High speed trading

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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

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algorithmic trading, automated trading system, banking crisis, bash_history, Bernie Madoff, butterfly effect, buttonwood tree, cloud computing, collapse of Lehman Brothers, Donald Trump, 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!

In November 2007, Trading Machines launched with $20 million. While small by some standards, it was deemed substantial for a high-speed trading outfit—and spoke to the economics of the business. Fast traders make money by picking up pennies and nickels on thousands of trades a day. Because they move in and out of positions so rapidly, they can recycle a small amount of cash over and over again. Imagine lowering a water-powered generator into a stream of water. The faster the stream, the more energy it generates. The ability to scale up to massive volumes with seemingly little risk—in effect causing the stream to flow more rapidly—was a major reason why high-speed trading had become one of the industry’s hottest strategies by the late 2000s. Trading Machines was among the elite at this approach.

The new wave of dark pools epitomized a driving force in finance as old as time: secrecy. In part a solution to a problem, they were also the symptom of a disease. The lit market had become a playground for highly sophisticated traders—many of the very traders sitting in Mathisson’s audience—who’d designed and deployed the robo algos that hacked the market’s plumbing. Sadly, the exchanges had helped make all of this possible. They provided to the high-speed trading firms expensive, data-rich feeds that broadcast terabytes of information about specific buy and sell orders from giant mutual funds to the Bot algos. So much information that it could be used to engage in the hit-and-run tactics regulators, fund managers, and senators were screaming about. This was all playing out every day, every nanosecond, in the lit markets—a frenzied dance of predator and prey, with Mathisson’s peers playing the part of the swarming piranha.

It was a new version of the old stock market—and highly toxic. Bodek began to think it had become broken at its core. If I’m swinging at market phantoms, buying too high, selling too low, what chance do ordinary investors have? It was so complex. The number of destinations for trading stocks was maddening. There were four public exchanges: the NYSE, Nasdaq, Direct Edge, and BATS (the latter two, which specialized in high-speed trading, appeared on the scene in 2005 and 2006, respectively). Inside each of those exchanges were various other destinations. The NYSE had NYSE Arca, NYSE Amex, NYSE Euronext, and NYSE Alternext. Nasdaq had three markets. BATS had two. Direct Edge had EDGA, which had no “maker-taker” system, and EDGX, which did. Then there were the dark pools. Giant banks ran most of them. Credit Suisse owned the largest, Dan Mathisson’s Crossfinder.

 

pages: 280 words: 73,420

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

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algorithmic trading, automated trading system, Bernie Madoff, Bernie Sanders, Bretton Woods, buttonwood tree, credit crunch, Credit Default Swap, financial innovation, 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, 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

“I’m pleased that SEC Chairman Schapiro has said the Commission will soon move to ban flash orders. But that is not the end of the story. It is becoming increasingly clear that naked short selling was just the first of a series of issues surrounding the way stock trades are executed that create unfair advantages for powerful insiders,” he said. “We seem to be learning more every day about certain order types, high-speed trading, collocation of servers at exchanges, dark pools, and other indications that we have a two-tiered market: one for privileged insiders with high-speed computers and another for the average investor who must follow the rules. We need the SEC to move with urgency to restore investor protections and thereby strengthen the credibility and integrity of America’s financial markets,” he said. In short, Kaufman wanted Schapiro to take the high-frequency traders head on.

Getco registered as a New York Stock Exchange (NYSE) specialist firm, and its competitors believed it was trying to convince regulators to make all HFT firms engaged in market-making activities to register with the SEC and adhere to strict capital standards, a change that would have driven many of the smaller trading firms out of business. Banks and Wall Street brokerages also established proprietary high-speed trading desks. But the majority of high-frequency traders were smaller proprietary trading shops or “prop shops,” which had no outside customers. They clustered around New York and Chicago to be close on the one hand to securities markets and on the other to the Chicago Mercantile Exchange (CME). The public often mislabeled high-frequency traders as “Quants.” The term is short for quantitative traders and refers to graduates of elite schools such as MIT and the University of Chicago whose inventiveness over the past 30 years has brought marvelous wonders to the marketplace.

It took the company 47 minutes to realize it had gone bust and to call its clearing bank, to apprise it of the situation.4 Most HFT firms were collocating machines at multiple exchanges in both the equities and commodities markets, and the exchanges always welcomed these customers with open arms. Regulation National Market System (NMS), which had fostered competition among the exchanges to reduce costs to investors, had created a market in which HFT firms could thrive and so change the nature of trading that it became toxic for most everyone else. Endnotes 1. Jill Barshay, “High-Speed Trading Goes Off the Street,” Market Watch, August 26, 2009. http://marketplace.publicradio.org/display/web/2009/08/26/pm-colocation/. 2. Ibid. 3. Jacob Bunge, “DJ NYSE Euronext Turns on NJ Data Center as Emigration Begins,” Dow Jones News Wires, August 25, 2010. 4. Carol L. Clark, “Controlling Risk in a Lightning-Speed Trading Environment,” Chicago Fed Letter, March 2010, No. 272. 16.

