G4S, Lloyds, Burberry: How artificial intelligence spots insider trading before a stock hits freefall

Machine learning algorithms can warn investors when a particular stock is going to fall by predicting likely instances of insider trading (when information that's not in the public domain is capitalised upon by people in the know). This can be done by analysing previous occasions when company insiders did apparently well-timed trades in their own stocks, and recognising these patterns. This might seem deceptively simple, but it isn't, explains Tom Doris, CEO of OTAS Technologies, a London-based market analytics and machine learning trading system. While company executives are required to file details of transactions in their company's stock, most insider trades are few and far between: a needle in a haystack. Doris told IBTimes UK: "We look at all of the insiders, the directors of companies, and we see all of their historical transactions in their own stock. If you are the chief financial officer of Vodafone, any time you buy or sell Vodafone stock, you're obliged under regulation to file details of those transactions. So that would include the amount that you bought or sold, when you did it and what price you got and the reason, if any, for the transaction. There is an enormous database of all of these transactions for all of the world's listed stocks and we go and we basically back-test all of the insiders and we find the ones that are apparently good at timing their own stocks."