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We study the effect of algorithmic trading (AT) on market quality between 2001 and 2011 in 42 equity markets around the world. We use an exchange colocation service that increases AT as an exogenous instrument to draw causal inferences about AT on market quality. On average, AT improves liquidity and informational efficiency but increases short-term volatility. Importantly, AT also lowers execution shortfalls for buy-side institutional investors. Our results are surprisingly consistent across markets and thus across a wide range of AT environments. We further document that the beneficial effect of AT is stronger in large stocks than in small stocks.

We study the informativeness of trades via discount and full-service retail brokers. We find that trades via full-service retail brokers are statistically and economically more informative than are trades via discount retail brokers. This finding holds in every year over the 12-year sample period and in various subsamples. We also find that past returns, volatility, and news announcements positively relate to the net volume of discount retail brokers, but these variables are unrelated to the net volume of full-service retail brokers. Our results suggest that broker type selection bias is an important consideration in studying individual investors’ trades.