 

pages: 282 words: 80,907

Who Gets What — and Why: The New Economics of Matchmaking and Market Design by Alvin E. Roth

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Affordable Care Act / Obamacare, Airbnb, algorithmic trading, barriers to entry, Berlin Wall, bitcoin, Build a better mousetrap, centralized clearinghouse, computer age, crowdsourcing, deferred acceptance, desegregation, experimental economics, first-price auction, Flash crash, High speed trading, income inequality, Internet of things, invention of agriculture, invisible hand, Jean Tirole, law of one price, Lyft, market clearing, market design, medical residency, obamacare, proxy bid, road to serfdom, school choice, sealed-bid auction, second-price auction, second-price sealed-bid, Silicon Valley, spectrum auction, Spread Networks laid a new fibre optics cable between New York and Chicago, Steve Jobs, The Wealth of Nations by Adam Smith, two-sided market

Such a trader might be able to buy from them at their old prices (now out of date, or “stale”) and then moments later sell back to them at the new higher prices. The wider the spreads the liquidity providers quote, the further prices have to jump before they can be exploited on both sides of the trade this way, and the more they pass on the cost of protecting themselves to ordinary investors. Very high speed trading can also contribute to instability in the market. A famous example, in which high-speed trading of ES futures and SPY exchange-traded funds was implicated, is the “flash crash” of 2010. In just four minutes, the prices of futures and of the related SPY exchange-traded funds (as well as many of the stocks in the index) were driven down by several percentage points—a very big move, in the absence of earth-shattering news—and then recovered almost as fast.

Let’s take a look at each in turn, starting with the fastest market of all: finance. A Game of (Milli)Seconds Not far from where wheat futures are traded at the Chicago Board of Trade, there’s another marketplace, the Chicago Mercantile Exchange. And near them both, at the University of Chicago, an innovative market designer named Eric Budish (a former student of mine) has been thinking about high-speed trading at both exchanges. Budish is looking at the growing use of computerized algorithms and how they influence financial markets. He’s also looking at how changes in the design of financial marketplaces might help solve some of their long-standing structural problems. The Chicago Mercantile Exchange is a lot like the New York Stock Exchange. For one thing, they both have similar market designs: trades are made via a continuous electronic limit order book, which records the offers to buy (bids) and the offers to sell (asks) starting with the highest bid first and the lowest ask first.

 

pages: 317 words: 84,400

Automate This: How Algorithms Came to Rule Our World by Christopher Steiner

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23andMe, Ada Lovelace, airport security, Al Roth, algorithmic trading, backtesting, big-box store, Black-Scholes formula, call centre, cloud computing, collateralized debt obligation, Credit Default Swap, credit default swaps / collateralized debt obligations, delta neutral, Donald Trump, Douglas Hofstadter, dumpster diving, Flash crash, Gödel, Escher, Bach, High speed trading, Howard Rheingold, index fund, Isaac Newton, John Maynard Keynes: technological unemployment, knowledge economy, late fees, Mark Zuckerberg, market bubble, medical residency, Narrative Science, PageRank, pattern recognition, Paul Graham, prediction markets, quantitative hedge fund, Renaissance Technologies, ride hailing / ride sharing, risk tolerance, Sergey Aleynikov, side project, Silicon Valley, Skype, speech recognition, Spread Networks laid a new fibre optics cable between New York and Chicago, transaction costs, upwardly mobile, Watson beat the top human players on Jeopardy!, Y Combinator

He later turned his industrious focus to stamp buying, selling, and trading. The irregular market, in which some stamps sold for more in one place than they did in another, enthralled him. He had discovered arbitrage, where one takes advantage of similar asset markets with disparate prices. An arbitrageur buys where the price is lower and sells where the price is higher—a strategy that, in far faster form, comprises the backbone of many modern high-speed trading operations. After graduating high school, Peterffy studied advanced geometry in a technical school for surveyors, with a long-term goal of college and a degree in civil engineering. But his education was derailed in 1965 when, at twenty-one, he got a short-term visa to visit some distant relatives in West Germany. He seized this opportunity in Americanized Germany to apply for a U.S. immigration permit, which he eventually received.

At Mocatta’s headquarters in Manhattan, Peterffy’s programmers worked at computer screens and read market data as it came in on Teletype machines. The programmers then typed the data by hand into their computers, whose algorithms issued prices for Mocatta to quote on the New York Commodities Exchange floor. The programmers, speaking to clerks near the floor action downtown, would bark out quotes as fast as the algorithm issued them, and Mocatta’s clerks would signal the prices to their pit traders with hand gestures. It was hardly high-speed trading, but it was the first time markets were consistently dictated by an algorithm. And the best part for Peterffy: the rest of the market had little idea where he got his numbers from. He might have entered Wall Street as a hacker with little market sense, but Peterffy’s trading instincts—born while chopping up chewing gum sticks, chasing scrap metal, and pawning stamps—became sharpened.

