computerized trading

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pages: 407 words: 104,622

The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution by Gregory Zuckerman

affirmative action, Affordable Care Act / Obamacare, Albert Einstein, Andrew Wiles, automated trading system, backtesting, Bayesian statistics, beat the dealer, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, blockchain, Brownian motion, butter production in bangladesh, buy and hold, buy low sell high, Claude Shannon: information theory, computer age, computerized trading, Credit Default Swap, Daniel Kahneman / Amos Tversky, diversified portfolio, Donald Trump, Edward Thorp, Elon Musk, Emanuel Derman, endowment effect, Flash crash, George Gilder, Gordon Gekko, illegal immigration, index card, index fund, Isaac Newton, John Meriwether, John Nash: game theory, John von Neumann, Loma Prieta earthquake, Long Term Capital Management, loss aversion, Louis Bachelier, mandelbrot fractal, margin call, Mark Zuckerberg, More Guns, Less Crime, Myron Scholes, Naomi Klein, natural language processing, obamacare, p-value, pattern recognition, Peter Thiel, Ponzi scheme, prediction markets, quantitative hedge fund, quantitative trading / quantitative finance, random walk, Renaissance Technologies, Richard Thaler, Robert Mercer, Ronald Reagan, self-driving car, Sharpe ratio, Silicon Valley, sovereign wealth fund, speech recognition, statistical arbitrage, statistical model, Steve Jobs, stochastic process, the scientific method, Thomas Bayes, transaction costs, Turing machine

They closed out his potato positions, costing Simons and his investors millions of dollars. 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 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 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 that he was gay. They tried to make him comfortable, but the young man felt increasingly out of place. “I just felt I had a better chance meeting someone compatible in California,” says Hullender, who eventually earned his degree and became a machine-learning specialist for Amazon and Microsoft.

New types of errors could be introduced, some of which have yet to be experienced, making them harder to anticipate. Until now, markets have been driven by human behavior, reflecting the dominant roles played by traders and investors. If machine learning and other computer models become the most influential factors in markets, they 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 quants employ momentum strategies, so they intensify the selling by other investors in a downtown. But other approaches—including smart beta, factor investing, and style investing—are the largest and fastest-growing investment categories in the quant world.

(Source: Medallion annual reports; investors) APPENDIX 2 Returns Comparison Investor Key Fund/Vehicle Period Annualized Returns* Jim Simons Medallion Fund 1988–2018 39.1% George Soros Quantum Fund 1969–2000 32%* Steven Cohen SAC 1992–2003 30% Peter Lynch Magellan Fund 1977–1990 29% Warren Buffett Berkshire Hathaway 1965–2018 20.5%* Ray Dalio Pure Alpha 1991–2018 12% (Source: For Simons, Dalio, Cohen, Soros: reporting; for Buffett: Berkshire Hathaway annual report; for Lynch: Fidelity Investments.) NOTES Introduction 1. “Seed Interview: James Simons,” Seed, September 19, 2006. 2. Gregory 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 11, 2017, https://www.newyorker.com/magazine/2017/12/18/jim-simons-the-numbers-king. 2. James Simons, “Dr. James Simons, S. Donald Sussman Fellowship Award Fireside Chat Series. Chat 2,” interview by Andrew Lo, March 6, 2019, https://www.youtube.com/watch?


pages: 200 words: 54,897

Flash Boys: Not So Fast: An Insider's Perspective on High-Frequency Trading by Peter Kovac

bank run, barriers to entry, bash_history, Bernie Madoff, computerized markets, computerized trading, Flash crash, housing crisis, index fund, locking in a profit, London Whale, market microstructure, merger arbitrage, prediction markets, price discovery process, Sergey Aleynikov, Spread Networks laid a new fibre optics cable between New York and Chicago, transaction costs, zero day

There are no mountains of trial evidence meticulously documenting this alleged fleecing of the public. Maybe the end is nigh for those villainized by Lewis, and we’ll see them heading to prison in a few months. Or maybe not. We just don’t know at this time, and, unfortunately, Lewis supplies 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 not surprising, although it is rather unusual, that Lewis’ own “experts” have since gone out of their way to make it clear that they didn’t fact-check the book, and that, in fact, they don’t believe that the market is rigged.[2] Perhaps the most surprising example of speed trumping fact checks comes in a footnote at the end of Chapter 7.

Oddly, Katsuyama and his trader colleagues at RBC apparently did expect the world to wait while they received and processed their stock market information. They knew that, for individual investors, stock prices might change between the time that you or I saw the price 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 there until they decided to act on it. In effect, they believed that they were entitled to whatever price they had seen at the gas station yesterday, even if the rest of us weren’t. When they realized that, just like everyone else, the prices they were seeing were yesterday’s news, they declared the market was rigged.

You made $0.54 cents per share – not the 6% return you expected, but actually a 5.4% return. Where did the money go? That extra money vanished into “the spread.” Ten percent of your return disappeared. Poof. This is why the spread is quite important: if it is big, you waste a lot of 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 than to make the reader compare fractions. So, let us convert Lewis’ fractions into decimal percentages: the spread dropped from 0.0625% to 0.0100%. Put another way, Lewis tells us that the transaction costs to buy and sell your stock dropped six times lower after we moved to a computerized market.


pages: 374 words: 114,600

The Quants by Scott Patterson

Albert Einstein, asset allocation, automated trading system, beat the dealer, Benoit Mandelbrot, Bernie Madoff, Bernie Sanders, Black Swan, Black-Scholes formula, Blythe Masters, Bonfire of the Vanities, Brownian motion, buttonwood tree, buy and hold, buy low sell high, capital asset pricing model, centralized clearinghouse, Claude Shannon: information theory, cloud computing, collapse of Lehman Brothers, collateralized debt obligation, commoditize, computerized trading, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, Donald Trump, Doomsday Clock, Edward Thorp, Emanuel Derman, Eugene Fama: efficient market hypothesis, fixed income, Gordon Gekko, greed is good, Haight Ashbury, I will remember that I didn’t make the world, and it doesn’t satisfy my equations, index fund, invention of the telegraph, invisible hand, Isaac Newton, job automation, John Meriwether, John Nash: game theory, Kickstarter, law of one price, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, margin call, merger arbitrage, money market fund, Myron Scholes, NetJets, new economy, offshore financial centre, old-boy network, Paul Lévy, Paul Samuelson, Ponzi scheme, quantitative hedge fund, quantitative trading / quantitative finance, race to the bottom, random walk, Renaissance Technologies, risk-adjusted returns, Robert Mercer, Rod Stewart played at Stephen Schwarzman birthday party, Ronald Reagan, Sergey Aleynikov, short selling, South Sea Bubble, speech recognition, statistical arbitrage, The Chicago School, The Great Moderation, The Predators' Ball, too big to fail, transaction costs, value at risk, volatility smile, yield curve, éminence grise

After Merrill, the peripatetic Tartaglia went to five other firms before landing at Morgan in 1984. He renamed the group he’d taken over Automated Proprietary Trading, or APT, and moved it to a single forty-foot-long room on the nineteenth floor in Morgan’s Exxon Building headquarters in mid-town Manhattan. Tartaglia 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 strategy earned $6 million in the first year Tartaglia ran the group. In 1986, it pulled in an eye-popping $40 million, then $50 million in 1987. The group started to gain legendary status on Wall Street, in part due to its CIA-like secrecy. In 1986, Tartaglia hired David Shaw, a computer whiz teaching at Columbia University, to head APT’s technology unit.

This machine has no name. But it is one of the most revolutionary technological developments of modern times. It is vast, its octopuslike tentacles reaching to the farthest corners of civilization, yet it is also practically invisible. Call it the 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 Brothers and eventual mayor of New York City, designed a machine that would allow users to get data on virtually any security in the world in seconds, turning its creator into a billionaire. The Nasdaq Stock Market, which provided entirely electronic transactions, as opposed to the lumbering humans at the New York Stock Exchange, made it quicker and cheaper to buy and sell stocks around the globe.

They started trading in the United States, then added Japan, followed by London and Paris. They would trade once a day, based on their models. They worked crazy hours, but it all seemed for naught. Muller was able to glean tidbits of information from other fledgling groups of mathematicians who were trying 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 Morgan Stanley, for seed capital. Muller’s job was to check them out. A founder of Prediction Company was Doyne Farmer, a tall, ropy physicist and early innovator in an obscure science called chaos theory. Given more to tie-dyed T-shirts and flip-flops than the standard-issue Wall Street suit and tie, Farmer had followed in Ed Thorp’s footsteps in the 1980s, creating a system to predict roulette using cutting-edge computers wedged into elaborate “magic” shoes.


pages: 356 words: 105,533

Dark Pools: The Rise of the Machine Traders and the Rigging of the U.S. Stock Market by Scott Patterson

algorithmic trading, automated trading system, banking crisis, bash_history, Bernie Madoff, butterfly effect, buttonwood tree, buy and hold, Chuck Templeton: OpenTable:, cloud computing, collapse of Lehman Brothers, computerized trading, creative destruction, Donald Trump, fixed income, Flash crash, Francisco Pizarro, Gordon Gekko, Hibernia Atlantic: Project Express, High speed trading, Joseph Schumpeter, latency arbitrage, Long Term Capital Management, Mark Zuckerberg, market design, market microstructure, pattern recognition, pets.com, Ponzi scheme, popular electronics, prediction markets, quantitative hedge fund, Ray Kurzweil, Renaissance Technologies, Sergey Aleynikov, Small Order Execution System, South China Sea, Spread Networks laid a new fibre optics cable between New York and Chicago, stealth mode startup, stochastic process, transaction costs, Watson beat the top human players on Jeopardy!, zero-sum game

In another life, the bespectacled five-seven onetime trader would have been teaching students quantum physics or working for Mission Control at NASA. Instead, starting in 2001, he’d devoted himself to building a space-age trading platform for Credit Suisse called Advanced Electronic Systems. He was an elite market 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, worth hundreds of millions of dollars to those in the know. The reason: A new breed of trader had emerged who focused on gaming the plumbing itself, exploiting complex loopholes and quirks inside the blueprints like card counters ferreting out weaknesses in a blackjack dealer’s hand.

Most of Hull’s top people had already left, and the creative magic that had driven Hull’s machine for years had been suffocated by Goldman’s embrace, he felt. In 2003, Bodek landed at UBS and set up shop at the bank’s massive Stamford headquarters. The Guinness Book of World Records had dubbed UBS’s Stamford trading floor the largest in the 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 go head-to-head with the likes of Hull—and he succeeded in spades. His first signal achievement was an entirely new options trading strategy called dynamic sizing. In September 2003, soon after he’d arrived at UBS, he developed a monster algorithm to dominate all others.

The market had been designed for limit orders. An insiders’ term for the market itself was a “central limit order book”—a CLOB in the industry jargon. No less than USA Today told investors that “the best, easiest and free way for investors to protect 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 traders like ducks in a pond. BODEK thought practically nonstop for days about what the exchange representative had told him that night at the New York party. The way that the abusive order types worked made him think back to a document he’d been given by a colleague that summer as he researched what was going wrong at Trading Machines.


pages: 318 words: 87,570

Broken Markets: How High Frequency Trading and Predatory Practices on Wall Street Are Destroying Investor Confidence and Your Portfolio by Sal Arnuk, Joseph Saluzzi

algorithmic trading, automated trading system, Bernie Madoff, buttonwood tree, buy and hold, commoditize, computerized trading, corporate governance, cuban missile crisis, financial innovation, Flash crash, Gordon Gekko, High speed trading, latency arbitrage, locking in a profit, Mark Zuckerberg, market fragmentation, Ponzi scheme, price discovery process, price mechanism, price stability, Sergey Aleynikov, Sharpe ratio, short selling, Small Order Execution System, statistical arbitrage, stocks for the long run, stocks for the long term, transaction costs, two-sided market, zero-sum game

Here is how Traders Magazine, a leading industry publication, described the morning after, in an article titled, “Sellside Moves to Protect Buyside from HFT Onslaught”:18 Talk about the power of television. On Monday morning, Oct. 11, 2010, the phones in Credit Suisse’s Advanced Execution Services department were ringing more than usual. On the other end were anxious customers asking the big broker what it was doing to protect their orders from predatory black-box traders. They had all watched 60 Minutes the night before, when the popular television program explored the world of computerized trading and the role of high-frequency traders. Reporter Steve Kroft interviewed Joe Saluzzi, co-head of agency brokerage Themis Trading, who told Kroft that high-frequency traders were using their superior firepower-i.e., speed-to push prices up or down, to the disadvantage of the institutional investor. “They’re parasites who exploit technological advantages to suck money out of the market,” Saluzzi told Kroft.

As nonprofit companies, they said they were in business to serve investors and publicly listed companies, but critics accused them of using their market power to fend off competitors, keep trading costs high, and protect their owner-members. In 1997, alternative markets called electronic crossing networks, or ECNs, sprang up, encouraged by the SEC to compete with the established exchanges. The new ECNs were for-profit companies that, unlike the NYSE and NASDAQ, relied exclusively on computerized trading to do business. They also introduced a low-cost business model that was relatively new to the United States. Unlike NASDAQ and the NYSE, the ECNs didn’t have middlemen called “specialists” or “market makers,” regulated firms that were obligated to be in the market at all times, ready to buy and sell stock with investors. Instead, ECNs let investors trade directly with each other, cutting out the middlemen and in theory lowering costs, but also exposing their markets to the whims of whoever did or didn’t show up.

Reformers judged that if market makers were cheating their investor customers, then investors should just trade directly with one another, bypassing the market makers altogether. ECNs offered that service. Investors don’t always come to the market at the same time, however. A buyer might have to wait quite a while for a seller to show up. The ECNs quickly discovered they too needed middlemen to provide liquidity to their markets. With an emphasis on blazing-fast computerized trading, and with an emerging technology base that supported vast amounts of computer transactions, in an ironic twist the ECNs soon became a food plot for a new kind of firm, one that looked like a middleman but wasn’t regulated like one. Sharp-eyed traders figured out there was a good business in being a middleman on the ECNs if they didn’t have to obey the same rules as the NYSE specialists or the NASDAQ market makers, and they didn’t.


pages: 280 words: 73,420

Crapshoot Investing: How Tech-Savvy Traders and Clueless Regulators Turned the Stock Market Into a Casino by Jim McTague

algorithmic trading, automated trading system, Bernie Madoff, Bernie Sanders, Bretton Woods, buttonwood tree, buy and hold, computerized trading, corporate raider, creative destruction, credit crunch, Credit Default Swap, financial innovation, fixed income, Flash crash, High speed trading, housing crisis, index arbitrage, locking in a profit, Long Term Capital Management, margin call, market bubble, market fragmentation, market fundamentalism, Myron Scholes, naked short selling, pattern recognition, Ponzi scheme, quantitative trading / quantitative finance, Renaissance Technologies, Ronald Reagan, Sergey Aleynikov, short selling, Small Order Execution System, statistical arbitrage, technology bubble, transaction costs, Vanguard fund, Y2K

After a few years at the prestigious firm, they both concluded independently that to advance in the world of finance, they’d have to obtain graduate degrees. So they both left Morgan Stanley to enroll in MBA programs. Arnuk started attending the Stern School of Business at NYU part time; and Saluzzi resigned a few months later to attend the Kenan-Flagler Business School of the University of North Carolina. Arnuk graduated in 1991, and Saluzzi in 1993. Arnuk began working for Instinet, a global brokerage firm that specialized in computerized trading. He recruited Saluzzi for a job there. They were neighbors at this point. Both men had married and secured homes in Bay Ridge. In 2002, Saluzzi and Arnuk got tired of the rat race and decided to move to New Jersey and start their own company. Arnuk was the first to go, and he convinced Saluzzi to join him in a trading venture. They were not making the kind of big money that drives a congressman to denounce Wall Street from the floor of the House or the Senate, but they were not doing badly either.

