Trading is risky. Every professional broker or casual trader will admit it. Significant gains or total ruin are at the whims of the market, and its trends cannot be resisted even by large financial institutions. The thrill of the risk is part of human nature, and as such, trading has often been labeled as being another form of gambling. Emotion – and panic most of all – is undoubtedly a large part of the “game.”
However, the trade finance game is finally changing, but it’s not due to the regulatory pressures of the government or the extreme levels of competition in the market – it’s because of technology. Pervasive and relentless, the continuous rise of smartphones, AI, enhanced processing abilities and increasingly intelligent algorithms cannot leave trading untouched.
The Future Is Now
Developing an algorithm capable of foreseeing the movements of the market has been the dream of traders and brokers for decades. With it, the risk would be reduced, if not entirely eliminated from the equation, and attributed a coefficient. Angry calls and hopeful investments would be turned into strings of 1 and 0.
Already, artificial intelligence and natural language processing are being used to establish patterns on the market. Technology has evolved so much that algorithms can understand and process complex financial structures and make decisions based on the risk profile of a portfolio.
In one way, the automatisation of trading has been in the making for a long time. Ever since the digitalisation and expansion of the financial markets, trading has been a source of enormous quantities of data. Now, virtually anyone can act on the market, becoming another data-producing active element. The AIs operate on the data, establishing trends in seconds and making snap recommendations or alerting suspicious behaviour.
Algorithmic (Algo) Trading
While AIs make great financial advisors, it is the rise of automatic trading that is changing the financial markets to a greater extent. It was after 1987’s Black Monday stock market crash that algorithmic trading, or “algo trading,” became a focus for investors and traders. If before, technology was used to monitor the prices simply, since then automation was devised to be a failsafe against such crashes.
Primarily, automatic or algorithmic trading consists of computers automatically buying or selling shares or currency when certain market conditions are met. After pairing his forex demo account with this type of program, the user is left to choose a handful of rules that the algorithm should follow, such as the type of order and the time at which the trade will be triggered.
As a result, trading is becoming available to even more people than until now. Not having to oversee the evolution of the market across the day personally, the user can simply reap what the algorithm has sown. Full-time traders, however, constantly tweak the parameters of their algorithms in order to reach greater efficiency.
Predicting the way in which the market would twist and turn was the attribute of seasoned traders. Even they made merely informed guesses and were miles away from the certainty of any form. As a result, money would be lost, brokers would be blamed, the market cursed, and trading avoided entirely.
Instinct Or Automation
The benefits of automation, however, are hard to contest. With easier access to the markets, the algorithms will establish consistency, improve order entry speed and diversify the portfolio at a degree that would not be humanly possible.
In terms of security, trading is by all indications going to be safer, faster and with a higher degree of stability. While it was digitalisation that made the financial markets vulnerable to hackers, automation could make them immune to any such interference. At the same time, the extremely fast processing powers of algorithms can identify attempts of tampering with the markets as they happen.
The proliferation of algorithm-based trading adds a certain level of security against hackers, fraud or even crashes. Predicted, identified and dealt with by the emotionless brain of a computer, the panic-induced ups, and downs of the prices are less of danger.
Moreover, with automation, the amount of available information will only dramatically increase. Consequently, AIs will also likely be revamped into more complex digital stock avatars that will “translate” the data to the user in order to help him or her decide on a trading strategy.
Even more globalised and “democratised,” the markets will encourage the appearance of more and more start-ups, something we see today as well. Banks – especially investment banks – will see a terrible downfall, as their mastery of the markets will be no match for the processing powers of algorithms. That will be the case unless, of course, the same banks will be able to move with the times and be the first to embrace the new technologies.
As a result of the rise of automatic trading, the big gains and risks that defined taking part in the financial markets are likely to diminish greatly. As the game becomes safer and the players increasingly equal in processing power and decision-making speed, trading will cease to be what it is now.
The next race will be in developing better algorithms that can find patterns and reveal market indicators even faster. If the computers that operate in the market today aim to make their environment safer and more predictable, the digital traders of the future will have to resort back to allowing a certain degree of risk. In this way, a chilling scenario will come to pass – they will have to become like us, but better.
Ethan Featherly has studied economics and trading at The University of Chicago. Late on, he decided to pursue his life-long dream of becoming a financial analyst. Ethan is currently employed at Admiral Market, where he is a content manager in charge of the educational section. He also loves cats, has a vast collection of fantasy novels, and he’s an avid PC gamer.