Peterffy thinks that in this age of light-speed trading, bids and offers on stocks should be held up for a minimum amount of time, still far less than a second, but enough to eliminate the head fakes, parries, and trickery that comprise the contemporary market and that lead us to clifflike falls and rocketlike spikes. His ultimate fear is that a rogue series of algorithms sparks a string of colossal losses that their owners can’t cover. Because some high-speed trading algorithms are able to trade on margin with leverage, it’s conceivable that a series of bad trades, all conducted in seconds, could lead to a liquidity crisis, bankrupting a trader’s broker and the clients he trades for. Such incidents have nearly happened before. In late 2009, Chicago’s Infinium Capital Management, one of the more secretive and powerful trading houses in the United States, twice lost control of an algorithm that began selling S&P 500 futures as fast as it could, dropping the market.

 

pages: 268 words: 75,850

The Formula: How Algorithms Solve All Our Problems-And Create More by Luke Dormehl

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3D printing, algorithmic trading, Any sufficiently advanced technology is indistinguishable from magic, augmented reality, big data - Walmart - Pop Tarts, call centre, Cass Sunstein, Clayton Christensen, computer age, death of newspapers, deferred acceptance, Edward Lorenz: Chaos theory, Erik Brynjolfsson, Filter Bubble, Flash crash, Florence Nightingale: pie chart, Frank Levy and Richard Murnane: The New Division of Labor, Google Earth, Google Glasses, High speed trading, Internet Archive, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, Kevin Kelly, Kodak vs Instagram, Marshall McLuhan, means of production, Nate Silver, natural language processing, Netflix Prize, pattern recognition, price discrimination, recommendation engine, Richard Thaler, Rosa Parks, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley startup, Slavoj Žižek, social graph, speech recognition, Steve Jobs, Steven Levy, Steven Pinker, Stewart Brand, the scientific method, The Signal and the Noise by Nate Silver, upwardly mobile, Wall-E, Watson beat the top human players on Jeopardy!, Y Combinator

If this is the case, then how many shipwrecks do we need before we stop building ships? Those looking for stories of algorithms run amok can certainly find them with relative ease. On May 6, 2010, the Dow Jones Industrial Average plunged 1,000 points in just 300 seconds—effectively wiping out close to $1 trillion of wealth in a stock market debacle that became known as the Flash Crash. Unexplained to this day, the Flash Crash has been pinned on everything from the impact of high-speed trading to a technical glitch.15 Yet few people would seriously put forward the view that algorithms are, in themselves, bad. Indeed, it’s not simply a matter of algorithms doing the jobs that were once carried out manually; in many cases algorithms perform tasks that would be impossible for a human to perform. Particularly, algorithms like those utilized by Google that rely on unimaginably large datasets could never be reenacted by hand.

Farewell to the Working Class: An Essay on Post-Industrial Socialism (London: Pluto Press, 1982). Rifkin, Jeremy. The End of Work: The Decline of the Global Labor Force and the Dawn of the Post-Market Era (New York: G. P. Putnam’s Sons, 1995). 14 Evans, Christopher. The Mighty Micro (Sevenoaks, UK: Coronet, 1980). 15 Keim, Brandon. “Nanosecond Trading Could Make Markets Go Haywire.” Wired, February 16, 2012. wired.com/wiredscience/2012/02/high-speed-trading/. 16 bbc.co.uk/news/technology-18427851. 17 Fallows, Deborah. Search Engine Users, January 23, 2005. Pew Research Center and American Life Project, pewinternet.org. 18 Vaidhyanathan, Siva. The Googlization of Everything (and Why We Should Worry) (Berkeley: University of California Press, 2011). 19 MacCormick, John. Nine Algorithms That Changed the Future: The Ingenious Ideas That Drive Today’s Computers (Princeton, N.J.: Princeton University Press, 2012). 20 Anderson, Chris.

 

pages: 250 words: 87,722

Flash Boys: A Wall Street Revolt by Michael Lewis

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automated trading system, bash_history, Berlin Wall, Bernie Madoff, collateralized debt obligation, Fall of the Berlin Wall, financial intermediation, Flash crash, High speed trading, latency arbitrage, pattern recognition, risk tolerance, Sergey Aleynikov, Small Order Execution System, Spread Networks laid a new fibre optics cable between New York and Chicago, too big to fail, trade route, transaction costs, Vanguard fund

Exactly why speed was so important to them was not clear; what was clear was that they felt threatened by this faster new line. “Somebody would say, ‘Wait a second,’ ” recalls Carley. “ ‘If we want to continue with the strategies we are currently running, we have to be on this line. We have no choice but to pay whatever you’re asking. And you’re going to go from my office to talk to all of my competitors.’ ” “I’ll tell you my reaction to them,” says Darren Mulholland, a principal at a high-speed trading firm called Hudson River Trading. “It was, ‘Get out of my office.’ The thing I couldn’t believe was that when they came to my office they were going to go live in a month. And they didn’t even know who the clients were! They only discovered us from reading a letter we’d written to the SEC. . . .Who takes those kinds of business risks?” For $300,000 a month plus a few million more in up-front expenses, the people on Wall Street then making perhaps more money than people have ever made on Wall Street would enjoy the right to continue doing what they were already doing.

