Financial Technologies Women Should Know More About (Part 1)
Contributed by Sophie Fletcher
Technology is changing the financial arena. No longer limited by execution venue, exchange or geographical brokers and dealers, trading moves to where liquidity is greatest and so, the market evolves. As players in this dynamic market, women should be familiar with the technology behind the process of making educated trades. The Glass Hammer has compiled a brief run-down of the top technologies our readers should be familiar with. The first in this five part series is Algorithmic Trading technology.
Algorithmic Trading reminds me of the 2004 movie with Will Smith, I, Robot. The plot revolved around a robot that was programmed with rules. These rules were made by humans and integrated into the robot’s “brain” system. Ultimately, the artificial intelligence of the robot turned on the humans but throughout the film, the robot was just following its internal rules. I am not saying that Algorithmic Trading is as dangerous as a movie plot but it does have certain capabilities and a type of artificial intelligence that could make you wonder…
Computer algorithms are used to develop mathematical models that interpret historical and real time data and identify patterns. Use of algorithm-generating software to execute financial transactions is also known as blackbox or electronic trading. The computer generated programs will buy and sell orders at a remarkably fast speed. The models have reduced latency, increased the number of trades and market data messages and sped up the entire trading operation.
Some algorithms can even read news feeds. Reuters and Dow Jones have released news products that are electronically tagged for algorithms to pick up and interpret. According to an article in the Economist, regulators are utilizing these models to pick up suspicious trading activity, such as insider trading.
Regulators also suspect that some price movements that have occurred before takeover announcements stem from algorithms picking up early warning price signals. In essence, algorithms are able to interpret the data feeds faster than journalists and market analysts. The article asks if the public will be getting their news from algorithms and not journalists anymore.
The concept is not as crazy as it sounds, since algorithms have replaced half the floor traders, once a symbol of the financial markets. According to a white paper by IBM, entitled The Trader is Dead! Long Live The Trader!, for every 40 day traders in the business today, only 4 will be left standing in 2015. The remaining traders will work alongside “quants” designing the algorithms (this illustrates why quantitative analytics is a great sector to look into for career opportunities).
While algorithmic trading has its advantages, it is not the most convenient instrument for the volatile markets we are experiencing today. Algorithms are tools that identify patterns and then predict market happenings. However what happens if the market performs in a different and unexpected way than it has in the past?
“When the market moves don’t resemble past movements, all models struggle,” Lee Ferridge, a senior prop trader at Rabobank, said to Reuters.
Algorithms were particularly challenging for old-school portfolio managers to adapt to. The market experienced sharp moves, causing algorithms to sell orders on the same securities. The algorithmic models then encouraged the downward spiral. The same article partially attributes Morgan Stanley’s third quarter losses in 2007 to the algorithms employed within their portfolios.
Matt Simon from the Tabb Group, a financial research firm, told Financial Services Technology that algorithms are more reactive than predictive.
“Being able to take more standard data like news articles and make repetitive decisions that would be a proactive approach and that would imply the intelligence of an algorithm,” said Simon.
He also explained that, as technology increases in application, it may soon over take the knowledge of the person implementing it. Algorithms develop quickly and comprehending what an individual trader is doing becomes difficult. It is in this regard that algorithms have an artificial intelligence.
As we implement these strategies into our every day operations, it is important we comprehend the full scale of capabilities associated with computer-generated algorithms. As I said, it’s not that I predict a scenario fit for a movie screen. However, with the ability to knock half the floor traders out of their seats and questions looming about whether algorithmic trading could replace market analysts too, this is a technology we should all be familiar with.