Before the appearance of the Europeans on U.S. soil, there had been four major commodities exchanges and several smaller, specialized, regional exchanges. All of them had been owned mutually by their trading members. The largest exchanges were the Chicago Mercantile Exchange (CME); the Chicago Board of Trade (CBOT); the New York Mercantile Exchange; and the New York Board of Trade. Throughout the 1990s when computerized trading began to spread owing to the introduction of more sophisticated personal computers, these exchanges resisted the transformation to electronic trading simply because that threatened the livelihood of their owners. The CBOT was the oldest exchange, established in 1847. At its founding, it specialized in wheat and oat futures. In the twentieth century, it proved to be one of the most innovative exchanges in the world, introducing U.S.

SECs investigators also felt the need to acquire secondary information in the form of testimony and interviews from market participants to flesh out the story told by the tape. The SEC picked up the pace of its information gathering within a few weeks, inviting a roundtable of experts on high-frequency trading (HFT) to its headquarters on June 2 for a public discussion of the pluses and minuses of computerized trading. Schapiro had urged Kaufman to watch her, and he was—like a hawk. He didn’t like what he was seeing. A spy had leaked him a list of the panel’s participants in advance, and it was laughably lopsided in favor of high-frequency traders. They were to occupy six of seven seats on the stage. The Senator could hardly believe his eyes. Kaufman angrily wrote a protest letter to Schapiro and then took to the floor of the Senate to bring his complaint to the attention of his colleagues and the press.


pages: 342 words: 94,762

Wait: The Art and Science of Delay by Frank Partnoy

algorithmic trading, Atul Gawande, Bernie Madoff, Black Swan, blood diamonds, Cass Sunstein, Checklist Manifesto, cognitive bias, collapse of Lehman Brothers, collateralized debt obligation, computerized trading, corporate governance, Daniel Kahneman / Amos Tversky, delayed gratification, Flash crash, Frederick Winslow Taylor, George Akerlof, Google Earth, Hernando de Soto, High speed trading, impulse control, income inequality, information asymmetry, Isaac Newton, Long Term Capital Management, Menlo Park, mental accounting, meta analysis, meta-analysis, MITM: man-in-the-middle, Nick Leeson, paper trading, Paul Graham, payday loans, Ralph Nader, Richard Thaler, risk tolerance, Robert Shiller, Robert Shiller, Ronald Reagan, Saturday Night Live, six sigma, Spread Networks laid a new fibre optics cable between New York and Chicago, Stanford marshmallow experiment, statistical model, Steve Jobs, The Market for Lemons, the scientific method, The Wealth of Nations by Adam Smith, upwardly mobile, Walter Mischel

If only one share is available at a low price, the first buy order to arrive will secure that price. Any later orders might pay more. High-speed trading can be a kind of temporal arms race, like a superfast version of holiday shopping. If you aren’t among the first customers in line on Black Friday for the post-Thanksgiving sale, by the time you get in the door the best bargains will be gone. High-frequency traders say this kind of superfast computerized trading is good for all investors because we can buy or sell whenever we want at the lowest possible cost. Others argue that the increasing speed of trading is not only socially wasteful but dangerous. Critics believe we have been fortunate to avoid a market crash caused by high-frequency trading and that someday we will not be so lucky. One fundamental concern is that although stock prices quickly reflect new information, short-term price swings are too volatile and do not reflect a company’s long-term value; at some point, if automated trading programs push stock prices too far in one direction, they will abruptly reverse.

One fundamental concern is that although stock prices quickly reflect new information, short-term price swings are too volatile and do not reflect a company’s long-term value; at some point, if automated trading programs push stock prices too far in one direction, they will abruptly reverse. At its core, the debate is about computer versus human decision-making. Is it better to let computers trade on their own at preconscious speeds, or do we need conscious human intervention? At 2:32 PM on May 6, 2010, an employee of Waddell & Reed, a mutual fund company headquartered about a mile from my childhood home in Overland Park, Kansas, clicked Start on a computerized trading software program.5 The firm’s goal was to reduce its exposure to $4.1 billion of stocks it owned by selling something called “E-Mini” futures contracts. The E-Mini is based on the Standard & Poor’s 500 Index of top stocks, except that it is traded in small amounts (hence “Mini”), and it goes through an electronic trading platform instead of the frenzied “open outcry” method still used for other futures contracts (hence “E-”).

But then, at 2:41 PM, high-frequency traders began selling the contracts they had accumulated to zero out their positions. During the first minute, as they switched sides, trading volume increased and Waddell & Reed’s automated program responded by selling a larger number of E-Mini contracts. During the second minute, more traders sold and so did the automated program. During the third and fourth minutes, everyone sold even more, in a kind of high-speed computerized trading death spiral. By 2:45 PM, trading volume was exploding and the E-Mini futures contract was collapsing. Its price had fallen 5 percent in just thirteen minutes. The high-frequency computer programs were a big chunk of the market at this time. During one fourteen-second period, high-frequency traders accounted for 27,000 E-Mini contracts, about half of the total trading volume. The decline in the value of the E-Mini contracts instantly spread to the rest of the market.


pages: 467 words: 154,960

Trend Following: How Great Traders Make Millions in Up or Down Markets by Michael W. Covel

Albert Einstein, Atul Gawande, backtesting, beat the dealer, Bernie Madoff, Black Swan, buy and hold, buy low sell high, capital asset pricing model, Clayton Christensen, commodity trading advisor, computerized trading, correlation coefficient, Daniel Kahneman / Amos Tversky, delayed gratification, deliberate practice, diversification, diversified portfolio, Edward Thorp, Elliott wave, Emanuel Derman, Eugene Fama: efficient market hypothesis, Everything should be made as simple as possible, fiat currency, fixed income, game design, hindsight bias, housing crisis, index fund, Isaac Newton, John Meriwether, John Nash: game theory, linear programming, Long Term Capital Management, mandelbrot fractal, margin call, market bubble, market fundamentalism, market microstructure, mental accounting, money market fund, Myron Scholes, Nash equilibrium, new economy, Nick Leeson, Ponzi scheme, prediction markets, random walk, Renaissance Technologies, Richard Feynman, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Shiller, shareholder value, Sharpe ratio, short selling, South Sea Bubble, Stephen Hawking, survivorship bias, systematic trading, the scientific method, Thomas L Friedman, too big to fail, transaction costs, upwardly mobile, value at risk, Vanguard fund, William of Occam, zero-sum game

It traded each market three to five times a year, automatically reversing if the trend moved in the other direction. [Dunn determined] position size by risking 2 percent to 6 percent of equity under management on each trade.”18 It’s not uncommon for long-term trend followers to have trades in place for well over a year, hence the term “long.” If you want day trading insanity or the feeling of exhilaration in Las Vegas, Dunn is not the person you should choose as a trading role model. Following his computerized trading system, Dunn holds longterm positions in major trends typically trading only two to five times per year in each market. The original system was and still is a reversal system, whereby it is always in the market, either long or Chapter 2 • Great Trend Followers short. Dunn says he’s held winning positions for as long as a year and half.19 Early on Dunn needed more capital to execute his particular plan of trading attack.

Ed Seykota52 60 Trend Following (Updated Edition): Learn to Make Millions in Up or Down Markets About Ed Seykota Seykota was born in 1946. He earned his Bachelor of Science from MIT in 1969 and by 1972 had embarked on the trading career he pursues to this day—investing for his own account and the accounts of a few select others. He was self-taught, but influenced in his career by Amos Hostetter and Richard Donchian. Early in his career, Seykota was hired by a major broker. He conceived and developed the first commercial computerized trading system for client money in the futures markets. According to Jack Schwager’s Market Wizards, he increased one client’s account from $5,000 to $15,000,000 in just 12 years. For the past few years, Seykota has worked from a home office in Incline Village, Nevada. His trading is largely confined to the few minutes it takes to run his internally written computer program, which generates trading signals for the next day.

Money managers must deal with the pressure and expectations of clients at all times. There may have been other reasons for Dennis’ problems beyond pressure and expectations from clients. For example, Dennis said he could not program a computer if it walked in and bit him. He outsourced his programming, as many traders do. But there is something to be said about knowing how everything under the hood works. Ed Seykota is generally acknowledged to have programmed the first computerized trading system. Bill Dunn and his staff wrote their original programming for their trading systems. In other words, there may be value in learning all you can about every aspect of trading if you are going to trade a trend following trading system. Key Points • Dennis: “Trading was even more teachable than I imagined. In a strange sort of way, it was almost humbling.” • Dennis: “When you have a position, you put it on for a reason, and you’ve got to keep it until the reason no longer exists.


pages: 354 words: 26,550

High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems by Irene Aldridge

algorithmic trading, asset allocation, asset-backed security, automated trading system, backtesting, Black Swan, Brownian motion, business cycle, business process, buy and hold, capital asset pricing model, centralized clearinghouse, collapse of Lehman Brothers, collateralized debt obligation, collective bargaining, computerized trading, diversification, equity premium, fault tolerance, financial intermediation, fixed income, high net worth, implied volatility, index arbitrage, information asymmetry, interest rate swap, inventory management, law of one price, Long Term Capital Management, Louis Bachelier, margin call, market friction, market microstructure, martingale, Myron Scholes, New Journalism, p-value, paper trading, performance metric, profit motive, purchasing power parity, quantitative trading / quantitative finance, random walk, Renaissance Technologies, risk tolerance, risk-adjusted returns, risk/return, Sharpe ratio, short selling, Small Order Execution System, statistical arbitrage, statistical model, stochastic process, stochastic volatility, systematic trading, trade route, transaction costs, value at risk, yield curve, zero-sum game

Figure 3.3 illustrates the cost curves for rolling out computerized and traditional trading systems. The cost of traditional trading remains fairly constant through time. With the exception of trader “burn-outs” necessitating hiring and training new trader staff, costs of staffing the traditional trading desk do not change. Developing computerized trading systems, however, requires an up-front investment that is costly in terms of labor and time. One successful trading system takes on average 18 months to develop. The costs of computerized trading decline as the system moves into production, ultimately requiring a small support staff that typically includes a dedicated systems engineer and a performance monitoring agent. Both the systems engineer and a monitoring agent can be responsible for several trading systems simultaneously, driving the costs closer to zero. 28 HIGH-FREQUENCY TRADING Cost High-frequency trading Traditional trading Time in development and use FIGURE 3.3 The economics of high-frequency versus traditional trading businesses.

Whoever was able to run a quant model the fastest was the first to identify and trade upon a market inefficiency and was the one to capture the biggest gain. To increase trading speed, traders began to rely on fast computers to make and execute trading decisions. Technological progress enabled exchanges to adapt to the new technology-driven culture and offer docking convenient for trading. Computerized trading became known as “systematic trading” after the computer systems that processed run-time data and made and executed buy-and-sell decisions. High-frequency trading developed in the 1990s in response to advances in computer technology and the adoption of the new technology by the exchanges. From the original rudimentary order processing to the current state-of-the-art all-inclusive trading systems, high-frequency trading has evolved into a billion-dollar industry.


pages: 280 words: 79,029

Smart Money: How High-Stakes Financial Innovation Is Reshaping Our WorldÑFor the Better by Andrew Palmer

Affordable Care Act / Obamacare, algorithmic trading, Andrei Shleifer, asset-backed security, availability heuristic, bank run, banking crisis, Black-Scholes formula, bonus culture, break the buck, Bretton Woods, call centre, Carmen Reinhart, cloud computing, collapse of Lehman Brothers, collateralized debt obligation, computerized trading, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Daniel Kahneman / Amos Tversky, David Graeber, diversification, diversified portfolio, Edmond Halley, Edward Glaeser, endogenous growth, Eugene Fama: efficient market hypothesis, eurozone crisis, family office, financial deregulation, financial innovation, fixed income, Flash crash, Google Glasses, Gordon Gekko, high net worth, housing crisis, Hyman Minsky, implied volatility, income inequality, index fund, information asymmetry, Innovator's Dilemma, interest rate swap, Kenneth Rogoff, Kickstarter, late fees, London Interbank Offered Rate, Long Term Capital Management, longitudinal study, loss aversion, margin call, Mark Zuckerberg, McMansion, money market fund, mortgage debt, mortgage tax deduction, Myron Scholes, negative equity, Network effects, Northern Rock, obamacare, payday loans, peer-to-peer lending, Peter Thiel, principal–agent problem, profit maximization, quantitative trading / quantitative finance, railway mania, randomized controlled trial, Richard Feynman, Richard Thaler, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Shiller, short selling, Silicon Valley, Silicon Valley startup, Skype, South Sea Bubble, sovereign wealth fund, statistical model, Thales of Miletus, transaction costs, Tunguska event, unbanked and underbanked, underbanked, Vanguard fund, web application

Despite making a lot of deals, the capital they kept invested in the company was low on average, which suggests they were making their money by trading in the shares. By providing liquidity, the Raphoens made it easier for people to buy and sell, which in turn made the market more attractive to financial traders and increased the volume of transactions on the exchange. The Raphoens would not recognize the form of their modern counterparts—computerized trading firms that zip in and out of holdings at staggering speeds—but their function would be familiar enough. *** THE INSURANCE MARKET also took a big leap forward in the seventeenth century, thanks to the forgetfulness of a London baker named Thomas Farynor. His failure to properly put out the ashes of a fire at his shop on Pudding Lane led to a blaze that started in the early hours of September 2, 1666, and four days later had spread across the center of the city and destroyed 13,200 homes.

Institutional investors may now complain about being forced into “dark pools” (off-exchange venues where they can deal anonymously) to avoid the high-frequency traders, but these pools existed before HFTs and were set up in part to avoid being scalped by brokers or floor traders. Indeed, in the very early days of automation, it was the machines that needed protection from the humans. One of the pioneers of computerized trading was a firm called the Prediction Company, which was founded in 1991 in Santa Fe, New Mexico, by a couple of chaos physicists called Norman Packard and Doyne Farmer. Packard and Farmer had already worked together on a scheme to beat the house at roulette using a toe-operated computer; the Prediction Company was an equally idiosyncratic attempt to take on the biggest casino of all, the stock market, by using physics-based models to predict short-term price movements.


pages: 304 words: 80,965

What They Do With Your Money: How the Financial System Fails Us, and How to Fix It by Stephen Davis, Jon Lukomnik, David Pitt-Watson

activist fund / activist shareholder / activist investor, Admiral Zheng, banking crisis, Basel III, Bernie Madoff, Black Swan, buy and hold, centralized clearinghouse, clean water, computerized trading, corporate governance, correlation does not imply causation, credit crunch, Credit Default Swap, crowdsourcing, David Brooks, Dissolution of the Soviet Union, diversification, diversified portfolio, en.wikipedia.org, financial innovation, financial intermediation, fixed income, Flash crash, income inequality, index fund, information asymmetry, invisible hand, Kenneth Arrow, Kickstarter, light touch regulation, London Whale, Long Term Capital Management, moral hazard, Myron Scholes, Northern Rock, passive investing, performance metric, Ponzi scheme, post-work, principal–agent problem, rent-seeking, Ronald Coase, shareholder value, Silicon Valley, South Sea Bubble, sovereign wealth fund, statistical model, Steve Jobs, the market place, The Wealth of Nations by Adam Smith, transaction costs, Upton Sinclair, value at risk, WikiLeaks

Because their electronic signals literally have less distance to travel, they can react to developments and leap in before everyone else’s buy and sell requests. High-frequency traders can buy and sell the ownership right in a company one thousand times in the time it takes you to blink. To be clear, this activity is not marginal to our capital markets. The World Federation of Exchanges notes that in 2012, computerized trading programs accounted for an estimated 51 percent of shares traded in the United States and 39 percent of shares traded in Europe.6 Thanks to the rise of these high-frequency traders and the glorification of day trading, the activity in buying and selling companies has exploded. That changed context pervades—some would say perverts—the thinking of virtually every market participant. Few share Buffett’s favorite holding period of forever.

