Provocative reporting from the Financial Times on UCL's Financial Computing Centre:
As of this winter, the centre had about 60 PhD students, of whom 80 per cent were men. Virtually all hailed from such forbiddingly numerate subjects as electrical engineering, computational statistics, pure mathematics and artificial intelligence. These realms of knowledge contain concepts such as data mining, non-linear dynamics and chaos theory that make many of us nervous just to see written down. Philip Treleaven, the centre’s director, is delighted by this. “Bright buggers,” he calls his students. “They want to do great things.”
Deciphering such patterns is what excites collaborators with the Financial Computing Centre who are more interested in stabilising the markets than beating them. Zheludev’s supervisor is David Tuckett, a psychoanalyst at UCL who studies the interplay of emotion and the unconscious in trading decisions. He told me that the database could, if used properly, allow us to see our exaggerated hopes and paranoias for what they are, before they grow to overwhelm us. “If you think about it like the sea,” said Tuckett, of the torrents of digital information that we produce each day, “can we identify narratives when they are not yet at the surface? Can we learn about how they come and go?”
As Tuckett spoke, I began to believe in the idea of quants enabling us to digest the world in more rational ways, to become, in a sense, better versions of ourselves. “We are not interested in a world that is completely without excitement or volatility,” said Tuckett, “But we are interested in getting a handle on things before they get out of hand.” The paradox is that in order to become safer, in order to become better informed, we will have to continue to place ever more faith in brains and machines that we only begin to understand. It is always easy to start. The problem is knowing when to stop.
H/T Tyler Cowen