The pension fund would not be able to say, for example, whether the Wall Street bank allowed its own proprietary traders to know of the big buy order, or if those traders had used their (faster than the dark pool) market connections to front-run the order on the public exchanges. Even if the Wall Street bank resisted the temptation to trade for itself against its own customers, there was virtually no chance they resisted the temptation to sell access to the dark pool to high-frequency traders. The Wall Street banks did not disclose which high-speed trading firms had paid them for special access to their dark pools, or how much they had paid, but selling that access was standard practice. Raising, again, the obvious question: Why would anyone pay for access to the customers’ orders inside a Wall Street bank’s dark pool? The straight answer was that a customer’s stock market order, inside a dark pool, was fat and juicy prey. The order was typically large, and its movements were especially predictable: Each Wall Street bank had its own detectable pattern for handling orders.

 

pages: 903 words: 235,753

The Stack: On Software and Sovereignty by Benjamin H. Bratton

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1960s counterculture, 3D printing, 4chan, Ada Lovelace, additive manufacturing, airport security, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, algorithmic trading, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, Berlin Wall, bioinformatics, bitcoin, blockchain, Buckminster Fuller, Burning Man, call centre, carbon footprint, carbon-based life, Cass Sunstein, Celebration, Florida, charter city, clean water, cloud computing, connected car, corporate governance, crowdsourcing, cryptocurrency, dark matter, David Graeber, deglobalization, dematerialisation, disintermediation, distributed generation, don't be evil, Douglas Engelbart, Edward Snowden, Elon Musk, en.wikipedia.org, Eratosthenes, ethereum blockchain, facts on the ground, Flash crash, Frank Gehry, Frederick Winslow Taylor, future of work, Georg Cantor, gig economy, global supply chain, Google Earth, Google Glasses, Guggenheim Bilbao, High speed trading, Hyperloop, illegal immigration, industrial robot, information retrieval, intermodal, Internet of things, invisible hand, Jacob Appelbaum, Jaron Lanier, Jony Ive, Julian Assange, Khan Academy, linked data, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, Masdar, McMansion, means of production, megacity, megastructure, Menlo Park, Minecraft, Monroe Doctrine, Network effects, new economy, offshore financial centre, oil shale / tar sands, packet switching, PageRank, pattern recognition, peak oil, performance metric, personalized medicine, Peter Thiel, phenotype, place-making, planetary scale, RAND corporation, recommendation engine, reserve currency, RFID, Sand Hill Road, self-driving car, semantic web, sharing economy, Silicon Valley, Silicon Valley ideology, Slavoj Žižek, smart cities, smart grid, smart meter, social graph, software studies, South China Sea, sovereign wealth fund, special economic zone, spectrum auction, Startup school, statistical arbitrage, Steve Jobs, Steven Levy, Stewart Brand, Stuxnet, Superbowl ad, supply-chain management, supply-chain management software, TaskRabbit, the built environment, The Chicago School, the scientific method, Torches of Freedom, transaction costs, Turing complete, Turing machine, Turing test, universal basic income, urban planning, Vernor Vinge, Washington Consensus, web application, WikiLeaks, working poor, Y Combinator

The limits of machinic calculation are not the same as the limits of deterministic rationality, and the social effects of computational systems are certainly given to creative accidents.17 Reactionary analog aesthetics and patriotisms, Emersonian withdrawal, and deconstrucivist political theology buy us less time and far less wiggle room than they promise, even less actually than the unfortunate notion that planetary-scale computation could emerge and mature without fundamental constitutive violence against traditional (that is, “modern”) concepts of individual, society, and sovereignty. Because they simulate logic but are not themselves necessarily logical, computers make the world in ways that do not ultimately require our thinking to function (such as the interactions between high-speed trading algorithms that even their programmers cannot entirely predict and comprehend). The forms of inhuman intelligence that they manifest will never pass the Turing test, nor should we bother asking this of them. It is an absurd and primitive request.18 It is inevitable that synthetic algorithmic intelligences can and will create things that we have not thought of in advance or ever intended to make, but as suggested, because they do not need our thinking or intention as their alibi, it is their inhumanity that may make them most creative.19 Like Deleuze on the beach making sand piles, humans wrangle computation with our algorithm boxes, and in doing so, we make things by accident, sometimes little things like signal noise on the wire and sometimes big things like megastructures. 17. 