When former SEC chair Elisse Walter was asked about the SEC’s role in facilitating high-frequency trading, she admitted that the regulatory response had been “inconsistent.”64 ENCOURAGE NEW TRADING PLATFORMS THAT PROTECT INVESTORS Some entrepreneurs are not waiting for regulators to tackle the high-frequency trading issue but are creating a new exchange, called the IEX, that will build a 350 microsecond delay into its computerized trading so as to frustrate high-frequency traders. Nor will the IEX pay the rebates other exchanges pay to high-frequency traders to get them to boost volumes and liquidity. The IEX is backed by mutual fund companies and other longer-term investors, and the hope is that it will attract enough investors frustrated with the advantages given to high-frequency traders to provide adequate liquidity.65 It may or may not work, but the basic idea, to find a venue where longer-term investors can be treated fairly, will no doubt be a driving force in other innovations.


pages: 512 words: 162,977

New Market Wizards: Conversations With America's Top Traders by Jack D. Schwager

backtesting, beat the dealer, Benoit Mandelbrot, Berlin Wall, Black-Scholes formula, butterfly effect, buy and hold, commodity trading advisor, computerized trading, Edward Thorp, Elliott wave, fixed income, full employment, implied volatility, interest rate swap, Louis Bachelier, margin call, market clearing, market fundamentalism, money market fund, paper trading, pattern recognition, placebo effect, prediction markets, Ralph Nelson Elliott, random walk, risk tolerance, risk/return, Saturday Night Live, Sharpe ratio, the map is not the territory, transaction costs, War on Poverty

The lack of intrinsic meaning of angles on a bar chart has significance even for chart-oriented traders who do not employ angles. How sharply a trend slopes on a chart is often a psychological consideration in making a trade. If you fall prey to this influence, you’re letting the chart maker’s practical and aesthetic considerations impinge on your trading. Any trend can be made to look either gentle or steep by adjusting the price scale. This example also highlights one of the advantages of computerized trading. A computer ignores all but what it is instructed not to ignore. If you wanted your computer system to be cognizant of slope, you would have to program this feature into it. At that point, it would become abundantly clear that the slope value depends directly on the choice of units and scales for the time and price axes. William Eckhardt / 111 I’ve always been amazed by how many people are either oblivious to the scale-dependent nature of chart angles or unconcerned about its ramifications.

Driehaus says that the mind is like a parachute; it’s good only when it’s open. 35. THE MARKETS ARE AN EXPENSIVE PLACE TO LOOK FOR EXCITEMENT Excitement has a lot to do with the image of trading but nothing to do with success in trading (except in an inverse sense). In Market Wizards, 476 / The New Market Wizard Larry Hite described his conversation with a friend who couldn’t understand his absolute adherence to a computerized trading system. His friend asked, “Larry, how can you trade the way you do. Isn’t it boring?” Larry replied, “I don’t trade for excitement; 1 trade to win.” This passage came to mind when Faulkner described the trader who blew out because he found it too boring to be trading in the way that produced profits. 36. THE CALM STATE OF A TRADER If there is an emotional state associated with successful trading, it is the antithesis of excitement.

At one point, after years of net profitable recommendations, I hit a bad streak. I just couldn’t do anything right. When I was right about the direction of the market, my buy recommendation was just a bit too low (or my sell price too high). When I got in and the direction was right, I got stopped out—frequently within a few ticks of the extreme of the reaction. I responded by developing a range of computerized trading programs and technical indicators, thereby widely diversifying the trading Market Wiz(ar)dom / 477 advice I provided to the firm. I still made my day-to-day subjective calls on the market, but everything was no longer riding on the accuracy of these recommendations. By widely diversifying the trading-related advice and information, and transferring much of this load to mechanical approaches, I was able to greatly diminish a source of personal stress—and improve the quality of the research product in the process. 38.


Risk Management in Trading by Davis Edwards

asset allocation, asset-backed security, backtesting, Black-Scholes formula, Brownian motion, business cycle, computerized trading, correlation coefficient, Credit Default Swap, discrete time, diversified portfolio, fixed income, implied volatility, intangible asset, interest rate swap, iterative process, John Meriwether, London Whale, Long Term Capital Management, margin call, Myron Scholes, Nick Leeson, p-value, paper trading, pattern recognition, random walk, risk tolerance, risk/return, selection bias, shareholder value, Sharpe ratio, short selling, statistical arbitrage, statistical model, stochastic process, systematic trading, time value of money, transaction costs, value at risk, Wiener process, zero-coupon bond

Only Strategy A B. Only Strategy B C. An equal weight combination of Strategy A + Strategy B D. A combination of Strategy A and B, with a larger investment in Strategy A than Strategy B What is a way to reduce trading risk? A. Require all trades to be recorded with a trading repository that ensures that trades are accurately recorded on the day of entry. B. A system to prevent unusually large computerized trades without approval by a human. C. Perform suitability checks on trades, like credit risk approval and restricted lists, to ensure that approved instruments are being traded in approved sizes. D. All are ways to reduce risk. Which answer best describes the term slippage in the context of a trading strategy? A. The risk that the price obtained from trading will be different than the price expected when the order was sent to the market.

However, since Strategy A and Answer Key 279 B are anti‐correlated (correlation = −1.0), the volatility will exactly offset. In other words, an equally weighted combination of Strategy A and Strategy B will have a positive return with no volatility. 5. What is a way to reduce trading risk? A. Require all trades to be recorded with a trading repository that ensures that trades are accurately recorded on the day of entry. B. A system to prevent unusually large computerized trades without approval by a human. C. Perform suitability checks on trades, like credit risk approval and restricted lists, to ensure that approved instruments are being traded in approved sizes. D. All are ways to reduce risk. Correct Answer: D Explanation: All are examples of ways that computer systems can reduce the risk of trading. 6. Which answer best describes the term slippage in the context of a trading strategy?


pages: 151 words: 38,153

With Liberty and Dividends for All: How to Save Our Middle Class When Jobs Don't Pay Enough by Peter Barnes

Alfred Russel Wallace, banks create money, basic income, Buckminster Fuller, collective bargaining, computerized trading, creative destruction, David Ricardo: comparative advantage, declining real wages, deindustrialization, diversified portfolio, en.wikipedia.org, Fractional reserve banking, full employment, hydraulic fracturing, income inequality, Jaron Lanier, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, land reform, Mark Zuckerberg, Network effects, oil shale / tar sands, Paul Samuelson, profit maximization, quantitative easing, rent-seeking, Ronald Coase, Ronald Reagan, Silicon Valley, sovereign wealth fund, the map is not the territory, The Spirit Level, The Wealth of Nations by Adam Smith, Thorstein Veblen, transaction costs, Tyler Cowen: Great Stagnation, Upton Sinclair, Vilfredo Pareto, wealth creators, winner-take-all economy

What Ford showed in the twentieth century was that automation could have the opposite effect. By making complex products so cheap that millions could afford to buy them, it vastly increased the number of workers needed. On top of that, it enabled large, automated companies to pay decent wages. This was the beginning of industrial America’s mass middle class. Today, automation is displacing workers again. ATMs replace human tellers, e-mail replaces postal workers, computerized trading replaces floor traders, and so on. The result is an American workforce that’s splitting into well-paid elites at the top and low-paid service workers at the bottom, with few decently paid punters in the middle. Deunionization. An affluent economy is a prerequisite for a large middle class but by no means a guarantee. To sustain a large middle class, a nation must consciously and continuously temper the natural impulse of capitalism to minimize labor costs.


pages: 403 words: 119,206

Toward Rational Exuberance: The Evolution of the Modern Stock Market by B. Mark Smith

bank run, banking crisis, business climate, business cycle, buy and hold, capital asset pricing model, compound rate of return, computerized trading, credit crunch, cuban missile crisis, discounted cash flows, diversified portfolio, Donald Trump, Eugene Fama: efficient market hypothesis, financial independence, financial innovation, fixed income, full employment, income inequality, index arbitrage, index fund, joint-stock company, locking in a profit, Long Term Capital Management, Louis Bachelier, margin call, market clearing, merger arbitrage, money market fund, Myron Scholes, Paul Samuelson, price stability, random walk, Richard Thaler, risk tolerance, Robert Bork, Robert Shiller, Robert Shiller, Ronald Reagan, shareholder value, short selling, stocks for the long run, the market place, transaction costs

The dictionary definition of “arbitrage” is “the purchase of securities in one market for resale on another market in order to profit from a price discrepancy.” Index arbitrageurs buy all the stocks that make up an index and simultaneously sell the index futures when the price of the futures is too high, or do the reverse when the price of the futures is too low. To accomplish this quickly for a large number of stocks, computerized trading was necessary—hence the oft-used phrase “computer trading” (or “program trading”). It was assumed that index arbitrage would always keep the futures prices in line with cash prices. According to Leland, portfolio insurance was ideal for pension funds that needed to meet certain defined obligations but could afford to take more risk once the ability to meet those obligations was guaranteed.

The stock market began to trend lower in September, with the pace of the decline accelerating in early October. Concerns were expressed about the potential impact on the market of new program trading systems (such as the index arbitrage discussed in chapter 14). Writing about the early October market slide, The Wall Street Journal took note of these sentiments, referring to “fears that some computerized trading techniques, such as portfolio insurance, could deal a nasty blow to an already fragile market.” Things quickly got worse. The week ending Friday, October 16, witnessed a steep decline in prices, with the biggest drop occurring at the end of the week. On Friday the Dow Industrials fell more than 100 points, or 4.6%, the sixth largest percentage loss since World War II. New York Stock Exchange trading volume soared to a record 344 million shares, bursting the old mark of 302 million.


pages: 119 words: 10,356

Topics in Market Microstructure by Ilija I. Zovko

Brownian motion, computerized trading, continuous double auction, correlation coefficient, financial intermediation, Gini coefficient, information asymmetry, market design, market friction, market microstructure, Murray Gell-Mann, p-value, quantitative trading / quantitative finance, random walk, stochastic process, stochastic volatility, transaction costs

Quantitative model of price diffusion and market friction based on trading as a mechanistic random process. Physical Review Letters, 90(10): Article no. 108102, 2003. H. Demsetz. The cost of transacting. The Quarterly Journal of Economics, 82:33–53, 1968. P. M. Dixon, J. Weiner, T. Mitchell-Olds, and R. Woodley. Bootstrapping the gini coefficient of inequality. Ecology, 68(5):1548– 1551, 1987. I. Domowitz and J. Wang. Auctions as algorithms: Computerized trade execution and price discovery. Journal of Economic Dynamics and Control, 18(1):29–60, 1994. D. Easley and M. O’Hara. Price, trade size, and information in securities markets. Journal of Financial Economics, 19(1):69–90, 1987. D. Easley, M. O’Hara, and G. Saar. How stock splits affect trading: A microstructure approach. Journal of Financial and Quantitative Analysis, 36(1):25–51, 2001. 101 BIBLIOGRAPHY D.


pages: 515 words: 132,295

Makers and Takers: The Rise of Finance and the Fall of American Business by Rana Foroohar

accounting loophole / creative accounting, activist fund / activist shareholder / activist investor, additive manufacturing, Airbnb, algorithmic trading, Alvin Roth, Asian financial crisis, asset allocation, bank run, Basel III, bonus culture, Bretton Woods, British Empire, business cycle, buy and hold, call centre, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, carried interest, centralized clearinghouse, clean water, collateralized debt obligation, commoditize, computerized trading, corporate governance, corporate raider, corporate social responsibility, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, crowdsourcing, David Graeber, deskilling, Detroit bankruptcy, diversification, Double Irish / Dutch Sandwich, Emanuel Derman, Eugene Fama: efficient market hypothesis, financial deregulation, financial intermediation, Frederick Winslow Taylor, George Akerlof, gig economy, Goldman Sachs: Vampire Squid, Gordon Gekko, greed is good, High speed trading, Home mortgage interest deduction, housing crisis, Howard Rheingold, Hyman Minsky, income inequality, index fund, information asymmetry, interest rate derivative, interest rate swap, Internet of things, invisible hand, John Markoff, joint-stock company, joint-stock limited liability company, Kenneth Rogoff, Kickstarter, knowledge economy, labor-force participation, London Whale, Long Term Capital Management, manufacturing employment, market design, Martin Wolf, money market fund, moral hazard, mortgage debt, mortgage tax deduction, new economy, non-tariff barriers, offshore financial centre, oil shock, passive investing, Paul Samuelson, pensions crisis, Ponzi scheme, principal–agent problem, quantitative easing, quantitative trading / quantitative finance, race to the bottom, Ralph Nader, Rana Plaza, RAND corporation, random walk, rent control, Robert Shiller, Robert Shiller, Ronald Reagan, Satyajit Das, Second Machine Age, shareholder value, sharing economy, Silicon Valley, Silicon Valley startup, Snapchat, Social Responsibility of Business Is to Increase Its Profits, sovereign wealth fund, Steve Jobs, technology bubble, The Chicago School, the new new thing, The Spirit Level, The Wealth of Nations by Adam Smith, Tim Cook: Apple, Tobin tax, too big to fail, trickle-down economics, Tyler Cowen: Great Stagnation, Vanguard fund, zero-sum game

It’s a rare opportunity that must be seized, because, as I will explore in this book, our financial apparatus has collapsed under its own weight multiple times in the last several decades, and without changes to our system, it’s only a matter of time before it does again, taking us all down with it. THE LIFEBLOOD OF FINANCE Our shift to a system in which finance has become an end in and of itself, rather than a helpmeet for Main Street, has been facilitated by many changes within the financial services industry. One of them is a decrease in lending, and another is an increase in trading—particularly the kind of rapid-fire computerized trading that now makes up about half of all US stock market activity.13 The entire value of the New York Stock Exchange now turns over about once every nineteen months, a rate that has tripled since the 1970s.14 No wonder the size of the securities industry grew fivefold as a share of gross domestic product (GDP) between 1980 and mid-2000s while ordinary bank deposits shrunk from 70 to 50 percent of GDP.15 With the rise of the securities and trading portion of the industry came a rise in debt of all kinds, public and private.

