The Joint Impact of Fragmentation into the Dark and Algorithmic Trading on Implicit Trading Costs and Market Manipulation

Abstract

The authors investigate the effects of algorithmic trading and lit/dark fragmentation on US equity market quality. Market quality refers to the efficiency of lower implicit trading costs as well as market integrity, which are addressed here as reduced end-of-day (EOD) trade-based manipulation. A simultaneous equations model of effective spreads, a proxy for algorithmic trading, and EOD manipulation is carefully specified, and the instrumental variables are pretested to confirm exogeneity and strength. They estimate how fragmentation of the lit and dark order flow in NYSE-listed firms pre and post Regulation National Market System (Reg NMS) along with high frequency algorithmic trading (HFT/AT) jointly determine round-trip implicit transaction costs and EOD manipulation. The authors find that lit (dark) market fragmentation lowers (raises) effective spreads, reduces (increases) EOD manipulation, and increases (decreases) HFT/AT once Reg NMS establishes quote discipline.