International Evidence on Algorithmic Trading

We study the effect of algorithmic trading (AT) intensity on equity market liquidity, short-term volatility, and informational efficiency between 2001 and 2011 in 42 equity markets around the world. On average, AT improves liquidity and informational efficiency, but it increases volatility. This result is robust to a range of different volatility measures and it is not due to more ‘good’ volatility that would arise from faster price discovery. Moreover, this result does not reflect algo traders’ inclination to enter the market when volatility is high, because these volatility-seeking traders are associated with declines in market quality. Our results are surprisingly consistent across markets, but they vary in the cross-sections of stocks. In contrast to the average effect, more AT reduces liquidity in small stocks; has little effect on the liquidity of low- priced or high-volatility stocks; and leads to greater increases in volatility in these stocks. Finally, AT is more beneficial when there is greater competition from traditional market makers.