Finance is now scooping up the country’s brightest people, diverting them from careers that would move our economy forward in more productive ways. Before the 1980s, banking was boring and not nearly as lucrative. But now PhDs who might once have crafted new engines at Boeing or come up with new polymers for Dow can make four to five times those former starting salaries at a hedge fund, where they can busy themselves creating twelve-dimensional computerized trading models. Eleven percent of the undergraduate class at MIT, for example, now goes to Wall Street, and despite the 2008 crisis, financial engineering is the fastest-growing field at many of the country’s best engineering schools.58 “Not only are these people not making scientific progress,” says Greg Smith, the former Goldman Sachs quantitative trader who famously published his resignation letter in the New York Times, “but the complex derivatives products they create are being sold to unsuspecting public pension funds and investors [who don’t know any better].


pages: 517 words: 139,477

Stocks for the Long Run 5/E: the Definitive Guide to Financial Market Returns & Long-Term Investment Strategies by Jeremy Siegel

Asian financial crisis, asset allocation, backtesting, banking crisis, Black-Scholes formula, break the buck, Bretton Woods, business cycle, buy and hold, buy low sell high, California gold rush, capital asset pricing model, carried interest, central bank independence, cognitive dissonance, compound rate of return, computer age, computerized trading, corporate governance, correlation coefficient, Credit Default Swap, Daniel Kahneman / Amos Tversky, Deng Xiaoping, discounted cash flows, diversification, diversified portfolio, dividend-yielding stocks, dogs of the Dow, equity premium, Eugene Fama: efficient market hypothesis, eurozone crisis, Everybody Ought to Be Rich, Financial Instability Hypothesis, fixed income, Flash crash, forward guidance, fundamental attribution error, housing crisis, Hyman Minsky, implied volatility, income inequality, index arbitrage, index fund, indoor plumbing, inflation targeting, invention of the printing press, Isaac Newton, joint-stock company, London Interbank Offered Rate, Long Term Capital Management, loss aversion, market bubble, mental accounting, money market fund, mortgage debt, Myron Scholes, new economy, Northern Rock, oil shock, passive investing, Paul Samuelson, Peter Thiel, Ponzi scheme, prediction markets, price anchoring, price stability, purchasing power parity, quantitative easing, random walk, Richard Thaler, risk tolerance, risk/return, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Reagan, shareholder value, short selling, Silicon Valley, South Sea Bubble, sovereign wealth fund, stocks for the long run, survivorship bias, technology bubble, The Great Moderation, the payments system, The Wisdom of Crowds, transaction costs, tulip mania, Tyler Cowen: Great Stagnation, Vanguard fund

After the close, the NYSE, in consultation with the Financial Industry Regulatory Authority (FINRA), “broke,” or canceled, all trades that were 60 percent or more above or below their previous price. It is very likely that these extreme prices would not have been realized if specialists, those exchange representatives who maintained markets in assigned stocks before the advent of computerized trading, still controlled the flow of buy and sell orders. These specialists would have stepped in to buy these stocks at prices well above the absurdly low price they traded at. But most modern computerized trading systems were programmed to react very differently than the specialists would have. When prices begin to fall steeply, the programs are instructed to withdraw from the market. This is because large moves in individual stocks are almost always associated with company-specific news that computerized traders do not have access to.


pages: 162 words: 51,473

The Accidental Theorist: And Other Dispatches From the Dismal Science by Paul Krugman

"Robert Solow", Bonfire of the Vanities, Bretton Woods, business cycle, clean water, collective bargaining, computerized trading, corporate raider, declining real wages, floating exchange rates, full employment, George Akerlof, George Gilder, Home mortgage interest deduction, income inequality, indoor plumbing, informal economy, invisible hand, Kenneth Arrow, knowledge economy, life extension, new economy, Nick Leeson, paradox of thrift, Paul Samuelson, plutocrats, Plutocrats, price stability, rent control, Ronald Reagan, Silicon Valley, trade route, very high income, working poor, zero-sum game

So Mahathir’s claims that he is the victim of an American conspiracy are just plain silly. He has nobody but himself to blame for his difficulties. Or at least that’s what George, Bob, and Madeleine told me to say. A Note on Currency Crises I often run into people who assert confidently that massive speculative attacks on currencies like the British pound in 1992, the Mexican peso in 1994–1995, and the Thai baht in 1997 prove that we are in a new world in which computerized trading, satellite hookups, and all that, mean that old economic rules, and conventional economic theory, no longer apply. (One physicist insisted that the economy has “gone nonlinear,” and is now governed by chaos theory.) But the truth is that currency crises are old hat; the travails of the French franc in the twenties were thoroughly modern, and the speculative attacks that brought down the Bretton Woods system of exchange rates in the early seventies were almost as big compared with the size of the economies involved as the biggest recent blowouts.


pages: 586 words: 159,901

Wall Street: How It Works And for Whom by Doug Henwood

accounting loophole / creative accounting, activist fund / activist shareholder / activist investor, affirmative action, Andrei Shleifer, asset allocation, asset-backed security, bank run, banking crisis, barriers to entry, borderless world, Bretton Woods, British Empire, business cycle, capital asset pricing model, capital controls, central bank independence, computerized trading, corporate governance, corporate raider, correlation coefficient, correlation does not imply causation, credit crunch, currency manipulation / currency intervention, David Ricardo: comparative advantage, debt deflation, declining real wages, deindustrialization, dematerialisation, diversification, diversified portfolio, Donald Trump, equity premium, Eugene Fama: efficient market hypothesis, experimental subject, facts on the ground, financial deregulation, financial innovation, Financial Instability Hypothesis, floating exchange rates, full employment, George Akerlof, George Gilder, hiring and firing, Hyman Minsky, implied volatility, index arbitrage, index fund, information asymmetry, interest rate swap, Internet Archive, invisible hand, Irwin Jacobs, Isaac Newton, joint-stock company, Joseph Schumpeter, kremlinology, labor-force participation, late capitalism, law of one price, liberal capitalism, liquidationism / Banker’s doctrine / the Treasury view, London Interbank Offered Rate, Louis Bachelier, market bubble, Mexican peso crisis / tequila crisis, microcredit, minimum wage unemployment, money market fund, moral hazard, mortgage debt, mortgage tax deduction, Myron Scholes, oil shock, Paul Samuelson, payday loans, pension reform, plutocrats, Plutocrats, price mechanism, price stability, prisoner's dilemma, profit maximization, publication bias, Ralph Nader, random walk, reserve currency, Richard Thaler, risk tolerance, Robert Gordon, Robert Shiller, Robert Shiller, selection bias, shareholder value, short selling, Slavoj Žižek, South Sea Bubble, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, The Market for Lemons, The Nature of the Firm, The Predators' Ball, The Wealth of Nations by Adam Smith, transaction costs, transcontinental railway, women in the workforce, yield curve, zero-coupon bond

But it displays an understanding of finance apparently derived from capital's own publicists, like George Gilder, who celebrate the obsolescence of matter and the transcendence of all the old hostile relations of production. Cybertopians and other immaterialists are lost in a second- or even third-order fetishism, unable to decode the relations of power behind the disembodied ecstasies of computerized trading. And, on the other hand, lefties of all sorts — liberal, populist, and socialist — who haven't succumbed to vulgar postmodernism have continued the long tradition of beating up on finance, denouncing it as a stinkpot of parasitism, irrelevance, malignancy, and corruption, without providing much detail beyond that. Many critics denounce "speculation" as a waste of social resources, without making any connections between it and the supposedly more fundamental world of "production."

On the second page of his article, Shiller charted the value of stock prices against the WALL STREET "true" value a perfectly rational market should have been assigning stocks based on how dividends actually turned out (a highly defensible use of 20/20 hindsight) from 1871-1979"" The line representing dividends is remarkably stable, even through the Great Depression, but the line representing stock prices zigs and zags wildly, remaining at extremes of over-and under-valuation for years, even decades. Another perspective on the market's labile temperament is the "volatility paradox," the enormous variations in volatility in stock prices (Shiller 1988; Schwert 1989). This volatility bears no statistical relation to the volatility of real-world phenomena like inflation, money growth, industrial production, interest rates, or business failures.^^ Moreover, despite the advent of computerized trading techniques such as portfolio insurance and index arbitrage during the 1980s, day-to-day volatility during that decade was little different from that of the 1970s, though both decades were more volatile than the 1950s and 1960s (Davis and White 1987). Schwert's data report stock volatility to have been low during times of great economic distress, like wars or the extended depression of the late 19th century, suggesting that in times of real social stress, people have more important things to worry about than their portfolios.


pages: 598 words: 169,194

Bernie Madoff, the Wizard of Lies: Inside the Infamous $65 Billion Swindle by Diana B. Henriques

accounting loophole / creative accounting, airport security, Albert Einstein, banking crisis, Bernie Madoff, break the buck, British Empire, buy and hold, centralized clearinghouse, collapse of Lehman Brothers, computerized trading, corporate raider, diversified portfolio, Donald Trump, dumpster diving, Edward Thorp, financial deregulation, financial thriller, fixed income, forensic accounting, Gordon Gekko, index fund, locking in a profit, mail merge, merger arbitrage, money market fund, plutocrats, Plutocrats, Ponzi scheme, Potemkin village, random walk, Renaissance Technologies, riskless arbitrage, Ronald Reagan, short selling, Small Order Execution System, source of truth, sovereign wealth fund, too big to fail, transaction costs, traveling salesman

Young accountants and MBA graduates were hired. They set up elaborate charts that assessed fund performance against various benchmarks. They developed a formal checklist of questions to ask about a money manager’s operations—questions they put to Bernie Madoff when they tagged along on Tucker’s visits. Madoff or DiPascali would answer some of the questions, show them the fake records, perhaps even do a little phoney computerized trading in their account as they watched, and then show them the bogus clearinghouse statements that backed up what they had been told. Some questions Madoff simply refused to answer. In hindsight, his intransigence may seem like a blatant red flag, but at the time, given Madoff’s status in the financial industry and apparent success on Wall Street, it was all too convincing. The young due-diligence staffers apparently did not raise any concerns with the partners.

His firm’s trading desk handled hundreds of thousands of transactions a day from the nation’s biggest mutual fund companies, online brokers, and Wall Street trading desks. It seemed perfectly plausible that Madoff could step into that order flow, trading for his private clients ahead of market-moving orders to lock in foolproof profits. The SEC did not seem to realize that the split-second computerized trading networks Madoff had helped to create had made the illicit practice much harder to carry off. And since front-running was a crime that Madoff’s sons and brother were absolutely certain he was not committing, at least not on their trading desk, the regulators’ fixation was actually reassuring to those who thought they knew Bernie best. To the SEC staffer supervising Ostrow and Lamore in this 2005 exam, however, front-running was the major focus of this exercise.


pages: 224 words: 13,238

Electronic and Algorithmic Trading Technology: The Complete Guide by Kendall Kim

algorithmic trading, automated trading system, backtesting, commoditize, computerized trading, corporate governance, Credit Default Swap, diversification, en.wikipedia.org, family office, financial innovation, fixed income, index arbitrage, index fund, interest rate swap, linked data, market fragmentation, money market fund, natural language processing, quantitative trading / quantitative finance, random walk, risk tolerance, risk-adjusted returns, short selling, statistical arbitrage, Steven Levy, transaction costs, yield curve

The traditional clerks running across the trading floor with order slips and men in pits negotiating bid prices may soon be replaced by the sound of traders typing in their parameters onto their broker screens to facilitate order flow using programs and algorithms. In the past, there were limited opportunities to apply technology to the trading process or interact directly with exchanges and market participants. This has all changed with 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 the parameters behind implementing them, but computers may calculate algorithms that route the order flow efficiently and in many cases, computers help the breakdown of trades to each individual stock within the program. 1.2 The Emergence of Electronic Trading Networks Algorithmic trading has become another method for large brokerage firms to grasp an advantage over their competitors for lower-cost executions; however, smaller players such as agency brokers also see algorithms as a way to level the playing field and infringe on the bigger bulge-bracket firms.


pages: 1,164 words: 309,327

Trading and Exchanges: Market Microstructure for Practitioners by Larry Harris

active measures, Andrei Shleifer, asset allocation, automated trading system, barriers to entry, Bernie Madoff, business cycle, buttonwood tree, buy and hold, compound rate of return, computerized trading, corporate governance, correlation coefficient, data acquisition, diversified portfolio, fault tolerance, financial innovation, financial intermediation, fixed income, floating exchange rates, High speed trading, index arbitrage, index fund, information asymmetry, information retrieval, interest rate swap, invention of the telegraph, job automation, law of one price, London Interbank Offered Rate, Long Term Capital Management, margin call, market bubble, market clearing, market design, market fragmentation, market friction, market microstructure, money market fund, Myron Scholes, Nick Leeson, open economy, passive investing, pattern recognition, Ponzi scheme, post-materialism, price discovery process, price discrimination, principal–agent problem, profit motive, race to the bottom, random walk, rent-seeking, risk tolerance, risk-adjusted returns, selection bias, shareholder value, short selling, Small Order Execution System, speech recognition, statistical arbitrage, statistical model, survivorship bias, the market place, transaction costs, two-sided market, winner-take-all economy, yield curve, zero-coupon bond, zero-sum game

During development, traders in Australia were concerned that they would have slower access than traders who were close to Chicago. The system designers therefore designed the system to 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 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 may be less than a millisecond, speedy connections are essential to trading successfully. Although the GLOBEX communications network is extremely fast, traders for whom reaction time is of the essence undoubtedly place their computers in Chicago. ◀ * * * Costs Several vendors sell fully automated exchange trading systems off the shelf.

If they expose their orders, they may scare away traders who might otherwise supply liquidity to them, and other traders may front-run them. Large traders therefore prefer market structures that allow them to find traders willing to trade while minimizing the information they must 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 matches they have arranged. ◀ * * * Large traders also prefer markets that enforce strict time precedence rules in conjunction with an economically significant minimum price increment. These rules protect them from quote-matching front runners when they expose their orders.


pages: 302 words: 86,614

The Alpha Masters: Unlocking the Genius of the World's Top Hedge Funds by Maneet Ahuja, Myron Scholes, Mohamed El-Erian

activist fund / activist shareholder / activist investor, Asian financial crisis, asset allocation, asset-backed security, backtesting, Bernie Madoff, Bretton Woods, business process, call centre, collapse of Lehman Brothers, collateralized debt obligation, computerized trading, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, Donald Trump, en.wikipedia.org, family office, fixed income, high net worth, interest rate derivative, Isaac Newton, Long Term Capital Management, Marc Andreessen, Mark Zuckerberg, merger arbitrage, Myron Scholes, NetJets, oil shock, pattern recognition, Ponzi scheme, quantitative easing, quantitative trading / quantitative finance, Renaissance Technologies, risk-adjusted returns, risk/return, rolodex, short selling, Silicon Valley, South Sea Bubble, statistical model, Steve Jobs, systematic trading, zero-sum game

At any given time, a lot of them are going to be wrong, and we have to accept that. But in the long run, we’ll be more right than wrong.” Evidently—since 1990, AHL’s total returns have exceeded 1,000 percent. Still, AHL is hardly invulnerable. The financial crisis brought on a sharp reversal, and the firm remains vulnerable to the Fed-induced drop in market volatility. In response, says Wong, the company has developed “a number of computerized trading models designed to respond better in the current macro environment.” The fund’s 15 percent rebound last year substantiates this view, and Wong anticipates further growth” beyond its 2010 size of $22.6 billion. “I think that it is quite important to really understand the risk of your business and not overreact,” says Wong. “Quite a lot of people have gone out of business because either they couldn’t explain to the investors why the market behaves as it does or they fundamentally change what they do, and then cannot recover and make back the losses.


pages: 291 words: 81,703

Average Is Over: Powering America Beyond the Age of the Great Stagnation by Tyler Cowen

Amazon Mechanical Turk, Black Swan, brain emulation, Brownian motion, business cycle, Cass Sunstein, choice architecture, complexity theory, computer age, computer vision, computerized trading, cosmological constant, crowdsourcing, dark matter, David Brooks, David Ricardo: comparative advantage, deliberate practice, Drosophila, en.wikipedia.org, endowment effect, epigenetics, Erik Brynjolfsson, eurozone crisis, experimental economics, Flynn Effect, Freestyle chess, full employment, future of work, game design, income inequality, industrial robot, informal economy, Isaac Newton, Johannes Kepler, John Markoff, Khan Academy, labor-force participation, Loebner Prize, low skilled workers, manufacturing employment, Mark Zuckerberg, meta analysis, meta-analysis, microcredit, Myron Scholes, Narrative Science, Netflix Prize, Nicholas Carr, P = NP, pattern recognition, Peter Thiel, randomized controlled trial, Ray Kurzweil, reshoring, Richard Florida, Richard Thaler, Ronald Reagan, Silicon Valley, Skype, statistical model, stem cell, Steve Jobs, Turing test, Tyler Cowen: Great Stagnation, upwardly mobile, Yogi Berra

