Electronic Theses and Dissertations

Date of Award


Document Type


Degree Name

Ph.D. in Business Administration

First Advisor

Robert Van Ness

Second Advisor

Bonnie Van Ness

Third Advisor

Stephen Fier

Relational Format



In Part 1, I analyze independent technological malfunctions that forced trading halts at various equity exchanges over the past decade. During each halt, all other exchanges remained open. The primary purpose of this study is to examine intraday trading activity before, during, and after a technological malfunction, which are events that are neither driven by an informational event nor an order imbalance. Of the events I record in this study (8 technological malfunctions), a majority document a reduction in liquidity and an increase in short term volatility during and immediately after a technological malfunction. Furthermore, these affects appear to be relatively short-term but, in a few events, I see abnormal trading as far out as 10 days. Additionally, I investigate what impact these events have on algorithmic trading activity and find that algorithmic trading activity increases intra- and post-suspension. In part 2, I examine the extent algorithmic trading and highly fragmented stock markets are related. In this study, I use multiple methods to determine the level of fragmentation and examine algorithmic trading activity. Additionally, I dissect this relation further to determine what influence trading fees have on algorithmic trading and the possible appeal that different fee venues provide algorithmic traders. I find evidence that suggest more fragmented stocks will have a more algorithmic trading activity, and that this activity will be concentrated on make-take venues where algorithmic traders are paid a rebate to provide liquidity. I also demonstrate using the number of daily stock venues recorded by the SEC’s Midas dataset that there exists an inverted ‘U’ shape pattern between the number of daily venues a stock trades on and trading costs. In part 3, considering the SEC’s recent focus on addressing liquidity concerns for stocks with an average daily volume (ADV) below 100,000 shares, thinly traded securities, in this study I identify possible determinants of the poor liquidity of these types of securities. Among the commentary at a roundtable discussion held by the SEC in October of 2019, I identify there to be three prominent factors influencing daily liquidity in thinly traded stocks: (1) spatial fragmentation, (2) temporal fragmentation, and (3) market making activity. I find evidence that suggests that temporal fragmentation and market making activity appear to be more prominent factors contributing to the poor liquidity of thinly traded stocks. I also find that the market is capable of creating liquidity on its own without special advantages given to select exchanges and that spatial fragmentation doesn’t appear to be severely impacting transactions costs in thinly traded stocks. I further make use of the SEC’s Tick Size Pilot Program as a robustness check to confirm that temporal fragmentation and the lack of market makers are two driving factors influencing the differences in liquidity between thinly traded stocks and actively traded stocks.



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