract
In the study reported here, we explored high-frequency algorithmic trading and its effect on exchange-traded funds (ETFs). Using the cancel rate, the trade-to-order ratio, percentage odd-lot volume, and trade size as proxies for algorithmic trading, we found that more algorithmic trading in ETFs results in smaller and less persistent deviations of fund prices from their net asset values (NAVs). Arbitrage strategies adopted by algorithmic traders directly help reduce the magnitude and persistence of ETF price deviations from NAVs. Also, algorithmic trading improves ETF liquidity by lowering spreads and facilitates arbitrage.
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