This reflects how many of the very highest earners come from internet companies and finance, with some government and law thrown into the mix. There has been Steve Jobs, Mark Zuckerberg, and Bill Gates, but finance is a common source of riches within the very highest tier of earners. To give one extreme but illuminating example, in 2007 the top twenty-five hedge fund earners pulled in more income than all the CEOs of the S&P 500 put together. The modern financial sector has computers, computerized trading, arbitrage, super-rapid communications, and computerized risk assessment at its core. But don’t just focus on those computers; it’s also about management. The CEOs and higher-level managers are paid handsomely to assemble and direct the individuals who work every day with mechanized intelligent analysis. If you have an unusual ability to spot, recruit, and direct those who work well with computers, even if you don’t work well with computers yourself, the contemporary world will make you rich.


pages: 310 words: 85,995

The Future of Capitalism: Facing the New Anxieties by Paul Collier

"Robert Solow", accounting loophole / creative accounting, Airbnb, assortative mating, bank run, Berlin Wall, Bernie Sanders, bitcoin, Bob Geldof, bonus culture, business cycle, call centre, central bank independence, centre right, Commodity Super-Cycle, computerized trading, corporate governance, creative destruction, cuban missile crisis, David Brooks, delayed gratification, deskilling, Donald Trump, eurozone crisis, financial deregulation, full employment, George Akerlof, Goldman Sachs: Vampire Squid, greed is good, income inequality, industrial cluster, information asymmetry, intangible asset, Jean Tirole, job satisfaction, Joseph Schumpeter, knowledge economy, late capitalism, loss aversion, Mark Zuckerberg, minimum wage unemployment, moral hazard, negative equity, New Urbanism, Northern Rock, offshore financial centre, out of africa, Peace of Westphalia, principal–agent problem, race to the bottom, rent control, rent-seeking, rising living standards, Robert Shiller, Robert Shiller, Ronald Reagan, shareholder value, Silicon Valley, Silicon Valley ideology, sovereign wealth fund, The Wealth of Nations by Adam Smith, theory of mind, too big to fail, trade liberalization, urban planning, web of trust, zero-sum game

The winners are those with the exceptional abilities and resources to outsmart others; as a result, they earn staggering amounts of money. Given the potential benefits of gaining an informational advantage, there is constant pressure to get access to information. A company invested in a high-speed cable between Chicago and New York that skims milliseconds off the transmission of price information between the two markets.20 The commercial return on the investment depended upon this generating a tiny advantage in computerized trading, so that it could be sold to a few companies that would exploit it at the expense of those that received the same information milliseconds later. A society in which investment in such a cable is undertaken while bridges are left to collapse due to lack of maintenance has not got its priorities right. Excess asset transactions inflict several social costs beyond their damage to the horizon of firms, discussed in Chapter 4.


pages: 308 words: 84,713

The Glass Cage: Automation and Us by Nicholas Carr

Airbnb, Airbus A320, Andy Kessler, Atul Gawande, autonomous vehicles, Bernard Ziegler, business process, call centre, Captain Sullenberger Hudson, Charles Lindbergh, Checklist Manifesto, cloud computing, computerized trading, David Brooks, deliberate practice, deskilling, digital map, Douglas Engelbart, drone strike, Elon Musk, Erik Brynjolfsson, Flash crash, Frank Gehry, Frank Levy and Richard Murnane: The New Division of Labor, Frederick Winslow Taylor, future of work, global supply chain, Google Glasses, Google Hangouts, High speed trading, indoor plumbing, industrial robot, Internet of things, Jacquard loom, James Watt: steam engine, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Kevin Kelly, knowledge worker, Lyft, Marc Andreessen, Mark Zuckerberg, means of production, natural language processing, new economy, Nicholas Carr, Norbert Wiener, Oculus Rift, pattern recognition, Peter Thiel, place-making, plutocrats, Plutocrats, profit motive, Ralph Waldo Emerson, RAND corporation, randomized controlled trial, Ray Kurzweil, recommendation engine, robot derives from the Czech word robota Czech, meaning slave, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley ideology, software is eating the world, Stephen Hawking, Steve Jobs, TaskRabbit, technoutopianism, The Wealth of Nations by Adam Smith, turn-by-turn navigation, US Airways Flight 1549, Watson beat the top human players on Jeopardy!, William Langewiesche

By diminishing the intensity of their thinking, the software retards their ability to encode information in memory, which makes them less likely to develop the rich tacit knowledge essential to true expertise.19 The drawbacks to automated decision aids 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 suggested, “robotic methods” of decision making led to a widespread “judgment deficit” among bankers and other Wall Street professionals.20 While it may be impossible to pin down the precise degree to which automation figured in the disaster, or in subsequent fiascos like the 2010 “flash crash” on U.S. exchanges, it seems prudent to take seriously any indication that a widely used technology may be diminishing the knowledge or clouding the judgment of people in sensitive jobs.


To Pixar and Beyond by Lawrence Levy

computerized trading, index card, Loma Prieta earthquake, risk tolerance, Sand Hill Road, Silicon Valley, Silicon Valley startup, spice trade, Steve Jobs, Wall-E

Excluding the four Disney blockbusters, the average opening weekend for animated feature films during the past five years was under $3 million. No matter how we measured it, we were reaching for the sky. The second number that would define Pixar’s future was the price at which Pixar’s stock would start trading as a public company. The moment Pixar went public, its stock would begin to trade on the NASDAQ stock exchange—a computerized trading system on which most Silicon Valley IPOs were launched. Of all the issues in Pixar’s public offering, there were none that occupied Steve’s thinking more than what Pixar’s stock would sell for when it first went public. The first stock price was the price at which Pixar sold stock to investors. We were planning on selling roughly six million shares of stock. If the stock price was $10, we would raise $60 million.


Griftopia: Bubble Machines, Vampire Squids, and the Long Con That Is Breaking America by Matt Taibbi

addicted to oil, affirmative action, Affordable Care Act / Obamacare, Bernie Sanders, Bretton Woods, buy and hold, carried interest, clean water, collateralized debt obligation, collective bargaining, computerized trading, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, David Brooks, desegregation, diversification, diversified portfolio, Donald Trump, financial innovation, Goldman Sachs: Vampire Squid, Gordon Gekko, greed is good, illegal immigration, interest rate swap, laissez-faire capitalism, London Interbank Offered Rate, Long Term Capital Management, margin call, market bubble, medical malpractice, money market fund, moral hazard, mortgage debt, obamacare, passive investing, Ponzi scheme, prediction markets, quantitative easing, reserve currency, Ronald Reagan, Sergey Aleynikov, short selling, sovereign wealth fund, too big to fail, trickle-down economics, Y2K, Yom Kippur War

The NYSE memo reads: The purpose of this Information Memo is to advise all member organizations that the New York Stock Exchange LLC (“NYSE”) will be decommissioning the requirement to report program trading activity via the Daily Program Trading Report (“DPTR”), which was previously approved by the Securities and Exchange Commission (the “Commission”). The Zero Hedge war on Goldman became legend when his seemingly far-fetched conspiracy theories came sensationally true that summer. That’s when a Russian Goldman employee named Sergey Aleynikov was alleged to have stolen the bank’s computerized trading code. Aleynikov worked at precisely the desk Zero Hedge had accused of being involved in large-scale manipulations. And indeed, in a court proceeding after Aleynikov’s arrest, Assistant U.S. Attorney Joseph Facciponti reported that “the bank has raised the possibility that there is a danger that somebody who knew how to use this program could use it to manipulate markets in unfair ways.”


pages: 324 words: 92,805

The Impulse Society: America in the Age of Instant Gratification by Paul Roberts

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, accounting loophole / creative accounting, activist fund / activist shareholder / activist investor, Affordable Care Act / Obamacare, American Society of Civil Engineers: Report Card, asset allocation, business cycle, business process, Cass Sunstein, centre right, choice architecture, collateralized debt obligation, collective bargaining, computerized trading, corporate governance, corporate raider, corporate social responsibility, creative destruction, crony capitalism, David Brooks, delayed gratification, disruptive innovation, double helix, factory automation, financial deregulation, financial innovation, fixed income, full employment, game design, greed is good, If something cannot go on forever, it will stop - Herbert Stein's Law, impulse control, income inequality, inflation targeting, invisible hand, job automation, John Markoff, Joseph Schumpeter, knowledge worker, late fees, Long Term Capital Management, loss aversion, low skilled workers, mass immigration, new economy, Nicholas Carr, obamacare, Occupy movement, oil shale / tar sands, performance metric, postindustrial economy, profit maximization, Report Card for America’s Infrastructure, reshoring, Richard Thaler, rising living standards, Robert Shiller, Robert Shiller, Rodney Brooks, Ronald Reagan, shareholder value, Silicon Valley, speech recognition, Steve Jobs, technoutopianism, the built environment, The Predators' Ball, the scientific method, The Wealth of Nations by Adam Smith, Thorstein Veblen, too big to fail, total factor productivity, Tyler Cowen: Great Stagnation, Walter Mischel, winner-take-all economy

In the context of the Impulse Society, however, the more immediate effect of this cheap computing power was an acceleration in the realignment of the business world with the will of the shareholder. Wall Street would now become an even more ruthless enforcer of corporate efficiency. With computers and computer-aided data lines, brokers and investment bankers could monitor company performance in near-real time, analyze company data rapidly, and then, thanks to computerized trading, act on that data almost instantly. By the 1980s a company reporting unsatisfactory quarterly earnings might see its stock price fall within minutes, and soon, seconds. But computers also allowed companies to exploit more quickly the profit-making opportunities that Wall Street was demanding. With computer-assisted design and manufacturing, for example, companies could get a new product to market, and a return to investors, much more quickly.


pages: 297 words: 91,141

Market Sense and Nonsense by Jack D. Schwager

3Com Palm IPO, asset allocation, Bernie Madoff, Brownian motion, buy and hold, collateralized debt obligation, commodity trading advisor, computerized trading, conceptual framework, correlation coefficient, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, diversified portfolio, fixed income, high net worth, implied volatility, index arbitrage, index fund, London Interbank Offered Rate, Long Term Capital Management, margin call, market bubble, market fundamentalism, merger arbitrage, negative equity, pattern recognition, performance metric, pets.com, Ponzi scheme, quantitative trading / quantitative finance, random walk, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Shiller, selection bias, Sharpe ratio, short selling, statistical arbitrage, statistical model, survivorship bias, transaction costs, two-sided market, value at risk, yield curve

The key point is simply that the influence of emotions can lead to price behavior that is inconsistent with the efficient market hypothesis model. 17Although a segment of trading is run by computerized programs, this consideration does not alter the fact that a large portion of trading activity will reflect human decision making. Moreover, computerized programs are still subject to revisions and override, and thus even computerized trading can reflect human emotions. A classic example of this phenomenon was the meltdown of statistical arbitrage funds in August 2007. Statistical arbitrage is a market neutral, mean reversion strategy that uses mathematical models to identify short-term anomalies in stock movements, balancing sales of stocks witnessing upside deviations (as defined by its models) with purchases of stocks witnessing downside deviations.


pages: 348 words: 97,277

The Truth Machine: The Blockchain and the Future of Everything by Paul Vigna, Michael J. Casey

3D printing, additive manufacturing, Airbnb, altcoin, Amazon Web Services, barriers to entry, basic income, Berlin Wall, Bernie Madoff, bitcoin, blockchain, blood diamonds, Blythe Masters, business process, buy and hold, carbon footprint, cashless society, cloud computing, computer age, computerized trading, conceptual framework, Credit Default Swap, crowdsourcing, cryptocurrency, cyber-physical system, dematerialisation, disintermediation, distributed ledger, Donald Trump, double entry bookkeeping, Edward Snowden, Elon Musk, Ethereum, ethereum blockchain, failed state, fault tolerance, fiat currency, financial innovation, financial intermediation, global supply chain, Hernando de Soto, hive mind, informal economy, intangible asset, Internet of things, Joi Ito, Kickstarter, linked data, litecoin, longitudinal study, Lyft, M-Pesa, Marc Andreessen, market clearing, mobile money, money: store of value / unit of account / medium of exchange, Network effects, off grid, pets.com, prediction markets, pre–internet, price mechanism, profit maximization, profit motive, ransomware, rent-seeking, RFID, ride hailing / ride sharing, Ross Ulbricht, Satoshi Nakamoto, self-driving car, sharing economy, Silicon Valley, smart contracts, smart meter, Snapchat, social web, software is eating the world, supply-chain management, Ted Nelson, the market place, too big to fail, trade route, transaction costs, Travis Kalanick, Turing complete, Uber and Lyft, uber lyft, unbanked and underbanked, underbanked, universal basic income, web of trust, zero-sum game

He raised $5 million, partially with tokens, to launch a startup called Lykke, whose mission, he says, is to “build a matching engine that can offer a fair market price across any digital coin, whatever its nature.” Confident that the scaling problems of blockchains will be resolved one way or another, he is convinced that open data and middleman-free blockchain-based asset markets will trend toward zero transaction costs for cross-trading in all securitized digital assets. He plans to deploy into that efficient market setting a network of high-speed, computerized trading machines. Much like Wall Street bond traders, these will “make markets” to bring financial liquidity to every countervailing pair of tokens—buying some here and selling others there—so that if anyone wants to trade 100 BATs for a third of a Jackson Pollock, they can be assured of a reasonable market price. Our financial reporter minds, overly exposed to the sneaky ways Wall Street banks obscure prices to exploit investors, struggle to envisage how anything so complicated could be cost-effective.


pages: 372 words: 107,587

The End of Growth: Adapting to Our New Economic Reality by Richard Heinberg

3D printing, agricultural Revolution, back-to-the-land, banking crisis, banks create money, Bretton Woods, business cycle, carbon footprint, Carmen Reinhart, clean water, cloud computing, collateralized debt obligation, computerized trading, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, currency peg, David Graeber, David Ricardo: comparative advantage, dematerialisation, demographic dividend, Deng Xiaoping, Elliott wave, en.wikipedia.org, energy transition, falling living standards, financial deregulation, financial innovation, Fractional reserve banking, full employment, Gini coefficient, global village, happiness index / gross national happiness, I think there is a world market for maybe five computers, income inequality, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Isaac Newton, Kenneth Rogoff, late fees, liberal capitalism, mega-rich, money market fund, money: store of value / unit of account / medium of exchange, mortgage debt, naked short selling, Naomi Klein, Negawatt, new economy, Nixon shock, offshore financial centre, oil shale / tar sands, oil shock, peak oil, Ponzi scheme, price stability, private military company, quantitative easing, reserve currency, ride hailing / ride sharing, Ronald Reagan, short selling, special drawing rights, The Wealth of Nations by Adam Smith, Thomas Malthus, Thorstein Veblen, too big to fail, trade liberalization, tulip mania, WikiLeaks, working poor, zero-sum game

Land equity partnerships and land trusts (including agricultural land trusts) are other proven ways to overcome the landlord-tenant dilemma and remove land from the speculative market.50 Futurist Hazel Henderson, author of Ethical Markets: Growing the Green Economy, advises governments to charge a financial transaction tax of one percent or less.51 This would not affect the trades of 99.9 percent of all Americans. But it would put a major crimp in the games that the big boys play. Let the quants use their brainpower to cure cancer rather than to craft complex computerized trading systems that leave society with less than nothing. A small transaction tax could generate over a $100 billion a year from Wall Street — and in the process, bring those ridiculous bonuses and profits back in line with the real economy.52 Henderson also advocates breaking up too-big-to-fail banks and businesses and fostering non-profit community development finance institutions (CDFIs) to address the capital needs of micro-businesses.


