The global forex market accounts for more than $5 trillion worth of daily transactions. Most of these transactions are made by institutional investors and hedge funds. Traditional banking also plays a part. However, a lot has changed over the last few years. With more retail traders now using online platforms to buy and sell foreign currency, even the ordinary banker has been swayed to join the lot.
One of the driving forces behind the massive surge in forex trading activity has been the growing impact of fintech and advances in artificial intelligence applications. Fintech has created an enabling environment for a connected world of financial markets. On the other hand, artificial intelligence applications like machine learning been used by quant funds to create more efficient trading systems that have routinely outperformed manual trading.
Quant Funds Have Embraced Machine Learning
These systems are popular with quant funds, with some stats already showing that hedge funds employed quantitative trading techniques managed to boost their return on investment since 2010, according to Business Insider.
Some of those returns outperformed the market by as much as 64% and this has since prompted for mainstream hedge funds, as well as, retail forex traders to pursue the same technique. Last year, an article published by Bloomberg said that JPMorgan Chase, one of America’s biggest hedge fund managers had tapped an AI startup to create a system that would help its traders to predict market movements.
This further shows how automated trading programs have become so important over the last few years. In shares trading, most investors simply call them trading systems, whereas in advisory firms they go by the name Robo Advisors.
Automated Trading is Not New to Forex, but it is Evolving
However, in the world of forex trading, these trading systems have existed for quite sometime now. They started off as simple some partial trading algorithmic systems that helped traders to spot potentially profitable trades by analyzing historical trading data and price movements.
Then they moved a notch higher to introduce automated trading in what came to be referred to as trading robots, but now, with ambitious startups being launched left-right-and-center, retail traders are now gaining access to machine learning-based trading systems.
And with the digitization of the global financial markets, everything that affects exchange rates will soon be digitized, which means machine learning systems such the ones used by quant funds to trade the money markets will be able to access this data, thereby making trading seamless.
Blockchain Technology is Helping to Populate Forex Markets with More Data
Some might question the validity of the information stored in online platforms, but this issue will soon be overcome using blockchain technology.
Developments already indicate that banks are beginning to embrace blockchain. Some have already developed blockchain-based systems to help in the execution of bulk transactions. And because banks have been crucial in the global forex markets, this means that their activities in the financial markets including the ones that involve the transfer of enormous amounts of money will come in handy when traders start using machine-learning systems to trade.
With more data available to the trading systems to consume, the machine learning-based algorithms will continue to become more complex and more efficient thereby massively improving trading returns for forex traders.
This will also imply that retail traders that adopt the use of third-party artificial intelligence systems to trade will have to be more cautions when perusing the web for the best providers. Already, the forex market is flooded with fake trading systems that claim to deliver high returns to traders. In most cases, these claims have been proved to be false with some traders losing a lot of money in the process.
The AI/Machine Learning Field is Becoming More Complex and Highly Competitive
Therefore, as AI/machine learning-based systems become more complex in a bid to adapt to the growing portfolios of data sources, it will become even more challenging for small startups to come up with systems that can keep up with competition. As to whether they will be able to keep pace, the jury for that one is still out.
The bottom line is that most retail forex traders do not have the capacity to design their own AI-based trading systems. Therefore, as the forex market continually becomes reliant on algorithmic trading systems and machine learning, it will become a lot more difficult to make money without using such systems. As such, retail forex traders will have to adapt or reinvent their trading strategies to rival the machines. And that won’t be easy.