Three essays on the transformative role of technology in financial markets

Financial markets are vital for capital allocation and as a consequence, for the wider economy. They perform two primary functions: liquidity and price discovery. Liquidity refers to the ability to trade large quantities of an instrument quickly, and with relatively little price impact. Therefore, it offers investors the flexibility to make investment decisions. Price discovery encompasses the price formation process in financial markets and is, therefore, critical for efficient capital allocation. Both these functions are linked to the functioning of the wider economy. Over the last decade, financial markets have been transformed with the help of technology and are now a completely different proposition. Specifically, technological advancements, such as high frequency trading (HFT), have altered the structure of financial markets, the strategies of traders, and the liquidity and price discovery processes. These changes and developments have ignited a heated debate among academics and regulators. While some researchers claim that HFTs increase the market efficiency by improving the liquidity and price discovery (see as an example, Brogaard et al., 2014b), others argue that they create adverse selection risks for slow traders and contribute to market instability by exacerbating illiquidity shocks, such as flash crashes (see as an example, Kirilenko et al., 2017). Motivated by these contrasting views, this thesis investigates these issues, and is therefore situated at the intersection of financial markets, technology and regulations. It specifically examines the topical issues around the transformative role of technology in financial markets by adopting novel and unique approaches. In the first study, I present a novel framework illustrating the links between order aggressiveness and flash crashes. My framework involves a trading sequence beginning with significant increases in aggressive sell orders relative to aggressive buy orders until instruments’ prices fall to their lowest levels. Thereafter, a rise in aggressive buy orders propels the prices back to their pre-crash levels. Using a sample of S&P 500 stocks trading during the May 6 2010 flash crash, I show that the framework is correctly specified and provides a basis for linking flash crashes to aggressive strategies, which are found to be more profitable during flash crashes. The second study is a methodological contribution to the financial econometrics literature, in which I propose a state space modelling approach for decomposing a high frequency trading volume into liquidity- and information-driven components. Using a set of high frequency S&P 500 stocks data, I show that the model is empirically relevant, and that informed trading is linked to a reduction in volatility, illiquidity and toxicity/adverse selection. Furthermore, I observe that my estimated informed trading component of volume is a statistically significant predictor of one-second stock returns; however, it is not a significant predictor of one-minute stock returns. I show that this disparity can be explained through the HFT activity, which eliminates pricing inefficiencies at high frequencies. The third study exploits the impact of the international transmission latency on liquidity and volatility by constructing a measure of the transmission latency between exchanges in Frankfurt and London and exploiting speed-inducing technological upgrades. I find that a decrease in the transmission latency increases the liquidity and volatility. In line with the existing theoretical models, I show that the amplification of liquidity and volatility is associated with the variations in adverse selection risk and aggressive trading. I then investigate the net economic effect of high latency, which lead to the finding that the liquidity deterioration effect of high latency dominates its volatility reducing effect. This implies that the liquidity enhancing benefit of increased trading speed in financial markets outweighs its volatility inducing effect