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AI offers deep learning for investors Posted on : Jul 20 - 2017

In the late 1940s, Alan Turing first explored the idea that a computer could play chess, to offer up a good example of what these machines could be capable of.

Decades later, a computer for the first time beat a reigning world champion in a classic chess match when Garry Kasparov lost to IBM’s Deep Blue in 1997. Deep Blue could evaluate 200 million moves per second. It was another good example of what a machine with artificial intelligence (AI) could be capable of. 

Today, this potential is not lost on investors who are increasingly interested in how AI technology can give their trading strategies an edge in an era when high returns relative to the market – or alpha - have been difficult to come by.

While relying on computers for trading strategies is nothing new, with quantitative, or quant, funds mainstream more than a decade ago and automated high-frequency trading triggering a flash crash in 2010, we are entering a new era as AI has once again crossed a threshold in terms of power and accuracy, into what is called "deep learning". 

This category of AI is currently very popular among Wall Street banks such as Goldman Sachs and JP Morgan and some hedge funds including Two Sigma and WorldQuant. Deep learning is the ability of artificial neural networks, inspired by the biological brain, to, well, learn. It is what underpins more mainstream applications such as speech recognition and self-driving cars.

The aim of this learning is to better forecast outcomes and help to remove a lot of risk from any activity – in the case of autonomous cars, the goal is taking the risk of an accident while driving down to zero.

Researchers have utilised neural networks to help with the early detection of skin and brain cancer as well as to interpret signs of foetal distress from ultrasound images. Weather patterns, energy grid management, cubesat missions and the effects of earthquakes on structures are all areas where the application of neural network technology has improved forecasting.

Banks and hedge funds expect this technology could soon be a game changer in financial markets where assets managed by systematic funds – those that analyse large amounts of historical data to formulate computer-based trading strategies  –  already hit a record US$500 billion last year after doubling over the past decade, according to Barclays. A survey from Deutsche Bank, released in March, showed that 79 per cent of investors are allocating funds to systematic strategies, up from 70 per cent a year earlier.

However, deep learning technology is not yet a mainstream investment tool, something which is being addressed by AI-led fintech start-ups such as Alpaca, Inovance and Watstock, the Singapore company founded by Carl Freer, who has been working within the AI sector for the past decade. View More