pages: 311 words: 17,232

Living in a Material World: The Commodity Connection by Kevin Morrison

addicted to oil, barriers to entry, Berlin Wall, carbon footprint, clean water, commoditize, commodity trading advisor, computerized trading, diversified portfolio, Doha Development Round, Elon Musk, energy security, European colonialism, flex fuel, food miles, Hernando de Soto, Hugh Fearnley-Whittingstall, hydrogen economy, Intergovernmental Panel on Climate Change (IPCC), Kickstarter, Long Term Capital Management, new economy, North Sea oil, oil rush, oil shale / tar sands, oil shock, out of africa, Paul Samuelson, peak oil, price mechanism, Ronald Coase, Ronald Reagan, Silicon Valley, sovereign wealth fund, the payments system, The Wealth of Nations by Adam Smith, trade liberalization, transaction costs, uranium enrichment, young professional

‘It was more like the present day hedge funds, as it went long and short and in the beginning it was focused on commodities futures as it was before interest rate or financial futures were launched,’ said Samuelson, who is credited with the famous quip ‘The stock market has predicted nine out of the last five recessions.’ Commodities Corporation was, in effect, one of the first commodity-focused hedge funds. Its successes were underlined further when another of its traders – Ed Seykota – developed one of the first computerized trading systems for managing clients’ money in futures markets (Schwager, 1993). The success of the company was to spot a good trader who could manage ‘leverage’; i.e. the amount of money a fund can borrow to fund its trade. The difference between then and now, adds Samuelson, is that there are a lot more smart people today. ‘I would say 30 years ago, there were not many very smart kids on the block, now there are quite a lot.


pages: 419 words: 109,241

A World Without Work: Technology, Automation, and How We Should Respond by Daniel Susskind

3D printing, agricultural Revolution, AI winter, Airbnb, Albert Einstein, algorithmic trading, artificial general intelligence, autonomous vehicles, basic income, Bertrand Russell: In Praise of Idleness, blue-collar work, British Empire, Capital in the Twenty-First Century by Thomas Piketty, cloud computing, computer age, computer vision, computerized trading, creative destruction, David Graeber, David Ricardo: comparative advantage, demographic transition, deskilling, disruptive innovation, Donald Trump, Douglas Hofstadter, drone strike, Edward Glaeser, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, financial innovation, future of work, gig economy, Gini coefficient, Google Glasses, Gödel, Escher, Bach, income inequality, income per capita, industrial robot, interchangeable parts, invisible hand, Isaac Newton, Jacques de Vaucanson, James Hargreaves, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, John von Neumann, Joi Ito, Joseph Schumpeter, Kenneth Arrow, Khan Academy, Kickstarter, low skilled workers, lump of labour, Marc Andreessen, Mark Zuckerberg, means of production, Metcalfe’s law, natural language processing, Network effects, Occupy movement, offshore financial centre, Paul Samuelson, Peter Thiel, pink-collar, precariat, purchasing power parity, Ray Kurzweil, ride hailing / ride sharing, road to serfdom, Robert Gordon, Sam Altman, Second Machine Age, self-driving car, shareholder value, sharing economy, Silicon Valley, Snapchat, social intelligence, software is eating the world, sovereign wealth fund, spinning jenny, Stephen Hawking, Steve Jobs, strong AI, telemarketer, The Future of Employment, The Rise and Fall of American Growth, the scientific method, The Wealth of Nations by Adam Smith, Thorstein Veblen, Travis Kalanick, Turing test, Tyler Cowen: Great Stagnation, universal basic income, upwardly mobile, Watson beat the top human players on Jeopardy!, We are the 99%, wealth creators, working poor, working-age population, Y Combinator

These tailor instruction—the content, the approach, and the pace—to the particular needs of each student, in an effort to replicate the one-to-one personal tuition that is provided at a place like Oxford but unaffordable in most other settings. More than seventy companies are developing these systems, and 97 percent of US school districts have invested in them in some form.47 The list goes on and on. In finance, computerized trading is now widespread, responsible for about half of all trades on the stock market.48 In insurance, a Japanese firm called Fukoku Mutual Life Insurance has started using an AI system to calculate policyholder payouts, replacing thirty-four staff in the process.49 In botany, an algorithm trained on more than 250,000 scans of dried plants was able to identity species in new scans with almost 80 percent accuracy; one paleobotanist, reviewing the results, thought the system “probably out-performs a human taxonomist by quite a bit.”50 In journalism, the Associated Press has begun to use algorithms to compose their sports coverage and earnings reports, now producing about fifteen times as many of the latter as when they relied upon human writers alone.


Capital Ideas Evolving by Peter L. Bernstein

Albert Einstein, algorithmic trading, Andrei Shleifer, asset allocation, business cycle, buy and hold, buy low sell high, capital asset pricing model, commodity trading advisor, computerized trading, creative destruction, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, diversification, diversified portfolio, endowment effect, equity premium, Eugene Fama: efficient market hypothesis, financial innovation, fixed income, high net worth, hiring and firing, index fund, invisible hand, Isaac Newton, John Meriwether, John von Neumann, Joseph Schumpeter, Kenneth Arrow, London Interbank Offered Rate, Long Term Capital Management, loss aversion, Louis Bachelier, market bubble, mental accounting, money market fund, Myron Scholes, paper trading, passive investing, Paul Samuelson, price anchoring, price stability, random walk, Richard Thaler, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Robert Shiller, Sharpe ratio, short selling, Silicon Valley, South Sea Bubble, statistical model, survivorship bias, systematic trading, technology bubble, The Wealth of Nations by Adam Smith, transaction costs, yield curve, Yogi Berra, zero-sum game

A college endowment and an employee with a 401(k) plan are different investors. Since Capital Ideas appeared in 1992, the institutional structure of financial markets has gone through a fundamental transformation. Investors in the early 1990s had not even a glimmer of today’s f lood of information by means of the computer and the Internet; the instruments bern_c04.qxd 3/23/07 9:02 AM Page 49 Robert C. Merton 49 being traded; the reality of computerized trading in place of exchange f loors; the management of the stock exchanges themselves; the global interlocks; the size, sophistication, and orientation of the larger investors; the proliferation of money market funds, mutual funds, and hedge funds; the development of risk-sharing instruments blurring distinction between the commercial banks or insurance companies and the capital markets; or the transformation of pension funding from defined-benefit to defined-contribution.


pages: 289 words: 113,211

A Demon of Our Own Design: Markets, Hedge Funds, and the Perils of Financial Innovation by Richard Bookstaber

"Robert Solow", affirmative action, Albert Einstein, asset allocation, backtesting, beat the dealer, Black Swan, Black-Scholes formula, Bonfire of the Vanities, butterfly effect, commoditize, commodity trading advisor, computer age, computerized trading, disintermediation, diversification, double entry bookkeeping, Edward Lorenz: Chaos theory, Edward Thorp, family office, financial innovation, fixed income, frictionless, frictionless market, George Akerlof, implied volatility, index arbitrage, intangible asset, Jeff Bezos, John Meriwether, London Interbank Offered Rate, Long Term Capital Management, loose coupling, margin call, market bubble, market design, merger arbitrage, Mexican peso crisis / tequila crisis, moral hazard, Myron Scholes, new economy, Nick Leeson, oil shock, Paul Samuelson, Pierre-Simon Laplace, quantitative trading / quantitative finance, random walk, Renaissance Technologies, risk tolerance, risk/return, Robert Shiller, Robert Shiller, rolodex, Saturday Night Live, selection bias, shareholder value, short selling, Silicon Valley, statistical arbitrage, The Market for Lemons, time value of money, too big to fail, transaction costs, tulip mania, uranium enrichment, William Langewiesche, yield curve, zero-coupon bond, zero-sum game

Though Morgan Stanley management killed the stat arb golden goose, it revived the approach in 1992 when the equity division hired a young Princeton graduate, Peter Muller, to build a stat arb system. He started from scratch, plugging away on the SAS statistics package to build his approach. Peter’s first months of trading at Morgan Stanley were rocky; he was one month from being shut down, but then he hit his stride, beginning a streak of years of profits with nary a month of down performance. The computerized trading pulled in hundreds of millions a year for the firm and tens of millions for Muller, and the system was sufficiently automated that he could leave the day-to-day administration to his staff while he indulged in his other interests—performing his songs at New York clubs and kayaking in Ecuador—before finally retiring from the firm in 2001. Besides the use of pure mean reversion between pairs, Muller and other stat arb traders exploited another market characteristic: leads and lags in the price changes of stocks within the same sector.


pages: 464 words: 117,495

The New Trading for a Living: Psychology, Discipline, Trading Tools and Systems, Risk Control, Trade Management by Alexander Elder

additive manufacturing, Atul Gawande, backtesting, Benoit Mandelbrot, buy and hold, buy low sell high, Checklist Manifesto, computerized trading, deliberate practice, diversification, Elliott wave, endowment effect, loss aversion, mandelbrot fractal, margin call, offshore financial centre, paper trading, Ponzi scheme, price stability, psychological pricing, quantitative easing, random walk, risk tolerance, short selling, South Sea Bubble, systematic trading, The Wisdom of Crowds, transaction costs, transfer pricing, traveling salesman, tulip mania, zero-sum game

The Brain Myth Losers who suffer from the “brain myth” will tell you, “I lost because I didn't know trading secrets.” Many have a fantasy that successful traders have some secret knowledge. That fantasy helps support a lively market in advisory services and ready-made trading systems. A demoralized trader may whip 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 can stop losing and begin winning by contemplating the moon, the stars, or even Uranus. At an investment club we used to have in New York, I often ran into a famous financial astrologer. He often asked for free admission because he couldn't afford to pay a modest fee for the meeting and a meal.


pages: 429 words: 120,332

Treasure Islands: Uncovering the Damage of Offshore Banking and Tax Havens by Nicholas Shaxson

Asian financial crisis, asset-backed security, bank run, battle of ideas, Bernie Madoff, Big bang: deregulation of the City of London, Bretton Woods, British Empire, business climate, call centre, capital controls, collapse of Lehman Brothers, computerized trading, corporate governance, corporate social responsibility, creative destruction, Credit Default Swap, David Ricardo: comparative advantage, Double Irish / Dutch Sandwich, failed state, financial deregulation, financial innovation, Fractional reserve banking, full employment, high net worth, income inequality, Kenneth Rogoff, laissez-faire capitalism, land reform, land value tax, light touch regulation, Long Term Capital Management, Martin Wolf, money market fund, New Journalism, Northern Rock, offshore financial centre, oil shock, old-boy network, out of africa, passive income, plutocrats, Plutocrats, Ponzi scheme, race to the bottom, regulatory arbitrage, reserve currency, Ronald Reagan, shareholder value, The Spirit Level, too big to fail, transfer pricing, Washington Consensus

One enterprising trader at a major U.S. bank, recognizing how artificial this game was, planted a cardboard sign saying “Nassau” on a desk in his trading room in New York and recorded trades at that desk, booking them “offshore” and out of sight of regulators. After someone discovered the ploy the traders continued as before but ensured that a clerk simply copied them into a second set of books in the Bahamas.50 Soon, a shift to computerized trading removed the need for cardboard signs anyway. As the author Jeffrey Robinson noted, “The horse hadn’t merely bolted, it was living in a beach-front condo in the Caribbean.” The Euromarkets rippled outward, driven from the center in London, first to Britain’s semi-independent Crown Dependencies of Jersey, Guernsey, and the Isle of Man near the UK mainland, then out to the British-held Caribbean jurisdictions, then to Asia, and finally to British-held Pacific atolls.


pages: 354 words: 118,970

Transaction Man: The Rise of the Deal and the Decline of the American Dream by Nicholas Lemann

Affordable Care Act / Obamacare, Airbnb, airline deregulation, Albert Einstein, augmented reality, basic income, Bernie Sanders, Black-Scholes formula, buy and hold, capital controls, computerized trading, corporate governance, cryptocurrency, Daniel Kahneman / Amos Tversky, dematerialisation, diversified portfolio, Donald Trump, Elon Musk, Eugene Fama: efficient market hypothesis, financial deregulation, financial innovation, fixed income, future of work, George Akerlof, gig economy, Henry Ford's grandson gave labor union leader Walter Reuther a tour of the company’s new, automated factory…, index fund, information asymmetry, invisible hand, Irwin Jacobs, Joi Ito, Joseph Schumpeter, Kenneth Arrow, Kickstarter, life extension, Long Term Capital Management, Mark Zuckerberg, mass immigration, means of production, Metcalfe’s law, money market fund, Mont Pelerin Society, moral hazard, Myron Scholes, new economy, Norman Mailer, obamacare, Paul Samuelson, Peter Thiel, price mechanism, principal–agent problem, profit maximization, quantitative trading / quantitative finance, Ralph Nader, Richard Thaler, road to serfdom, Robert Bork, Robert Metcalfe, rolodex, Ronald Coase, Ronald Reagan, Sand Hill Road, shareholder value, short selling, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, Social Responsibility of Business Is to Increase Its Profits, Steve Jobs, TaskRabbit, The Nature of the Firm, the payments system, Thomas Kuhn: the structure of scientific revolutions, Thorstein Veblen, too big to fail, transaction costs, universal basic income, War on Poverty, white flight, working poor

The failure of significant financial institutions, something that had been a constant in American history before the New Deal, was almost unheard-of. In the late 1980s that began to change. On October 19, 1987, financial markets around the world plunged more in one day than they ever had before, even during the crash of 1929, at least partly because large institutional investors had adopted some of the techniques of financial economics, such as automated, computerized trading that proceeded almost instantly in response to complex calculations about the direction of the markets, without any human participation in the decisions to buy or sell. During the same period, more than a thousand savings and loans—a third of the total number in the country—failed, substantially because the deregulation of a few years earlier had permitted them to make highly risky investments that had gone sour.


pages: 415 words: 125,089

Against the Gods: The Remarkable Story of Risk by Peter L. Bernstein

"Robert Solow", Albert Einstein, Alvin Roth, Andrew Wiles, Antoine Gombaud: Chevalier de Méré, Bayesian statistics, Big bang: deregulation of the City of London, Bretton Woods, business cycle, buttonwood tree, buy and hold, capital asset pricing model, cognitive dissonance, computerized trading, Daniel Kahneman / Amos Tversky, diversified portfolio, double entry bookkeeping, Edmond Halley, Edward Lloyd's coffeehouse, endowment effect, experimental economics, fear of failure, Fellow of the Royal Society, Fermat's Last Theorem, financial deregulation, financial innovation, full employment, index fund, invention of movable type, Isaac Newton, John Nash: game theory, John von Neumann, Kenneth Arrow, linear programming, loss aversion, Louis Bachelier, mental accounting, moral hazard, Myron Scholes, Nash equilibrium, Norman Macrae, Paul Samuelson, Philip Mirowski, probability theory / Blaise Pascal / Pierre de Fermat, random walk, Richard Thaler, Robert Shiller, Robert Shiller, spectrum auction, statistical model, stocks for the long run, The Bell Curve by Richard Herrnstein and Charles Murray, The Wealth of Nations by Adam Smith, Thomas Bayes, trade route, transaction costs, tulip mania, Vanguard fund, zero-sum game

