Automate This – How Algorithms Came to Rule Our World

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At a 2010 black-tie banquet in Chicago, a spry Jarecki spotted Scholes across the room nursing a cocktail and lightly conversing. Jarecki made his way over to the Nobel laureate. "You know, you still have our Nobel Prize," Jarecki said to Scholes. The remark elicited a dry grimace. "He was not amused," Jarecki says. (c)
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The financial industry, as is the case with most high-paying fields, tends to be dominated by men who are wont to hire more men. So when Peterffy hired the tallest, prettiest, most buxom women he could find, the plan was more than a bit novel. The tactic worked miracles for his order flow. Suddenly, the specialists always took his trades. They put their arms around his traders, chitchatted, and recognized the blondes' orders as fast as they were issued. "The specialists were thinking, 'These dumb blondes, what do they know, right'" Peterffy says.
It's true that the women Peterffy hired didn't know much about trading, let alone algorithms. But none of his traders at that time were any good out on their own. And none of them were using the sheets for guidance anymore. Peterffy had devised a new system that empowered anybody to make smart trades. (c)
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The key to it all was a dependable flow of pure data that few others had. And data, as so many hot companies of today have demonstrated, can be the difference between domination of an industry and failure. Peterffy's operation pioneered the automated compilation and employment of vast data stores on Wall Street, where the mining of such things got its start. (c)
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He explained his success: "You gotta be able to calculate doo-boop-be-deeliyaboop-deal! I can do that." He had learned math, he said, studying astronomy in the Netherlands and in the air force ...

Van Peebles's story accentuated the success of the most improbable trading squad roaming the pits of New York, perhaps to this day: three blonde women and one highly acclaimed black writer, director, and actor, all of them well-disguised proxies of an algorithm that dwelled inside a machine. (c)
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Technically, a market maker is required to keep both bids and offers up at all times, no matter where the market goes. But Peterffy had been bending the rules, as a lot of market makers did, cherry-picking the trades he wanted according to the instructions of his algorithm. At no point was he maintaining constant bids and offers. (c)
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O'Connor was so secretive about its methods that when it bought two hundred Symbolics computers in the mid-1980s, executives shredded the packaging so Dumpster-diving competitors couldn't determine what technology the firm used. (c)
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