The market ecosystem in the age of algorithms: An analysis of trading dynamics and market quality

Abstract This paper examines the impact of algorithmic trading on market quality using a unique NASDAQ OMX Nordic dataset from 2010–2011. We classify traders into algorithmic, institutional, professional, and retail categories. Using two-way fixed effects models and instrumental variables estimation, we find that algorithmic traders enhance liquidity by reducing bid-ask spreads by 0.28 basis points relative to retail traders, with similar effects from institutional traders. These effects persist during high volatility periods, while professional traders are associated with wider spreads. Surprisingly, retail traders emerge as significant liquidity providers, while algorithmic traders exhibit higher order cancellation rates. These findings contribute to the debate on algorithmic trading's role in modern markets and offer implications for market design and regulation.