Intelligent machines will dominate FX trading – but when?

By:
Solomon Teague
Published on:

Artificial intelligence (AI) systems are too expensive to go mainstream for now, but a future in which human currency traders have been marginalized by machines seems closer than ever.

The first successful robot currency traders could be with us by around 2020: that is the prediction of Joséphine de Chazournes, senior research analyst at Celent, the research and consulting firm. 

Her timeframe, which she acknowledges is speculative, takes into account the enormous potential for AI in trading, as well as the equally large obstacles the technology still has to overcome.

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Joséphine de Chazournes,
Celent
 

"A lot of funds and banks are already investing in AI for trading, but latency is a big challenge when it comes to the FX market," she says. "FX is the ultimate challenge for AI and it will probably be the last asset class it learns to trade, after blue-chip equities and US treasuries, which have similar challenges to FX."

There are also many macroeconomic variables influencing the currency markets that make them more complicated to model cognitively. However, De Chazournes believes these obstacles will be overcome. "We will see AI trading FX successfully in about three years," she says.

Yaron Golgher, CEO at I Know First (IKF), which provides market forecasts based on an AI algorithm, thinks some financial institutions might already be further along in their efforts to develop AI FX trading machines.

"Although the field is very secretive, it's safe to assume that advanced AI-based algorithms are likely already being used in trading by some more successful trading houses," he says.

One trader who is open about his efforts to develop AI to trade currencies on his behalf is David Lopez Onate, founder of Forex Artilect. Although his fund is not yet investable, he believes trading forex is already viable for AI. However, as good as it is now, he believes it will get better over time as it overcomes the challenges that Celent's De Chazournes outlines.

"AI will get better as technology advances and Moore's Law makes processing power cheaper, because the computational power required is huge," says Onate. "It can be profitable now but it can be a hundred times better in the future."

Forex Artilect trades the four major currencies, which keeps trading costs down, typically holding positions for a few days. Using backtesting, it generated $100 million from an investment of $10,000 in just two years. 

"The backtested numbers look a little too good to be true, but if we can generate even a few percent of that performance in real trading conditions, that will be awesome," says Onate.

He says he is applying AI to forex partly because it was his market before he got interested in the technology. "But also it’s because there are so few people looking at applying AI to currencies, I saw that as an opportunity to get ahead," he adds.

Filtering the noise

Of course, algorithms have already gained considerable traction among traders in financial markets, with a significant proportion of currency trading already conducted electronically, with markedly reduced human involvement. However, where algorithms excel at analysing large data sets, looking for anomalies or hidden correlations, they lack the critical analysis of a human trader.

Software vendors have the programming skills to build AI, but for it to reach its potential trading the currency markets, they need to convince the best FX traders to help them build the systems. If the two groups can work together, AI promises to take algorithms to the next level, marrying the computational capabilities of a machine with the judgement of an experienced trader.

This remains a delicate exercise. Onate says: "There is a lot of noise in financial markets and the challenge for AI is filtering out the noise, because you can accidentally filter out a signal. Longer-term trading is easier because the signals are much clearer. But we are still experimenting; we are always testing and enhancing the system."

IKF, which generates daily market predictions not only for currencies but also for stocks, commodities, ETFs, interest rates and world indices, for the short-, medium- and long-term time horizons, claims to be further along in this process. Its AI system accounts for a broad range of market signals when forecasting, says Lipa Roitman, chief technology officer at IKF.

"What is particular about our algorithm is that every forecast is accompanied by a number – we call it 'predictability' – that indicates the quality of the learning," he says. "Then we sort the entire universe of forecasts and pick the most probable opportunities."