Machine learning could help quants

Contrary to much commentary, machine learning is not a brand new subject. Indeed, as long ago as 1957, Frank Rosenblatt invented the Perceptron – an algorithm that could be trained to classify images through supervised learning. The New York Times breathlessly described the hope that the machine might, one day, “be able to walk, talk, see, write, reproduce itself and be conscious of its existence”. The machine learning conversation has recently hit new volumes, powered by three separate revolutions: first, computing power; second, data generation, storage and retrieval (an estimated 90 per cent of the data in existence today were created in the last two years, while in 1981 a GB of storage cost $300,000 whereas today the price is just $0.10); and third, the combination and maturing of methodology…

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