In this large-scale bandwidth, provision and access becomes a core spatial planning strategy, whether for small market cities like Kansas City, Missouri, the first test bed for Google's 100 megabyte fiber network, or for large market actors like traders who relocate their offices farther down the island in Manhattan to get closer to the central switches on Wall Street and shave nanoseconds off high-speed trading cycles. Despite its global spread and horizontal ubiquity, for Stack urbanism, proximity to the center, as defined by supermassive concentrations of bit flows, is seen as essential. 12.  See David Kusner, “The Real Story of Stuxnet,” IEEE Spectrum, February 23, 2013, http://spectrum.ieee.org/telecom/security/the-real-story-of-stuxnet. 13.  As well as simulations of all of these, as evidenced by the imaginary ISIS attack on Louisiana as invented by Russian mischief makers.

Among other things, the financial crisis is a crisis of addressability, a de-addressing of things, and one that continues consolidating a shift within global market economics (when not also collapsing them). We can only anticipate what forms of high weirdness will ensue, as the paired computerization of matter-into-monies (i.e., carbon credits trading, where the value of money is itself measured in carbon) and monies-into-virtuality (i.e., the light pulses of high-speed trading) continues to evolve and accelerate.8 New addressing schemes to locate and coordinate instances of value are multiplying, both as generic currency (bitcoin blockchains) and as platforms for brokering things-with-value (various sharing economy schemes). At stake in all this is also the design of the economy of information itself, from the smallest-scale object or gesture to the largest topological frameworks, and interrelations across scales by drawing and managing an orthodox map in the form of an address table.9 What gets to count and to whom, and who profits from merely counting?

 

pages: 320 words: 87,853

The Black Box Society: The Secret Algorithms That Control Money and Information by Frank Pasquale

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Affordable Care Act / Obamacare, algorithmic trading, Amazon Mechanical Turk, asset-backed security, Atul Gawande, bank run, barriers to entry, Berlin Wall, Bernie Madoff, Black Swan, bonus culture, Brian Krebs, call centre, Capital in the Twenty-First Century by Thomas Piketty, Chelsea Manning, cloud computing, collateralized debt obligation, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, crowdsourcing, cryptocurrency, Debian, don't be evil, Edward Snowden, en.wikipedia.org, Fall of the Berlin Wall, Filter Bubble, financial innovation, Flash crash, full employment, Goldman Sachs: Vampire Squid, Google Earth, Hernando de Soto, High speed trading, hiring and firing, housing crisis, informal economy, information retrieval, interest rate swap, Internet of things, invisible hand, Jaron Lanier, Jeff Bezos, job automation, Julian Assange, Kevin Kelly, knowledge worker, Kodak vs Instagram, kremlinology, late fees, London Interbank Offered Rate, London Whale, Mark Zuckerberg, mobile money, moral hazard, new economy, Nicholas Carr, offshore financial centre, PageRank, pattern recognition, precariat, profit maximization, profit motive, quantitative easing, race to the bottom, recommendation engine, regulatory arbitrage, risk-adjusted returns, search engine result page, shareholder value, Silicon Valley, Snapchat, Spread Networks laid a new fibre optics cable between New York and Chicago, statistical arbitrage, statistical model, Steven Levy, the scientific method, too big to fail, transaction costs, two-sided market, universal basic income, Upton Sinclair, value at risk, WikiLeaks

HFT often involves “very high order amounts; rapid order cancellation; a flat position at the end of the trading day; extracting very low margins per trade; and trading at ultra-fast speeds.” Andrew J. Keller, “Robocops: Regulating High Frequency Trading after the Flash Crash of 2010,” Ohio State Law Journal 73 (2012): 1459. 121. Matthew O’Brien, “High-Speed Trading Isn’t About Efficiency—It’s About Cheating,” The Atlantic, February 8, 2014. Available at http://www.the atlantic .com /business /archive /2014 /02/high-speed-trading -isnt-about-efficiency-its-about-cheating /283677/; Charles Schwab and Walt Bettinger, “Statement on High-Frequency Trading,” April 3, 2014. Available at http:// www.aboutschwab.com /press/issues/statement _on _high _frequency_trading. 122. Robert Hiltonsmith, The Retirement Savings Drain: The Hidden and Excessive Costs of 401(k)s (New York: Dēmos, 2012).

 

pages: 515 words: 132,295

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

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3D printing, accounting loophole / creative accounting, additive manufacturing, Airbnb, algorithmic trading, Asian financial crisis, asset allocation, bank run, Basel III, bonus culture, Bretton Woods, British Empire, call centre, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, carried interest, centralized clearinghouse, clean water, collateralized debt obligation, corporate governance, 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, interest rate derivative, interest rate swap, Internet of things, invisible hand, joint-stock company, joint-stock limited liability company, Kenneth Rogoff, knowledge economy, labor-force participation, labour mobility, London Whale, Long Term Capital Management, manufacturing employment, market design, Martin Wolf, moral hazard, mortgage debt, mortgage tax deduction, new economy, non-tariff barriers, offshore financial centre, oil shock, passive investing, 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, Second Machine Age, shareholder value, sharing economy, Silicon Valley, Silicon Valley startup, Snapchat, sovereign wealth fund, Steve Jobs, technology bubble, The Chicago School, 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

The key point is that the public policy decisions that aided financialization didn’t happen all at once, but were taken incrementally, creating a dysfunctional web of changes in areas like tax, trade, regulatory policy, corporate governance, and law. It’s a web that will take time and tremendous effort to dismantle. Financialization is behind the shifts in our retirement system and tax code that have given banks ever more money to play with, and the rise of high-speed trading that has allowed more and more risk and leverage in the system to serve up huge profits to a privileged few. It is behind the destructive deregulation of the 1980s and 1990s, and the failure to reregulate the banking sector properly after the financial crisis of 2008. Individuals from J.P. Morgan and Goldman Sachs may (or, more often, may not) go to jail for reckless trading, but the system that permitted their malfeasance remains in place.