If investors are unable to outguess one another with any degree of reliability, perhaps the computer can capitalize on the market's nonrational behavior; machines are immune from such human flaws as the endowment effect, myopia, and decision regret. So far, computer mod els that instruct the investor to buy when others are frightened and to sell when others are overconfident have produced mixed or irregular results. The investors become either more frightened or more overconfident than the computer model predicts, or else their behavior is outside the patterns the computer can recognize. Yet computerized trading is a fruitful area for further research, as we shall see shortly. Human investors do turn in outstanding track records from time to time. But even if we ascribe those achievements to skill rather than luck, two problems remain. First, past performance is a frail guide to the future. In retrospect, the winners are fully visible, but we have no reliable way of identifying in advance the investors whose skills will win out in the years ahead.


pages: 349 words: 134,041

Traders, Guns & Money: Knowns and Unknowns in the Dazzling World of Derivatives by Satyajit Das

accounting loophole / creative accounting, Albert Einstein, Asian financial crisis, asset-backed security, beat the dealer, Black Swan, Black-Scholes formula, Bretton Woods, BRICs, Brownian motion, business process, buy and hold, buy low sell high, call centre, capital asset pricing model, collateralized debt obligation, commoditize, complexity theory, computerized trading, corporate governance, corporate raider, Credit Default Swap, credit default swaps / collateralized debt obligations, cuban missile crisis, currency peg, disintermediation, diversification, diversified portfolio, Edward Thorp, Eugene Fama: efficient market hypothesis, Everything should be made as simple as possible, financial innovation, fixed income, Haight Ashbury, high net worth, implied volatility, index arbitrage, index card, index fund, interest rate derivative, interest rate swap, Isaac Newton, job satisfaction, John Meriwether, locking in a profit, Long Term Capital Management, mandelbrot fractal, margin call, market bubble, Marshall McLuhan, mass affluent, mega-rich, merger arbitrage, Mexican peso crisis / tequila crisis, money market fund, moral hazard, mutually assured destruction, Myron Scholes, new economy, New Journalism, Nick Leeson, offshore financial centre, oil shock, Parkinson's law, placebo effect, Ponzi scheme, purchasing power parity, quantitative trading / quantitative finance, random walk, regulatory arbitrage, Right to Buy, risk-adjusted returns, risk/return, Satyajit Das, shareholder value, short selling, South Sea Bubble, statistical model, technology bubble, the medium is the message, the new new thing, time value of money, too big to fail, transaction costs, value at risk, Vanguard fund, volatility smile, yield curve, Yogi Berra, zero-coupon bond

Ganging up is effective – you just get together with other traders and fall upon a weakened animal like hyenas or wolves. Ambush is also good – you know something that the other guy does not know, at least not yet. Flow traders are well-versed in ambush. It also helps to be lucky – better to be a lucky fool than an unlucky genius. I was consulting to an equity house and the project focused on a new computerized trading system. A trader records the trades done in order to work out what their position is, traditionally done manually on a large piece of paper (the blotter). The proposed system had an electronic version of the blotter; trades were entered into the system, creating the blotter for each trader. Steve was not convinced: ‘I don’t need this crap.’ I entered his trades that morning onto the system to show him how it worked.


pages: 513 words: 141,153

The Spider Network: The Wild Story of a Math Genius, a Gang of Backstabbing Bankers, and One of the Greatest Scams in Financial History by David Enrich

Bernie Sanders, call centre, centralized clearinghouse, computerized trading, Credit Default Swap, Downton Abbey, Flash crash, Goldman Sachs: Vampire Squid, information asymmetry, interest rate derivative, interest rate swap, London Interbank Offered Rate, London Whale, Long Term Capital Management, Nick Leeson, Northern Rock, Occupy movement, performance metric, profit maximization, tulip mania, zero-sum game

* * * The internship ran from July to September. Hayes rented a place in London and commuted into UBS’s offices, right around the corner from the old Mullens building where his top-hatted grandfather once worked. (In fact, S. G. Warburg, which had been purchased by UBS, had itself purchased Mullens in the 1980s.) Hayes found the job boring. He worked behind the scenes, helping UBS manage its technology and computerized trading systems. At the end of the summer, the bank offered him a permanent job. It wasn’t even conditioned on Hayes graduating—that’s how much they wanted him. But in his few months at UBS, Hayes had learned about the investment banking pecking order. Back-office roles, such as the one he’d been offered, were close to the bottom. At or near the top were traders. For most people, the notion of a trader is based largely on movies depicting Wall Street’s wild ethos.


pages: 611 words: 130,419

Narrative Economics: How Stories Go Viral and Drive Major Economic Events by Robert J. Shiller

agricultural Revolution, Albert Einstein, algorithmic trading, Andrei Shleifer, autonomous vehicles, bank run, banking crisis, basic income, bitcoin, blockchain, business cycle, butterfly effect, buy and hold, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, central bank independence, collective bargaining, computerized trading, corporate raider, correlation does not imply causation, cryptocurrency, Daniel Kahneman / Amos Tversky, debt deflation, disintermediation, Donald Trump, Edmond Halley, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, full employment, George Akerlof, germ theory of disease, German hyperinflation, Gunnar Myrdal, Gödel, Escher, Bach, Hacker Ethic, implied volatility, income inequality, inflation targeting, invention of radio, invention of the telegraph, Jean Tirole, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, litecoin, market bubble, money market fund, moral hazard, Northern Rock, nudge unit, Own Your Own Home, Paul Samuelson, Philip Mirowski, plutocrats, Plutocrats, Ponzi scheme, publish or perish, random walk, Richard Thaler, Robert Shiller, Robert Shiller, Ronald Reagan, Rubik’s Cube, Satoshi Nakamoto, secular stagnation, shareholder value, Silicon Valley, speech recognition, Steve Jobs, Steven Pinker, stochastic process, stocks for the long run, superstar cities, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, theory of mind, Thorstein Veblen, traveling salesman, trickle-down economics, tulip mania, universal basic income, Watson beat the top human players on Jeopardy!, We are the 99%, yellow journalism, yield curve, Yom Kippur War

The topic still comes up regularly, often on major anniversaries of that event. We might believe that memories of that crash make stock markets vulnerable to another crash, because fear of a crash may cause people to react to the apparent beginnings of a drop in stock prices. But the narrative of the 1987 crash need not have any such effect if people do not think current circumstances are similar. In 1987, there was much discussion of a new computerized trading program called portfolio insurance. Along with other factors, narratives about portfolio insurance led to a predisposition to consider selling that was peculiar to that time.5 Other disturbing stock market events were surrounded by narratives that had nothing to do with portfolio insurance. After Austria-Hungary declared war on Serbia on July 28, 1914, touching off World War I, stock prices began to fall precipitously.


pages: 519 words: 155,332

Tailspin: The People and Forces Behind America's Fifty-Year Fall--And Those Fighting to Reverse It by Steven Brill

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, activist fund / activist shareholder / activist investor, affirmative action, Affordable Care Act / Obamacare, airport security, American Society of Civil Engineers: Report Card, asset allocation, Bernie Madoff, Bernie Sanders, Blythe Masters, Bretton Woods, business process, call centre, Capital in the Twenty-First Century by Thomas Piketty, carried interest, clean water, collapse of Lehman Brothers, collective bargaining, computerized trading, corporate governance, corporate raider, corporate social responsibility, Credit Default Swap, currency manipulation / currency intervention, Donald Trump, ending welfare as we know it, failed state, financial deregulation, financial innovation, future of work, ghettoisation, Gordon Gekko, hiring and firing, Home mortgage interest deduction, immigration reform, income inequality, invention of radio, job automation, knowledge economy, knowledge worker, labor-force participation, laissez-faire capitalism, Mahatma Gandhi, Mark Zuckerberg, mortgage tax deduction, new economy, obamacare, old-boy network, paper trading, performance metric, post-work, Potemkin village, Powell Memorandum, quantitative hedge fund, Ralph Nader, ride hailing / ride sharing, Robert Bork, Robert Gordon, Robert Mercer, Ronald Reagan, shareholder value, Silicon Valley, Social Responsibility of Business Is to Increase Its Profits, telemarketer, too big to fail, trade liberalization, union organizing, Unsafe at Any Speed, War on Poverty, women in the workforce, working poor

This raises the core question: Is a corporate board supposed to bow to the day-to-day wishes of shareholders, or should it act in what the corporation’s leaders believe is the company’s best long-term interests, or even in the best interests of all stakeholders—shareholders, employees, consumers, suppliers, and the community as a whole? That stakeholder view seems to be making a comeback. Barton and many other business leaders are increasingly taking up the cause. And with the political climate turning against the kind of short-termism that computerized trading, hedge fund raids, and buybacks have exacerbated, regulatory reforms may become possible within a few election cycles. These include disallowing favorable capital gains tax treatment on stock sold within, say, three years of its purchase; putting an extra tax on computerized split-second trading in stocks, bonds, and currencies; limiting the power of raiders and fast-trading hedge funds by giving more weight in voting to shareholders who hold stock for a stipulated length of time, such as one or two years; and once again not allowing stock buybacks—a Reagan-era deregulatory experiment that has clearly been bad for the overall economy.


pages: 568 words: 162,366

The Oil and the Glory: The Pursuit of Empire and Fortune on the Caspian Sea by Steve Levine

Berlin Wall, California gold rush, computerized trading, corporate raider, cuban missile crisis, facts on the ground, failed state, fixed income, indoor plumbing, Khyber Pass, megastructure, Menlo Park, Mikhail Gorbachev, oil rush, Potemkin village, rolodex, Ronald Reagan, shareholder value, Silicon Valley, telemarketer, trade route

On a subsequent visit, they were told that privatization would proceed after the elections in October 1998, when Aliyev would be better positioned to enact the controversial reform. Kozeny’s flashy presence in Baku impressed his visitors. He cruised the city in an armored jeep with bodyguards and spent freely in pricey restaurants. He rented two floors in an expensive office building, where he established an investment house called Minaret, complete with a computerized “trading floor,” even though Baku as yet had no stock market. His 180-person staff was well paid and treated royally at his luxury seaside dacha. In April 1998, Kozeny celebrated Minaret’s formal opening with a poolside soirée at Baku’s premier hotel, the Hyatt. George Mitchell was the marquee guest. But something seemed amiss. Not a single senior Azeri leader appeared, nor did any of Baku’s most prominent foreign residents, such as the U.S. ambassador.


pages: 553 words: 168,111

The Asylum: The Renegades Who Hijacked the World's Oil Market by Leah McGrath Goodman

anti-communist, Asian financial crisis, automated trading system, banking crisis, barriers to entry, Bernie Madoff, computerized trading, corporate governance, corporate raider, credit crunch, Credit Default Swap, East Village, energy security, Etonian, family office, Flash crash, global reserve currency, greed is good, High speed trading, light touch regulation, market fundamentalism, peak oil, Peter Thiel, pre–internet, price mechanism, profit motive, regulatory arbitrage, reserve currency, rolodex, Ronald Reagan, side project, Silicon Valley, upwardly mobile, zero-sum game

Any harm done to energy consumers in the crossfire of their trading games was blithely categorized as collateral damage. Banks and hedge funds, whose automated trading systems bought and sold millions upon millions of energy contracts in just milliseconds, followed the same credo. Computer programmers were being hailed as the new gunslingers of Wall Street, fetching breathtaking salaries. Veteran energy traders began reporting that some of the computerized trading systems were letting banks and funds trade on the screen in ways that would have been illegal in the pits. They pointed to what they called “phantom trading volume,” “fake orders,” and “quote-stuffing” that made oil prices appear to be headed one way when they were really headed another. It was a problem worth looking into, but with Washington’s track record of understanding even the most basic financial instruments, like weather futures, it seemed unlikely it would be capable of troubleshooting advanced technology possibly being repurposed for the execution of illicit, high-speed trades.


pages: 272 words: 19,172

Hedge Fund Market Wizards by Jack D. Schwager

asset-backed security, backtesting, banking crisis, barriers to entry, beat the dealer, Bernie Madoff, Black-Scholes formula, British Empire, business cycle, buy and hold, Claude Shannon: information theory, cloud computing, collateralized debt obligation, commodity trading advisor, computerized trading, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, delta neutral, diversification, diversified portfolio, Edward Thorp, family office, financial independence, fixed income, Flash crash, hindsight bias, implied volatility, index fund, intangible asset, James Dyson, Jones Act, Long Term Capital Management, margin call, market bubble, market fundamentalism, merger arbitrage, money market fund, oil shock, pattern recognition, pets.com, Ponzi scheme, private sector deleveraging, quantitative easing, quantitative trading / quantitative finance, Right to Buy, risk tolerance, risk-adjusted returns, risk/return, riskless arbitrage, Rubik’s Cube, Sharpe ratio, short selling, statistical arbitrage, Steve Jobs, systematic trading, technology bubble, transaction costs, value at risk, yield curve

If I didn’t know him in context of being the founder of QIM, I would sooner have guessed that he was in his late twenties than in his early forties. Woodriff had looked forward to our meeting and was extremely disappointed that he had come down with a bad cold a day earlier. He repeatedly apologized for what he considered his foggy thinking and imprecise recollections. “God, I wish I weren’t sick. I’m not thinking clearly,” he said.4 How did you get interested in developing computerized trading systems? When I was about 9 or 10 years old, I became interested in odds and probability. I would obsessively roll a pair of dice to see seven win, and six and eight duke it out. It just fascinated me to see the results come out over time—to see the randomness, but also the certainty with which seven would always beat six and eight. When I was 12, I read about computers. It was an article about the new Commodore, a $300 computer, which in today’s terms would be several thousand dollars.


Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals by David Aronson

Albert Einstein, Andrew Wiles, asset allocation, availability heuristic, backtesting, Black Swan, butter production in bangladesh, buy and hold, capital asset pricing model, cognitive dissonance, compound rate of return, computerized trading, Daniel Kahneman / Amos Tversky, distributed generation, Elliott wave, en.wikipedia.org, feminist movement, hindsight bias, index fund, invention of the telescope, invisible hand, Long Term Capital Management, mental accounting, meta analysis, meta-analysis, p-value, pattern recognition, Paul Samuelson, Ponzi scheme, price anchoring, price stability, quantitative trading / quantitative finance, Ralph Nelson Elliott, random walk, retrograde motion, revision control, risk tolerance, risk-adjusted returns, riskless arbitrage, Robert Shiller, Robert Shiller, Sharpe ratio, short selling, source of truth, statistical model, stocks for the long run, systematic trading, the scientific method, transfer pricing, unbiased observer, yield curve, Yogi Berra

Peters, Fractal Market Analysis: Applying Chaos Theory to Investment & Economics (New York: John Wiley & Son., 1994), 21–38. A rule selected because of its superior performance in the mined data. This figure was inspired by a similar figure in Lawrence Lapin, Statistics for Modern Business Decisions, 2nd ed. (New York: Harcourt Brace Jovanovich, 1978), Figure 6-10, 186. Pardo, Design, Testing and Optimization, 108. M. De La Maza, “Backtesting,” Chapter 8 in Computerized Trading: Maximizing Day Trading and Overnight Profit, M. Jurik (Ed.) (Paramus, NJ: Prentice-Hall, 1999). Katz and McCormick, Encyclopedia of Trading Strategies. Kaufman, New Trading Systems. P.-H. Hsu and C.-M. Kuan, “Rexamining the Profitability of Technical Analysis with Data Snooping Checks,” Journal of Financial Econometrics 3, no. 4 (2005), 606–628. H.M. Markowitz and G.L. Xu, “Data Mining Corrections: Simple and Plausible,” Journal of Portfolio Management (Fall 1994), 60–69.


pages: 612 words: 179,328

Buffett by Roger Lowenstein

asset allocation, Bretton Woods, buy and hold, cashless society, collective bargaining, computerized trading, corporate raider, credit crunch, cuban missile crisis, Eugene Fama: efficient market hypothesis, index card, index fund, interest rate derivative, invisible hand, Jeffrey Epstein, John Meriwether, Long Term Capital Management, moral hazard, Paul Samuelson, random walk, risk tolerance, Robert Shiller, Robert Shiller, Ronald Reagan, selection bias, The Predators' Ball, traveling salesman, Works Progress Administration, Yogi Berra, young professional, zero-coupon bond

