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jerryking : winton_capital   3

Winton Capital’s David Harding on making millions through maths
NOVEMBER 25, 2016 | Financial Times | by Clive Cookson.

Harding’s career is founded on the relentless pursuit of mathematical and scientific methods to predict movements in markets. This is a never-ending process because predictive tools lose their power as markets change; new ones are always needed. “We have 450 people in the company, of whom 250 are involved in research, data collection or technology,” he says. That is equivalent to a medium-sized university physics department....Harding's approach to making money is to exploit failures in the efficient market theory...the problem with the EMT is that “It treats economics like a physical science when, in fact, it is a human or social science. Humans are prone to unpredictable behaviour, to overreaction or slumbering inaction, to mania and panic.”...The Winton investment system is based instead on “the belief that scientific methods provide a good means of extracting meaning from noisy market data. We don’t make assumptions about how markets should work, rather we use advanced statistical techniques to seek patterns in huge data sets and base all our investment strategies on the analysis of empirical evidence...Harding emphasises the breadth and volume of investments involved, covering bonds, currencies, commodities, market indices and individual equities. The aim is to exploit a large number of weak predictive signals, he says: “We don’t expect to find any strong relationships between data and the price of the market. That may sound counter-intuitive but if there are strong relationships, someone else is going to be exploiting those. Weak relationships are where we have a competitive advantage.” Weather strategies are one feature of Winton research, including analysis of cloud cover and soil moisture levels to predict the prices of agricultural commodities. Other important indicators, for which maths can uncover value not fully reflected in market prices, include seasonal factors and inventory levels across supply chains....When I ask Harding about the use of machine learning and artificial intelligence to guide investment decisions, he bristles slightly. “There is a sudden upsurge of excitement about AI,” he says, “but we have used techniques that would be described as machine learning for at least 30 years.”

Essentially, he says, quantitative investing, self-driving cars and speech recognition are all applications of “information engineering”....he heads off to a lecture by German psychologist Gerd Gigerenzer, who runs the Harding Centre for Risk Literacy in Berlin
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november 2016 by jerryking

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