Not only that, but it was also the nail in the coffin of Glass-Steagall, the Depression-era banking legislation that had kept consumers relatively safe from exploitation by financial interests since the 1930s. Weill called the merger “the greatest deal in the history of the financial services industry” and “the crowning of my career.”1 It was a transaction that would allow the newly formed company to offer pretty much every financial service ever invented, from credit cards to corporate IPO underwriting, high-speed trading to mortgages, investment advice to the sale of any complex security you could imagine, in 160-plus countries, twenty-four hours a day. As with the British Empire in a former era, the sun never set on Citigroup. So it was quite a moment when, in mid-2012, the emperor had an ideological abdication. Weill, who stepped down as Citi CEO in 2003 and has recently undergone something of an existential crisis over his role in the worst financial crash in eighty years, went on CNBC and declared that pretty much everything he’d believed about the bank, and about finance, was wrong.

 

pages: 236 words: 77,735

Rigged Money: Beating Wall Street at Its Own Game by Lee Munson

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affirmative action, asset allocation, backtesting, barriers to entry, Bernie Madoff, Bretton Woods, buy low sell high, California gold rush, call centre, Credit Default Swap, diversification, diversified portfolio, estate planning, fiat currency, financial innovation, fixed income, Flash crash, follow your passion, German hyperinflation, High speed trading, housing crisis, index fund, joint-stock company, moral hazard, passive investing, Ponzi scheme, price discovery process, random walk, risk tolerance, risk-adjusted returns, risk/return, too big to fail, trade route, Vanguard fund, walking around money

How is this useful to the other venues that are ready and willing to provide the liquidity? It short-changes competition by giving a select few the opportunity to play their hands without showing them. Longer term, it undermines the incentive for traders to show at least some interest in public markets. The exception to the regulation allowing flash orders was adopted in 1978, long before the use of high-speed trading systems. Now it is simply a loophole that needs to be closed. Who Decides the Best Price? This is what the Securities Reform Act of 1975 was all about: Creating a national market system to share securities transactions in real time. While the technology has changed from the original version, we still have a central network that consolidates trade information to create the tape. The Securities Industry Automation Corporation provides the communication systems that keep the three major tapes in the United States running.

 

pages: 252 words: 80,636

Bureaucracy by David Graeber

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3D printing, Affordable Care Act / Obamacare, airport security, Albert Einstein, banking crisis, barriers to entry, borderless world, Bretton Woods, British Empire, collateralized debt obligation, Columbine, conceptual framework, Corn Laws, David Graeber, George Gilder, High speed trading, hiring and firing, late capitalism, means of production, music of the spheres, new economy, obamacare, Occupy movement, Parkinson's law, Peter Thiel, planetary scale, price mechanism, Ronald Reagan, self-driving car, Silicon Valley, South Sea Bubble, transcontinental railway, union organizing, urban planning

Since what is the world of securitized derivatives, collateralized debt obligations, and other such exotic financial instruments but the apotheosis of the principle that value is ultimately a product of paperwork, and the very apex of a mountain of assessment forms which begins with the irritating caseworker determining whether you are really poor enough to merit a fee waiver for your children’s medicine and ends with men in suits engaged in high-speed trading of bets over how long it will take you to default on your mortgage. A critique of bureaucracy fit for the times would have to show how all these threads—financialization, violence, technology, the fusion of public and private—knit together into a single, self-sustaining web. The process of financialization has meant that an ever-increasing proportion of corporate profits come in the form of rent extraction of one sort or another.

 

pages: 342 words: 94,762

Wait: The Art and Science of Delay by Frank Partnoy

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algorithmic trading, Atul Gawande, Bernie Madoff, Black Swan, blood diamonds, Cass Sunstein, Checklist Manifesto, cognitive bias, collapse of Lehman Brothers, collateralized debt obligation, 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, Isaac Newton, Long Term Capital Management, Menlo Park, mental accounting, meta analysis, meta-analysis, 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, statistical model, Steve Jobs, The Market for Lemons, the scientific method, The Wealth of Nations by Adam Smith, upwardly mobile, Walter Mischel

It costs a fortune to send trades through the cables along this more direct new route, like a superfast version of Federal Express, but many firms are willing to pay to minimize latency. After all, they save three whole milliseconds.4 Why are three milliseconds so important? For some traders, having an electronic buy or sell order arrive first can be the difference between making money and losing money. 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.

