I have started reading “The Man Who Solved The Market - How Jim Simons Launched The Quant Revolution” by Gregory Zuckerman 
“Early on, Simons made a decision to dig through mountains of data, employ advanced mathematics, and develop cutting-edge computer models, while others were still relying on intuition, instinct, and old-fashioned research for their own predictions.”
“Do Simons’s achievements prove human judgement and intuition are inherently flawed, and that only models and automated systems can handle the deluge of data that seems to overwhelm us?”
Robert Mercer: “Once, Mercer told colleagues he believed he would live forever. The staffers thought he was serious, though historic precedent didn’t seem on his side.”
“”The lesson was: Do what you like in life, not what you feel you ‘should’ do,” Simons says. “It’s something I never forgot.””
“The way that powerful theorems and formulas could unlock truths and unify distinct areas in math and geometry captured Simons. ... “I realized I might not be spectacular or the best, but I could do something good. I just had that confidence,” he says.”
“Simons saw how wealth can grant independence and influence. “Jim understood at an early age that money is power,” Barbara says. “He didn’t want people to have power over him.””
“Staff members, most of whom had doctorates, were hired for their brainpower, creativity, and ambition, rather than for any specific expertise or background. ... “Bad ideas is good, good ideas is terrific, no ideas is terrible.””
“Simons and his colleagues weren’t alone in suggesting that stock prices are set by a complex process with many inputs, including some that are hard or even impossible to pin down and not necessarily related to traditional, fundamental factors.”
“Scientists and mathematicians are trained to dig below the surface of the chaotic, natural world to search for unexpected simplicity, structure, and even beauty. The emerging patterns and regularities are what constitute the laws of science.”
Even the best have experienced a few setbacks: “Wait, is Simons contemplating suicide?”
“Soon, he and Baum had lost confidence in their system. They could see the Piggy Basket’s trades and were aware when it made and lost money, but Simon and Baum weren’t sure why the model was making its trading decisions. Maybe a computerized model wasn’t the way to go, after all”
“An optimist by nature, Baum liked to purchase investments and sit on them until they rose, no matter how long it took. ... “Dad’s theory was buy low and hold on forever,” Stefi says.”
“Baum later described the episode as “the dumbest thing I ever did in this business.” ... “He had the buy-low part, but he didn’t always have the sell-high part,” Simons later said. ... Ultimately, Baum proved prescient.”
“Simons has to find a different method to speculate on financial markets; Lenny Baum’s approach, reliant on intellect and instinct, just didn’t seem to work.”
“Some people take years to identify a profession for which they are naturally suited; others never make the discovery. ... Some other traders were gathering and cleaning data, but no one collected as much as Straus, who was becoming something of a data guru.”
“In a sense, he was proposing an early machine-learning system. ... “It’s a black box!” he said with frustration. Carmona agreed with Simons’s assessment, but he persisted. “Just follow the data, Jim,” he said. “It’s not me, it’s the data.””
“I strongly believe, for all babies and a significant number of grownups, curiosity is a bigger motivator than money.” —Elwyn Berlekamp
Berlekamp and Shannon: “Berlekamp held a dismissive view of finance. “My impression was that it was a game in which rich people play around with each other, and it doesn’t do the world much good,” Berlekamp says. “It still is my impression.””
“Scientists are human, often all too human. When desire and data are in collision, evidence sometimes loses out to emotion.”
“Legitimate concerns had led to something of an unwritten rule on Wall Street: don’t trade too much. ... Berlekamp hadn’t worked on Wall Street and was inherently skeptical of long-held dogmas developed by those he suspected weren’t especially sophisticated in their analysis.”
“As the researchers worked to identify historic market behavior, they wielded a big advantage: They had more accurate pricing information than their rivals.”
“Investors moved on, searching for juicier opportunities, like fishermen ignoring the guppies in their nets, hoping for bigger catch. By trading frequently, the Medallion team figured it would be worthwhile to hold on to all the guppies they were collecting.”
“Despite the ridicule, many investors continue to chart financial markets, tracing head and shoulders formations and other common configurations and patterns. Some top, modern traders, including Stanley Druckenmiller, consult charts to confirm existing investment thesis.”
“Medallion would employ a single trading model rather than maintaining various models for different investments and market conditions ... a single model could draw on Straus’s vast trove of pricing data ... Narrow, individual models, by contrast, can suffer from too little data.”
“Betting algorithms” “Our system is a living thing; it’s always modifying,” he said. “We really should be able to grow it.”
“Patterson saw the world “becoming extremely mathematical” and knew computer firepower was expanding exponentially. He sensed Simons had an opportunity to revolutionize investing by applying high-level math and statistics.” And slippage or “The Devil”.
“Humans are most predictable in times of high stress - they act instinctively and panic. Our entire premise was that human actors will react the way humans did in the past ... we learned to take advantage.”
“Simons had long been driven by two ever-present motivations: proving he could solve big problems, and making lots and lots of money.”
