High Frequency Trading and Financial Stability

Over the last three decades, financial markets have undergone through an epochal revolution. The main driver of this profound change has been, as always, technology. Trading floors are not anymore full of yelling traders who shout orders from one side of the exchange to the other. People now need to adapt their mental picture of financial markets to a new representation: no more humans, only a collection of silent servers which collect and storage terabytes of data. In the first chapter, I will explore how financial markets have reached this new macro and micro organization. I will present the difference between algorithmic (AT) and high frequency trading (HFT). Then I will explain the reason why speed has become a crucial factor for financial markets. For this purpose, I will introduce the concepts of co-location, latency and nanosecond. Then I will discuss some trending market dynamics, such as exchanges’ fragmentation, competition between “light” and “dark” platforms and predatory behaviors. In the second chapter I will discuss the role of high frequency traders and their relative weight with respect to other players. A discussion of their main trading strategies, which kind of stocks they prefer and how they capture information from the market will follow. With regards to the latest point, I will also explore the relationship between HFT, big data and artificial intelligence. I will conclude my thesis exploring how and why HFT have had a huge and profound impact on financial markets stability. Therefore, I will deal with huge events as the Flash Crash and Flash Dash. Moreover, I will address which role regulators have played and could play in the future with respect to this topic. In this chapter, I will also present some results of my empirical research.