 

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

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algorithmic trading, automated trading system, Bernie Madoff, buttonwood tree, 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, transaction costs, two-sided market

The market is like a shattered vase that is now held together with glue called high frequency trading (HFT), and that glue is weak—very weak. In addition to fragmentation, under the cover of the digital revolution, conflicted stakeholders—stock exchanges, brokers, and owners of ATSs (alternative trading systems)—have • Enlisted their own regulators to help them create a mechanism that places high-speed trading interests above the interests of all other market participants, particularly investors. • Converted member-owned nonprofit legal structures into ones that are for-profit, which have enabled them to embark upon new business models centered around the creation and distribution of data feeds. • Perverted the true purpose and usage of tools like dark pools from mechanisms to effect large block trades for large mutual and pension funds to a means to feed internalization and proprietary HFT

 

pages: 308 words: 84,713

The Glass Cage: Automation and Us by Nicholas Carr

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Airbnb, Andy Kessler, Atul Gawande, autonomous vehicles, business process, call centre, Captain Sullenberger Hudson, Checklist Manifesto, cloud computing, David Brooks, deliberate practice, deskilling, 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, 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, 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, Watson beat the top human players on Jeopardy!

At its Wall Street trading desk, it has installed a proprietary software program, called THOR, that actually slows down the transmission of buy and sell orders in a way that protects them from the algorithmic manipulations of high-speed traders. By slowing the orders, RBC has found, trades often end up being executed at more attractive terms for its customers. The bank admits that it’s making a trade-off in resisting the prevailing technological imperative of speedy data flows. By eschewing high-speed trading, it makes a little less money on each trade. But it believes that, over the long run, the strengthening of client loyalty and the reduction of risk will lead to higher profits overall.35 One former RBC executive, Brad Katsuyama, is going even further. Having watched stock markets become skewed in favor of high-frequency traders, he spearheaded the creation of a new and fairer exchange, called IEX.

 

pages: 484 words: 104,873

Rise of the Robots: Technology and the Threat of a Jobless Future by Martin Ford

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3D printing, additive manufacturing, Affordable Care Act / Obamacare, AI winter, algorithmic trading, Amazon Mechanical Turk, artificial general intelligence, autonomous vehicles, banking crisis, Baxter: Rethink Robotics, Bernie Madoff, Bill Joy: nanobots, call centre, Capital in the Twenty-First Century by Thomas Piketty, Chris Urmson, Clayton Christensen, clean water, cloud computing, collateralized debt obligation, computer age, debt deflation, deskilling, diversified portfolio, Erik Brynjolfsson, factory automation, financial innovation, Flash crash, Fractional reserve banking, Freestyle chess, full employment, Goldman Sachs: Vampire Squid, High speed trading, income inequality, indoor plumbing, industrial robot, informal economy, iterative process, Jaron Lanier, job automation, John Maynard Keynes: technological unemployment, John von Neumann, Khan Academy, knowledge worker, labor-force participation, labour mobility, liquidity trap, low skilled workers, low-wage service sector, Lyft, manufacturing employment, McJob, moral hazard, Narrative Science, Network effects, new economy, Nicholas Carr, Norbert Wiener, obamacare, optical character recognition, passive income, performance metric, Peter Thiel, Plutocrats, plutocrats, post scarcity, precision agriculture, price mechanism, Ray Kurzweil, rent control, rent-seeking, reshoring, RFID, Richard Feynman, Richard Feynman, Rodney Brooks, secular stagnation, self-driving car, Silicon Valley, Silicon Valley startup, single-payer health, software is eating the world, sovereign wealth fund, speech recognition, Spread Networks laid a new fibre optics cable between New York and Chicago, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steven Levy, Steven Pinker, strong AI, Stuxnet, technological singularity, telepresence, telepresence robot, The Bell Curve by Richard Herrnstein and Charles Murray, The Coming Technological Singularity, Thomas L Friedman, too big to fail, Tyler Cowen: Great Stagnation, union organizing, Vernor Vinge, very high income, Watson beat the top human players on Jeopardy!, women in the workforce

Likewise, automated trading algorithms are now responsible for nearly two-thirds of stock market trades, and Wall Street firms have built huge computing centers in close physical proximity to exchanges in order to gain trading advantages measured in tiny fractions of a second. Between 2005 and 2012, the average time to execute a trade dropped from about 10 seconds to just 0.0008 seconds,56 and robotic, high-speed trading was heavily implicated in the May 2010 “flash crash” in which the Dow Jones Industrial Average plunged nearly a thousand points and then recovered for a net gain, all within the space of just a few minutes. Viewed from this perspective, financialization is not so much a competing explanation for our seven economic trends; it is rather—at least to some extent—one of the ramifications of accelerating information technology.

