Using AI/ machine-learning technology is not just for the institutions. Some of the best investment processes I have seen recently have come from the retail investor tinkering on their home computers and people from outside the investment industry.

While continually developing, the AI/ machine-learning technology is not new. It has been increasingly deployed in industries such as Telecommunications and Retail for many years. Investors are now adapting these machine-learning techniques and approaches and applying them to the financial markets.

The use of machine-learning algorithms for investing is increasing globally. Examples of overseas institutions using the technology include Rebellion Research, Renaissance Technologies, Winton Asset Management and Two Sigma.

The arrival of cloud computing, open-source modelling software and developments in database technology has allowed anyone with an interest in financial markets, a mathematical understanding and some coding experience to develop their own proprietary machine-learning technology and IP.

Combine a trade signal generator that they have built with a trading interface (most trading software packages have software APIs), run it using the computing power of a cloud computing solution and investors can run their process from anywhere that there is an internet connection.

Admittedly this over simplifies it somewhat, however with some research and work it can be set up. Indeed, I am often meeting self-taught Australian investors in the process of developing and testing their own trading systems.

For investors wanting to give it a go there are some excellent online courses (I would recommend Andrew Ang’s course on Coursera), some good data providers such as Quandl and many online brokers now provide the interfaces required to automatically backtest and trade.

Like anything new and unfamiliar it takes time for the investment community to adapt and become comfortable with new technologies. Once investors and traders have seen the benefits that adding predictive analytics can bring to their investment approach the technology will become more commonplace in an investor’s toolbox.

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