Impact of high-frequency trading on stock
Exchanges

Maastricht University | | | | School of Business & Economics | | | | Place & date: | Maastricht, 22 January 2013 | | | | Name, initials: | B.G.M. Lens | | For assessor only | | ID number: | I6048482 | | 1. Content | | Study: | International Business/Economics | | 2. Language structure | | Course code: | EBS1001 | | 3. Language accuracy | | Group number: | C | | 4. Language: Format & citing/referencing | | Tutor name: | Cigdem Akbulut | | Overall: | | Writing tutor name: | / | | Advisory grade | | Writing assignment: | High frequency trading paper | | Assessor’s initials | |
Your UM email address: brianlens@gmail.com
1. Introduction
On 6 May 2010 the stock market experienced a period of high instability generally known as the Flash Crash. This Flash Crash was the second largest point swing (1,010.14 points) and the biggest one-day point decline (998.5 points) in the history of the Dow Jones Industrial Average (Easley, Lopez de Prado, & O’Hara, 2010). For a few minutes, 1 trillion dollars in market value vanished. Therefore, it raised numerous alerts in the U.S. stock market and world markets. It was mainly attributed to the algorithms that nearly all high frequency traders (HFTs) use to make their stock trades. However, primarily blaming high frequency traders and their complex algorithms would ignore the other conditions that allowed the Flash Crash to occur.
This paper will have a look at other factors in the environment that might have influenced the market or participated in past breakdowns of the stock market.
Since HFT led to several crashes of the stock market after 2008, the purpose of this paper is to answer the question whether or not the level of dependence on automated trading algorithms that HFT brings with it, is a desirable state