 

pages: 261 words: 86,905

How to Speak Money: What the Money People Say--And What It Really Means by John Lanchester

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asset allocation, Basel III, Bernie Madoff, Big bang: deregulation of the City of London, bitcoin, Black Swan, blood diamonds, Bretton Woods, BRICs, Capital in the Twenty-First Century by Thomas Piketty, Celtic Tiger, central bank independence, collapse of Lehman Brothers, collective bargaining, credit crunch, Credit Default Swap, crony capitalism, Dava Sobel, David Graeber, disintermediation, double entry bookkeeping, en.wikipedia.org, estate planning, financial innovation, Flash crash, forward guidance, Gini coefficient, global reserve currency, high net worth, High speed trading, hindsight bias, income inequality, inflation targeting, interest rate swap, Isaac Newton, Jaron Lanier, joint-stock company, joint-stock limited liability company, Kodak vs Instagram, liquidity trap, London Interbank Offered Rate, London Whale, loss aversion, margin call, McJob, means of production, microcredit, money: store of value / unit of account / medium of exchange, moral hazard, neoliberal agenda, New Urbanism, Nick Leeson, Nikolai Kondratiev, Nixon shock, Northern Rock, offshore financial centre, oil shock, open economy, paradox of thrift, Plutocrats, plutocrats, Ponzi scheme, purchasing power parity, pushing on a string, quantitative easing, random walk, rent-seeking, reserve currency, Richard Feynman, Richard Feynman, road to serfdom, Ronald Reagan, Satoshi Nakamoto, security theater, shareholder value, Silicon Valley, six sigma, South Sea Bubble, sovereign wealth fund, Steve Jobs, The Chicago School, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, trickle-down economics, Washington Consensus, working poor, yield curve

Readers interested in finance are also spoiled by the quality of the writing. There’s no better place to start than with the work of Michael Lewis, perhaps beginning with his first book, Liar’s Poker, an account of his job working as a bond trader at Salomon Brothers, and then skipping forward to The Big Short, a riveting description of the shenanigans behind the credit crunch. His most recent book, Flash Boys, is an account of high-speed trading that will make your hair stand on end, if it hasn’t all fallen out from worry by the time you’ve finished reading it. Alice Shroeder’s The Snowball, a biography of Warren Buffett, is very different in tone and texture, but it brings in a lot of stories and information from the world of finance, as does Sebastian Mallaby’s More Money Than God, a (suprisingly and convincingly positive) study of hedge funds.

 

pages: 421 words: 110,406

Platform Revolution: How Networked Markets Are Transforming the Economy--And How to Make Them Work for You by Sangeet Paul Choudary, Marshall W. van Alstyne, Geoffrey G. Parker

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3D printing, Affordable Care Act / Obamacare, Airbnb, Amazon Mechanical Turk, Amazon Web Services, Andrei Shleifer, Apple's 1984 Super Bowl advert, autonomous vehicles, barriers to entry, big data - Walmart - Pop Tarts, bitcoin, blockchain, business process, buy low sell high, chief data officer, clean water, cloud computing, connected car, corporate governance, crowdsourcing, data acquisition, data is the new oil, discounted cash flows, disintermediation, Edward Glaeser, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, financial innovation, Haber-Bosch Process, High speed trading, Internet of things, inventory management, invisible hand, Jean Tirole, Jeff Bezos, jimmy wales, Khan Academy, Kickstarter, Lean Startup, Lyft, market design, multi-sided market, Network effects, new economy, payday loans, peer-to-peer lending, Peter Thiel, pets.com, pre–internet, price mechanism, recommendation engine, RFID, Richard Stallman, ride hailing / ride sharing, Ronald Coase, Satoshi Nakamoto, self-driving car, shareholder value, sharing economy, side project, Silicon Valley, Skype, smart contracts, smart grid, Snapchat, software is eating the world, Steve Jobs, TaskRabbit, The Chicago School, the payments system, Tim Cook: Apple, transaction costs, two-sided market, Uber and Lyft, Uber for X, winner-take-all economy, Zipcar

Yet the existence of arbitrage opportunities also highlights market inefficiencies. eBay now uses automated systems to provide spelling assistance, so sellers can have more confidence that they’ll receive what their items are worth. In a case like this, wise governance may disenfranchise a specific group of stakeholders, such as arbitrageurs, in order to increase the overall health of the ecosystem. High-speed trading on the New York Stock Exchange offers another example. Firms like Goldman Sachs use supercomputers to determine when an order placed in one market will spill over to another market. Then they swoop in to intercept the deal, buying low, selling high, and skimming the margin. This methodology gives a few market participants who can afford massive computing power an unfair advantage over others.35 Such asymmetric market power risks driving away players who feel cheated.

 

pages: 393 words: 115,263

Planet Ponzi by Mitch Feierstein

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Affordable Care Act / Obamacare, Albert Einstein, Asian financial crisis, asset-backed security, bank run, banking crisis, barriers to entry, Bernie Madoff, centre right, collapse of Lehman Brothers, collateralized debt obligation, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Daniel Kahneman / Amos Tversky, disintermediation, diversification, Donald Trump, energy security, eurozone crisis, financial innovation, financial intermediation, