by Larry Harris · 2 Jan 2003 · 1,164pp · 309,327 words
expose to find these traders. * * * ▶ Order Exposure in Crossing Networks Electronic crossing networks, such as POSIT, allow large traders to avoid exposing their orders. These computerized trading systems take electronically transmitted orders and match them at prices determined elsewhere. The systems are completely confidential. They reveal only the aggregate sizes of the
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ensure that all traders would receive a minimum quality of service regardless of where they are in the world. The issue is particularly important in computerized trading systems that allow their users to submit computer-generated orders. Computerized traders who can act most quickly on new information take advantage of market opportunities
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first. When two computerized trading systems employ the same trading strategies, the first to submit its orders will be the more profitable system. Since the difference in their submission times
by Nicholas Carr · 28 Sep 2014 · 308pp · 84,713 words
can be subtle, but they have real consequences, particularly in fields where analytical errors have far-reaching repercussions. Miscalculations of risk, exacerbated by high-speed computerized trading programs, played a major role in the near meltdown of the world’s financial system in 2008. As Tufts University management professor Amar Bhidé has
by Jack D. Schwager · 7 Feb 2012 · 499pp · 148,160 words
the best traders of our time. In the early 1970s, Seykota was hired by a major brokerage firm. He conceived and developed the first commercial computerized trading system for managing clients’ money in the futures markets. His system proved quite profitable, but interference and second-guessing by management significantly impeded its performance
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, I figured there wouldn’t be very much of a bureaucracy to interfere with my use of the computer. What became of your work on computerized trading systems? Eventually, management got interested in using my research results for managing money. I developed the first large-scale commercial
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computerized trading system. What do you mean by large scale? The program was marketed by several hundred agents of the firm, and the equity under management was
by Scott Patterson · 2 Feb 2010 · 374pp · 114,600 words
added more automation to the system, linking the desk to the New York Stock Exchange’s Super Designated Order Turnaround System, or SuperDOT, which facilitated computerized trades. APT was soon trading so much that at times it accounted for 5 percent of the daily trading volume on the NYSE. The stat arb
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Money Grid. Innovators such as Ed Thorp, Fischer Black, Robert Merton, Barr Rosenberg, and many others had been early architects of the Money Grid, designing computerized trading strategies that could make money in markets around the world, from Baghdad to Bombay, Shanghai to Singapore. Michael Bloomberg, a former stock trader at Salomon
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to crack the market’s code. In 1993, he paid a visit to a little-known group of physicists and scientists running a cutting-edge computerized trading outfit from a small building in Santa Fe, New Mexico. They called themselves Prediction Company, and they were reaching out to Wall Street firms, including
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cool, be confident. When his turn came, he flatly admitted that PDT hadn’t succeeded yet. But it was on the edge of great things. Computerized trading was the future. He just needed more time. As he stopped speaking, he looked at Mack, who gave him a confident nod back. Mack had
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trading reached unfathomable speeds, danger lurked. Many of these computer-driven funds were gravitating to a new breed of stock exchange called “dark pools”—secretive, computerized trading networks that match buy and sell orders for blocks of stocks in the frictionless ether of cyberspace. Normally, stocks are traded on public exchanges such
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devising new methods to operate in the shadows. Just look: exotic leveraged vehicles marketed to the masses worldwide, hedge funds gaming their returns, lightning-fast computerized trading robots, predatory ninja algorithms hunting liquidity in dark pools … Here come the quants. Notes 1 ALL IN Simons had pocketed $1.5 billion: Alpha, May
by Scott Patterson · 11 Jun 2012 · 356pp · 105,533 words
Plumber, an architect not of trading strategies or moneymaking schemes but of the pipes connecting the various pieces of the market and forming a massive computerized trading grid. Plumbers such as Mathisson had become incredibly powerful in recent years. Knowledge of the blueprints behind the market’s plumbing had become extremely valuable
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world. The size of two football fields at one hundred thousand square feet, it sported fourteen hundred seats and five thousand monitors. It was a computerized trading machine of vast proportions, juggling more than a trillion in assets a day. Bodek’s mandate was to build an options-trading desk that could
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themselves in this era of electronic trading is to use so-called limit orders” that safeguard against “short-term disruptions that might be caused by computerized trading.” But a representative for a U.S. exchange had just told Bodek not to use limit orders, which were getting picked off by high-speed
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Levine came across an approach to the markets from an abstract, theoretical basis. The only problem: He disagreed with just about everything Schwartz wrote. On computerized trading, Schwartz wrote that while its advantage is “the rapidity with which orders can be electronically transmitted and executed,” the drawback is that “speed may also
