How Algorithms Have Changed the Face of Wall Street

Visual Capitalist – In these modern times, it feels as if everything (and sometimes, everyone) is being replaced by electronics and computers. The financial industry is no exception. Algorithms have changed the way investors are trading on the stock market and it has made the process incredibly efficient. However, in addition to the benefits of technology in trading, there have been many problems that have come to light.

Through the increased capabilities of advanced computers and algorithms, high frequency trading (HFT) is made possible. High frequency trading is the rapid trade of stock and securities through use of advanced computer tools and algorithms.

While proponents of HFT would argue that they provide liquidity to the market and decrease overall costs, it has also arguably put mom and pop investors at a disadvantage when competing with investment banks and hedge funds. Quite simply, individual investors do not have the technological resources or the proximity to keep up with the speed their larger counterparts trade at.

Financial journalist, Michael Lewis, recently released an expose book, Flash Boyswhich focuses on HFT in the American equity market. Mr. Lewis’ book suggests that “the market is rigged” and that stock fraud is rampant through the illegal practice of insider trading.

In the wake of the media storm surrounding the release of the book, the FBI, US Department of Justice, and the New York Attorney General’s office have all launched investigations into HFT practices. The New York Stock Exchange was even fined $4.5 million for charges related to Lewis’ book.

In one famous case of Virtu Financial, the HFT firm lost money on only one day of 1,238 days of trading. With instances like this, retail investors have to ask themselves who is really making the big bucks in the market.

How Algorithms Have Changed the Face of Wall Street

Original article published by Jeff Desjardins on Visual Capitalist.

Original infographic from: QuantConnect.com

photo credit: Patcard via photopin cc