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2017-12-12 10:27:39
In investing, more artificial intelligence need not mean less of the human kind
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 not hold up in the wider world. This
is especially true of financial data, he says, because of their comparative
paucity. Share-price time series going back decades still contain far less
information than, say, the image data used to train Facebook s
facial-recognition algorithms.