Market quality: the joint impact of algorithmic trading and fragmentation
thesisposted on 28.03.2022, 10:28 authored by Drew Harris
This thesis examines the combined effect of algorithmic trading and market fragmentation on market quality. Three distinct but inter-related research studies are conducted and the ultimate findings of the thesis are three fold. First, exchange listed companies can use stock splits to manage their tick size and influence the level of algorithmic market making in their security, which can subsequently impact the company’s liquidity. Stock splits alter a security’s relative tick size. In some cases, this change in relative tick size increases the quoted spread captured by market makers. This extra incentive improves liquidity and reduces transaction costs. Companies that undertake stock splits while already tick constrained increase the profit of market makers at the cost of liquidity takers. Second, the research shows that dark trading contributes very little to the price discovery of a market. Further, regulation that reduces the level of dark trading in a market does not impact the relative competitiveness in price discovery for cross listed assets. Third, the thesis examines the joint impact of fragmentation and algorithmic trading. Findings show that on exchange fragmentation increases market competition and reduced transaction costs, with two side effects: the joint growth of dark fragmentation and algorithmic trading. Dark trading reduces integrity by adding an alternate venue with lesser price impact, while algorithmic trading increases both market efficiency and integrity.