In classical market microstructure, adverse selection risk is driven by private information or information asymmetry; thus, market-makers tend to widen their bid-ask spreads when confronted with this risk. Traditionally, adverse selection risk is linked to more skilled investors/traders acquiring and exploiting information at the expense of the so-called uninformed traders. However, in today's high-frequency trading (HFT)-dominated financial markets, informed traders need not be skilled at acquiring private information; they simply need to be faster at trading on what may already be public information. Although public information may be observable by all traders at the same time, faster traders react and complete their trading with slower traders before the latter can defensively update their orders or issue cancelations. This is latency arbitrage, which is essentially the HFT version of adverse selection. Thus, in a world where latency arbitrage exists, the speed of reaction to new information may end up being the most significant source of the adverse selection cost faced by slower traders. This implies that market participants of all types will invest in faster technologies either to either impose latency arbitrage linked adverse selection on other traders or to avoid being adversely selected. This succinctly sums up the origin of the so-called technological arms race phenomenon in financial markets, a phenomenon seen by many as a symptom of a flawed market design. In this thesis, I address the market quality and associated market structure issues arising from its emergence. Starting from the perspective that sub-second frequent batch auctions (FBA) has often been touted as a market design response aimed at shielding slower traders from adverse selection, in the first chapter, I empirically examine the market quality effects of FBA. Specifically, I exploit recent European regulatory restrictions on dark trading, which should induce an increase in FBA volumes, to investigate the effects of FBA on market quality characteristics in UK-listed stocks. The UK financial markets - the most active trading environment in Europe during the sample period - offer a unique opportunity to assess the direct effects of a shift in trading volume towards FBA following the imposition of dark trading restrictions in the markets. Using a series of difference-in-differences and instrumental variable frameworks and large ultra-high frequency dataset, I show that, as expected, the (regulatory) restrictions on dark trading are linked to an observable increase in FBA volumes and an economically meaningful loss of market liquidity. I also provide evidence that FBA is directly associated with a significant decline in liquidity and informational efficiency. However, increased order execution via FBA leads to a decline in adverse selection costs, which underscores its potential as a trading mechanism for addressing latency arbitrage and the technological arms race. This finding sets up the question for the study I report in the second empirical chapter of my thesis. In the third chapter, I investigate the relationship between latency arbitrage and trading via FBA. I propose five linked hypotheses to exhaustively ascertain whether a relationship exists between FBA and latency arbitrage and the nature of any such relationship. Using a sample including more than 324.5 million transactions executed in FTSE 100 stocks between 2019 and 2020 and a stock-panel intraday regression framework, I show that increases in single-market and cross-market latency arbitrage opportunities (LAOs) - a proxy for latency arbitrage - are linked to an economically meaningful increase in FBA activity. This implies that slower traders view trading in FBA as an effective strategy to avoid being adversely selected on speed by faster traders. This effect is consistent irrespective of whether LAOs are toxic or not; however, they vary in their magnitude by LAO duration. Shorter LAO durations are linked to progressively more severe shifts in trading activity from the standard continuous trading mechanism to FBA. The final empirical chapter recognises that emerging market phenomena, such as latency arbitrage, interact with other market phenomena that are still not well understood and complicates attempts to disentangle their effects. The chapter attempts to fill this void by investigating the interrelatedness of latency arbitrage, flash crashes and dark and lit market fragmentation. By exploiting regulatory and grey rhino events, such as the earlier referenced dark trading restrictions and Brexit, in two natural experiments, and a broad sample of FTSE100, CAC40, and DAX30 stocks, I show that a fragmented market, irrespective of whether the fragmentation tends towards dark or lit trading, can be beneficial from a market quality perspective by impacting the negative influences of HFT activity, such as latency arbitrage and flash crashes. Nevertheless, the analysis underscores the complex nature of the interactions among the various market phenomena examined.