The Financial Times
reports:
http://www.ft.com/cms/s/0/856bd92c-8fb0-11e5-8be4-3506bf20cc2b.html
“So-called quantitative financiers, or “quants”, have for years come up with innovative, complex ways to analyse and trade on company earnings or economic releases. But thanks to huge gains in computing power and algorithmic research, they are now pushing into “unstructured data” like internet searches, social media, satellite images, earnings calls or weather patterns to find market signals and overlooked trading opportunities. To do so they need to deploy innovative, increasingly powerful quasi-artificial intelligence algorithms, ratcheting up demand for computer scientists to do coding that is beyond mathematicians and physicists. “Traders used to be first class citizens of the financial world, but that’s not true any more. Technologists are the priority now,” says Jared Butler, a headhunter at Selby Jennings. “It’s easier to hire a computer scientist and teach them the financial world than the other way around.””
“So-called quantitative financiers, or “quants”, have for years come up with innovative, complex ways to analyse and trade on company earnings or economic releases. But thanks to huge gains in computing power and algorithmic research, they are now pushing into “unstructured data” like internet searches, social media, satellite images, earnings calls or weather patterns to find market signals and overlooked trading opportunities. To do so they need to deploy innovative, increasingly powerful quasi-artificial intelligence algorithms, ratcheting up demand for computer scientists to do coding that is beyond mathematicians and physicists. “Traders used to be first class citizens of the financial world, but that’s not true any more. Technologists are the priority now,” says Jared Butler, a headhunter at Selby Jennings. “It’s easier to hire a computer scientist and teach them the financial world than the other way around.””