We consider a dynamic equilibrium model of algorithmic trading (AT) for limit order markets. We show that AT improves market performance ‘only’ under specific conditions which are analyzed through diverse market quality measures. For instance, AT traders prefer to act as either demanders or suppliers of liquidity depending of market participation of ‘less-skilled’ investors, which may damage (or improve) liquidity and welfare. AT reduces waiting costs but finally damages traditional traders’ profits and changes their trading behaviour. AT traders prefer volatile assets, and we report that cancellation fees may be better policy instruments to control AT activity than latency restrictions.
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