Algorithmic trading (AT) has significantly increased over the past decade, and this paper investigates whether it improves market liquidity. Using the New York Stock Exchange (NYSE) automated quote dissemination in 2003 as an exogenous instrument, the study finds that AT improves liquidity, particularly for large-cap stocks. AT narrows spreads, reduces adverse selection, and reduces trade-related price discovery. The findings indicate that AT enhances the informativeness of quotes and improves liquidity. However, the relationship between AT and liquidity is not necessarily causal, and further research is needed to confirm the long-term effects. The paper also discusses the broader implications of AT on market quality and the potential for AT to lead to an unproductive arms race between liquidity suppliers and demanders. The study concludes that AT has salutary effects on market quality and should be encouraged.Algorithmic trading (AT) has significantly increased over the past decade, and this paper investigates whether it improves market liquidity. Using the New York Stock Exchange (NYSE) automated quote dissemination in 2003 as an exogenous instrument, the study finds that AT improves liquidity, particularly for large-cap stocks. AT narrows spreads, reduces adverse selection, and reduces trade-related price discovery. The findings indicate that AT enhances the informativeness of quotes and improves liquidity. However, the relationship between AT and liquidity is not necessarily causal, and further research is needed to confirm the long-term effects. The paper also discusses the broader implications of AT on market quality and the potential for AT to lead to an unproductive arms race between liquidity suppliers and demanders. The study concludes that AT has salutary effects on market quality and should be encouraged.