So maybe the market can go up regardless of fundamentals.36 No one disputed that prices were high, but the bull market had become an article of faith. Business Week suggested that “yesterday’s yardsticks” were no longer apt.37 Buffett felt that money managers were not using any yardstick. They had abandoned the effort to value stocks at all: “For them, stocks are merely tokens in a game, like the thimble and flatiron in Monopoly.”38 With computerized trading, fund managers were now buying groups of stocks by the bucketful in market “baskets”—a few million GM, a couple of million AT&T, and a dab of Westinghouse, on rye, please. A parallel trend was the emergence of stock-index futures in the commodity pits in Chicago. These new futures contracts, which traded next to pork bellies and cattle, enabled speculators to bet on the direction of the entire stock market.


pages: 584 words: 187,436

More Money Than God: Hedge Funds and the Making of a New Elite by Sebastian Mallaby

Andrei Shleifer, Asian financial crisis, asset-backed security, automated trading system, bank run, barriers to entry, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, Big bang: deregulation of the City of London, Bonfire of the Vanities, Bretton Woods, business cycle, buy and hold, capital controls, Carmen Reinhart, collapse of Lehman Brothers, collateralized debt obligation, computerized trading, corporate raider, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, currency manipulation / currency intervention, currency peg, Elliott wave, Eugene Fama: efficient market hypothesis, failed state, Fall of the Berlin Wall, financial deregulation, financial innovation, financial intermediation, fixed income, full employment, German hyperinflation, High speed trading, index fund, John Meriwether, Kenneth Rogoff, Kickstarter, Long Term Capital Management, margin call, market bubble, market clearing, market fundamentalism, merger arbitrage, money market fund, moral hazard, Myron Scholes, natural language processing, Network effects, new economy, Nikolai Kondratiev, pattern recognition, Paul Samuelson, pre–internet, quantitative hedge fund, quantitative trading / quantitative finance, random walk, Renaissance Technologies, Richard Thaler, risk-adjusted returns, risk/return, Robert Mercer, rolodex, Sharpe ratio, short selling, Silicon Valley, South Sea Bubble, sovereign wealth fund, statistical arbitrage, statistical model, survivorship bias, technology bubble, The Great Moderation, The Myth of the Rational Market, the new new thing, too big to fail, transaction costs

A first version of his program, a trend-following system called Techno-Fundamentals, ran money successfully from the end of 1997, but the job of creating a system that would shift according to the market environment remained uncompleted. Wadhwani returned to the task when he set up his own hedge fund, Wadhwani Asset Management, in London in 2002, and meanwhile, Tudor’s program trading continued to develop. By 2008 Paul Jones’s firm had more than fifty people working on its computerized trading, and their algorithms were driving more than $3 billion of Tudor’s $17 billion capital.18 The rock-and-roller with the Bruce Willis sneakers had accomplished quite a transformation. And yet, just as with D. E. Shaw, there were limits to this achievement. The systems that Tudor created were not as original as those developed by James Simons’s team at Renaissance Technologies. The fact that Tudor’s system was built by an economist from Goldman Sachs and based partly on the instincts of a trader from Goldman Sachs was revealing: No matter how brilliant Wadhwani and Heffernan might be, they came from the heart of the financial establishment, and other parts of that establishment were likely to hatch strategies that were at least somewhat similar.


pages: 733 words: 179,391

Adaptive Markets: Financial Evolution at the Speed of Thought by Andrew W. Lo

"Robert Solow", Albert Einstein, Alfred Russel Wallace, algorithmic trading, Andrei Shleifer, Arthur Eddington, Asian financial crisis, asset allocation, asset-backed security, backtesting, bank run, barriers to entry, Berlin Wall, Bernie Madoff, bitcoin, Bonfire of the Vanities, bonus culture, break the buck, Brownian motion, business cycle, business process, butterfly effect, buy and hold, capital asset pricing model, Captain Sullenberger Hudson, Carmen Reinhart, collapse of Lehman Brothers, collateralized debt obligation, commoditize, computerized trading, corporate governance, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, cryptocurrency, Daniel Kahneman / Amos Tversky, delayed gratification, Diane Coyle, diversification, diversified portfolio, double helix, easy for humans, difficult for computers, Ernest Rutherford, Eugene Fama: efficient market hypothesis, experimental economics, experimental subject, Fall of the Berlin Wall, financial deregulation, financial innovation, financial intermediation, fixed income, Flash crash, Fractional reserve banking, framing effect, Gordon Gekko, greed is good, Hans Rosling, Henri Poincaré, high net worth, housing crisis, incomplete markets, index fund, interest rate derivative, invention of the telegraph, Isaac Newton, James Watt: steam engine, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Meriwether, Joseph Schumpeter, Kenneth Rogoff, London Interbank Offered Rate, Long Term Capital Management, longitudinal study, loss aversion, Louis Pasteur, mandelbrot fractal, margin call, Mark Zuckerberg, market fundamentalism, martingale, merger arbitrage, meta analysis, meta-analysis, Milgram experiment, money market fund, moral hazard, Myron Scholes, Nick Leeson, old-boy network, out of africa, p-value, paper trading, passive investing, Paul Lévy, Paul Samuelson, Ponzi scheme, predatory finance, prediction markets, price discovery process, profit maximization, profit motive, quantitative hedge fund, quantitative trading / quantitative finance, RAND corporation, random walk, randomized controlled trial, Renaissance Technologies, Richard Feynman, Richard Feynman: Challenger O-ring, risk tolerance, Robert Shiller, Robert Shiller, Sam Peltzman, Shai Danziger, short selling, sovereign wealth fund, Stanford marshmallow experiment, Stanford prison experiment, statistical arbitrage, Steven Pinker, stochastic process, stocks for the long run, survivorship bias, Thales and the olive presses, The Great Moderation, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Thomas Malthus, Thorstein Veblen, Tobin tax, too big to fail, transaction costs, Triangle Shirtwaist Factory, ultimatum game, Upton Sinclair, US Airways Flight 1549, Walter Mischel, Watson beat the top human players on Jeopardy!, WikiLeaks, Yogi Berra, zero-sum game

After the third call, I realized that something significant was occurring on Wall Street, something that was off the radar of academic theory or hedge fund practice. 284 • Chapter 8 I knew all three alumni were working at hedge funds engaged in the same broad category of strategies known as “statistical arbitrage,” or “statarb” for short—highly sophisticated quantitative algorithms and computerized trading platforms involving long and short positions in hundreds of stocks. These were the same kinds of strategies used by Morgan Stanley and D. E. Shaw in the 1980s (see chapter 7). This seemed like too much of a coincidence. And the fact that these three were calling up their former finance professor to ask about what’s going on in the industry suggested that they must have been really desperate for information!


pages: 843 words: 223,858

The Rise of the Network Society by Manuel Castells

"Robert Solow", Apple II, Asian financial crisis, barriers to entry, Big bang: deregulation of the City of London, Bob Noyce, borderless world, British Empire, business cycle, capital controls, complexity theory, computer age, computerized trading, creative destruction, Credit Default Swap, declining real wages, deindustrialization, delayed gratification, dematerialisation, deskilling, disintermediation, double helix, Douglas Engelbart, Douglas Engelbart, edge city, experimental subject, financial deregulation, financial independence, floating exchange rates, future of work, global village, Gunnar Myrdal, Hacker Ethic, hiring and firing, Howard Rheingold, illegal immigration, income inequality, Induced demand, industrial robot, informal economy, information retrieval, intermodal, invention of the steam engine, invention of the telephone, inventory management, James Watt: steam engine, job automation, job-hopping, John Markoff, knowledge economy, knowledge worker, labor-force participation, laissez-faire capitalism, Leonard Kleinrock, longitudinal study, low skilled workers, manufacturing employment, Marc Andreessen, Marshall McLuhan, means of production, megacity, Menlo Park, moral panic, new economy, New Urbanism, offshore financial centre, oil shock, open economy, packet switching, Pearl River Delta, peer-to-peer, planetary scale, popular capitalism, popular electronics, post-industrial society, postindustrial economy, prediction markets, Productivity paradox, profit maximization, purchasing power parity, RAND corporation, Robert Gordon, Robert Metcalfe, Shoshana Zuboff, Silicon Valley, Silicon Valley startup, social software, South China Sea, South of Market, San Francisco, special economic zone, spinning jenny, statistical model, Steve Jobs, Steve Wozniak, Ted Nelson, the built environment, the medium is the message, the new new thing, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, total factor productivity, trade liberalization, transaction costs, urban renewal, urban sprawl, zero-sum game

However, in a long personal conversation, after reading the draft of my analysis, he did not disagree with my interpretation of the project of an “architecture of nudity,” although he conceived it rather as an innovative attempt to bring together high-tech and classic design. We both agreed that the new architectural monuments of our epoch are likely to be built as “communication exchangers” (airports, train stations, intermodal transfer areas, telecommunication infrastructures, harbors, and computerized trading centers). 86 For a useful debate on the matter, see Lillyman et al. (1994). 87 Castells (1972: 496ff). 88 For an updated social and spatial, illustrated history of Belleville, see the delightful book by Morier (1994); on urban renewal in Paris in the 1970s, see Godard et al. (1973). 89 Boyer (1994). 90 Jacobs (1993). 91 Machimura (1995: 16). See his book on the social and political forces underlying the restructuring of Tokyo: Machimura (1994). 7 The Edge of Forever: Timeless Time We are embodied time, and so are our societies, made out of history.


pages: 992 words: 292,389

Conspiracy of Fools: A True Story by Kurt Eichenwald

Asian financial crisis, Burning Man, computerized trading, corporate raider, estate planning, forensic accounting, intangible asset, Irwin Jacobs, John Markoff, Long Term Capital Management, margin call, Negawatt, new economy, oil shock, price stability, pushing on a string, Ronald Reagan, transaction costs, value at risk, young professional

Duncan was asking Stewart if he could review some materials when someone interrupted with horrifying news. An airliner had just struck the World Trade Center. It was the morning of September 11. The terrified voices from New York echoed through the Enron trading floor. One Enron trader had been on the line with Cantor Fitzgerald, based on the upper floors of One World Trade Center, when the first plane hit. The firm operated a computerized trading-reporting system used by trading desks, including at Enron, and now their screens had gone blank. “The building’s burning,” one trader on the line said. “We’re supposed to get out. But I don’t think we can.” Eventually the voices disappeared, and the Enron traders watched in horror as the two towers collapsed—first Tower Two, then, not long after, Tower One, where the people they had just been speaking with had been trapped.


pages: 1,336 words: 415,037

The Snowball: Warren Buffett and the Business of Life by Alice Schroeder

affirmative action, Albert Einstein, anti-communist, Ayatollah Khomeini, barriers to entry, Bob Noyce, Bonfire of the Vanities, Brownian motion, capital asset pricing model, card file, centralized clearinghouse, Charles Lindbergh, collateralized debt obligation, computerized trading, corporate governance, corporate raider, Credit Default Swap, credit default swaps / collateralized debt obligations, desegregation, Donald Trump, Eugene Fama: efficient market hypothesis, Everybody Ought to Be Rich, global village, Golden Gate Park, Haight Ashbury, haute cuisine, Honoré de Balzac, If something cannot go on forever, it will stop - Herbert Stein's Law, In Cold Blood by Truman Capote, index fund, indoor plumbing, intangible asset, interest rate swap, invisible hand, Isaac Newton, Jeff Bezos, John Meriwether, joint-stock company, joint-stock limited liability company, Long Term Capital Management, Louis Bachelier, margin call, market bubble, Marshall McLuhan, medical malpractice, merger arbitrage, Mikhail Gorbachev, money market fund, moral hazard, NetJets, new economy, New Journalism, North Sea oil, paper trading, passive investing, Paul Samuelson, pets.com, plutocrats, Plutocrats, Ponzi scheme, Ralph Nader, random walk, Ronald Reagan, Scientific racism, shareholder value, short selling, side project, Silicon Valley, Steve Ballmer, Steve Jobs, supply-chain management, telemarketer, The Predators' Ball, The Wealth of Nations by Adam Smith, Thomas Malthus, too big to fail, transcontinental railway, Upton Sinclair, War on Poverty, Works Progress Administration, Y2K, yellow journalism, zero-coupon bond

Buffett felt that following the market minute to minute and manipulating computers was not the way to invest. Finally it became obvious even to computer-averse Buffett that to trade bonds you had to have a Bloomberg terminal. But the Bloomberg sat some distance from Buffett’s office and he never looked at it; that was the job of Mark Millard, the bond trader.10 The advent of the Bloomberg terminal, symbol of the new computerized trading, mirrored the ongoing struggle over Salomon’s identity, which continued within the firm. Its laggard businesses had never gotten back on their feet. In 1994, Maughan had tried to realign pay at Salomon on the theory that employees should shoulder the same risk as shareholders. When times were good, they would get bonuses, but when times were bad, they would suffer as well. There were people inside the firm who agreed with him.11 But that was not the standard anywhere else on Wall Street, so thirty-five senior people walked out the door.


Principles of Corporate Finance by Richard A. Brealey, Stewart C. Myers, Franklin Allen

3Com Palm IPO, accounting loophole / creative accounting, Airbus A320, Asian financial crisis, asset allocation, asset-backed security, banking crisis, Bernie Madoff, big-box store, Black-Scholes formula, break the buck, Brownian motion, business cycle, buy and hold, buy low sell high, capital asset pricing model, capital controls, Carmen Reinhart, carried interest, collateralized debt obligation, compound rate of return, computerized trading, conceptual framework, corporate governance, correlation coefficient, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, cross-subsidies, discounted cash flows, disintermediation, diversified portfolio, equity premium, eurozone crisis, financial innovation, financial intermediation, fixed income, frictionless, fudge factor, German hyperinflation, implied volatility, index fund, information asymmetry, intangible asset, interest rate swap, inventory management, Iridium satellite, Kenneth Rogoff, law of one price, linear programming, Livingstone, I presume, London Interbank Offered Rate, Long Term Capital Management, loss aversion, Louis Bachelier, market bubble, market friction, money market fund, moral hazard, Myron Scholes, new economy, Nick Leeson, Northern Rock, offshore financial centre, Ponzi scheme, prediction markets, price discrimination, principal–agent problem, profit maximization, purchasing power parity, QR code, quantitative trading / quantitative finance, random walk, Real Time Gross Settlement, risk tolerance, risk/return, Robert Shiller, Robert Shiller, shareholder value, Sharpe ratio, short selling, Silicon Valley, Skype, Steve Jobs, The Nature of the Firm, the payments system, the rule of 72, time value of money, too big to fail, transaction costs, University of East Anglia, urban renewal, VA Linux, value at risk, Vanguard fund, yield curve, zero-coupon bond, zero-sum game, Zipcar

For example, you may wish to calculate two figures, one on the assumption that the opportunity for further profitable investment disappears after six years and another assuming it disappears after eight years. 2. How much of your estimate of the value of Bok’s stock comes from the present value of growth opportunities? ___________ 1Trades are still made face to face on the floor of the NYSE, but computerized trading is taking over. In 2006 the NYSE merged with Archipelago, an electronic trading system, and transformed itself into a public corporation. The following year it merged with Euronext, an electronic trading system in Europe, and changed its name to NYSE Euronext. 2Other good sources of trading data are moneycentral.msn.com or the online edition of The Wall Street Journal at www.wsj.com (look for the “Market” and then “Market Data” tabs). 3Yahoo!