Hedge funds embrace machine learning—up to a point


ARTIFICIAL intelligence (AI) has already changed some activities, including parts of finance like fraud prevention, but not yet fund management and stock-picking. That seems odd: machine learning, a subset of AI that excels at finding patterns and making predictions using reams of data, looks like an ideal tool for the business. Yet well-established “quant” hedge funds in London or New York are often sniffy about its potential. In San Francisco, however, where machine learning is so much part of the furniture the term features unexplained on roadside billboards, a cluster of upstart hedge funds has sprung up in order to exploit these techniques.

These new hedgies are modest enough to concede some of their competitors’ points. Babak Hodjat, co-founder of Sentient Technologies, an AI startup with a hedge-fund arm, says that, left to their own devices, machine-learning techniques are prone to “overfit”, ie, to finding peculiar patterns in the specific data they are trained on that do…

The Economist: Finance and economics

Post Author: martin

Martin is an enthusiastic programmer, a webdeveloper and a young entrepreneur. He is intereted into computers for a long time. In the age of 10 he has programmed his first website and since then he has been working on web technologies until now. He is the Founder and Editor-in-Chief of BriefNews.eu and PCHealthBoost.info Online Magazines. His colleagues appreciate him as a passionate workhorse, a fan of new technologies, an eternal optimist and a dreamer, but especially the soul of the team for whom he can do anything in the world.

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