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, the established market makers were already dropping out in droves as their profits evaporated. For Nasdaq, it was kill or be killed. Its solution: a computerized trading network that came to be known as the ECN Killer. They called it SuperMontage (the market’s book of buy and sell orders was often
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the Senate. Over the next year, the gangly, cerebral senator would become the most unlikely critic of high-frequency trading imaginable. Kaufman’s interest in computerized trading evolved out of his investigation into the SEC’s move in July 2007 to abolish the “uptick” rule. The rule, which had been in place
by Bruce Schneier · 7 Feb 2023 · 306pp · 82,909 words
the market does—another unfair advantage. Taking advantage of typos is yet another market hack that operates at computer speeds. Typos are not uncommon in computerized trading systems. The large failures make the news, like the time that a Japanese company, Mizuho Securities Co., lost $225 million on a stock trade when
by Alexander Elder · 28 Sep 2014 · 464pp · 117,495 words
out his credit card to buy access to “trading secrets.” He may send money to a charlatan for a $3,000 “can't miss,” backtested, computerized trading system. When that system self-destructs, he'll pull out his almost-maxed-out credit card again for a “scientific manual” that explains how he
by Peter Kovac · 10 Dec 2014 · 200pp · 54,897 words
absolutely no hard evidence to help us figure it out – instead we’re stuck with a handful of theories about computerized trading, proposed by a group of outsiders who have never done computerized trading. For a book about the dangers of speed in finance, the book itself seems rushed into print. It’s therefore
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and when we placed our orders. But they expected that they were different. They expected that their personal Bloomberg terminals and their bank’s custom computerized trading platform not only delivered stock prices to them faster than individual investors, but that it somehow guaranteed that the prices on their screens would remain
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investment dollars. If you can shrink the spread, your investments earn a lot more. So, how much has the spread shrunk? Lewis tells us that computerized trading has reduced spreads from a “sixteenth of a percentage point” to “one-hundredth of 1 percent.” There are few better techniques to obscure an argument
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’s largest mutual fund manager writes that when you retire, your investment would be 25% smaller without the benefit of the decreased costs wrought by computerized trading. This is incredibly important. Lewis does admit that, “spreads in the market had narrowed – that much was true.” He dismisses the role of high-frequency
by Gregory Zuckerman · 5 Nov 2019 · 407pp · 104,622 words
and father of modern portfolio theory, was searching for anomalies in securities prices, as was mathematician Edward Thorp. Thorp would attempt an early form of computerized trading, gaining a head start on Simons. (Stay tuned for more, dear reader.) Simons was part of this vanguard. He and his colleagues were arguing that
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were aware when it made and lost money, but Simons and Baum weren’t sure why the model was making its trading decisions. Maybe a computerized trading model wasn’t the way to go, after all, they decided. In 1980, Hullender quit to go back to school. Leaving college prematurely weighed on
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him, and he was ashamed he couldn’t help Simons make more progress on his computerized trading system. Hullender couldn’t understand the math Simons and Baum were using, and he was lonely and miserable. Weeks earlier, he had revealed to colleagues
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, as gold shot even higher, he phoned again: “It went up more, Elwyn!” Berlekamp was baffled. It was Simons who had pushed to develop a computerized trading system free of human involvement, and it was Simons who wanted to rely on the scientific method, testing overlooked anomalies rather than using crude charts
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wanted to expand the team, purchase additional satellite dishes for the roof, and spend on other infrastructure that would allow them to upgrade Medallion’s computerized trading system. He asked Berlekamp to chip in to pay for the new expenses. The pressures wore on Berlekamp. He had remained a part-time professor
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of stocks momentarily lost nearly all their value. Investors pointed the finger at computer-programmed trading firms and said the collapse highlighted the destabilizing role computerized trading can play, but the market quickly rebounded. Prosecutors later charged a trader operating out of his West London home for manipulating a stock-market-index
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may become less predictable and maybe even less stable, since human nature is roughly constant while the nature of this kind of computerized trading can change rapidly. The dangers of computerized trading are generally overstated, however. There are so many varieties of quant investing that it is impossible to generalize about the subject. Some
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Zuckerman, Rachel Levy, Nick Timiraos, and Gunjan Banerji, “Behind the Market Swoon: The Herdlike Behavior of Computerized Trading,” Wall Street Journal, December 25, 2018, https://www.wsj.com/articles/behind-the-market-swoon-the-herdlike-behavior-of-computerized-trading-11545785641. Chapter One 1. D. T. Max, “Jim Simons, the Numbers King,” New Yorker, December
by Kendall Kim · 31 May 2007 · 224pp · 13,238 words
the introduction of programs, direct market 1 2 Electronic and Algorithmic Trading Technology access, and algorithmic trading. Although automated trade flow can carry connotations of computerized trading taking over without human supervision, the actual decisions to buy and sell are made by people, not computers. Humans make the final trading decisions and
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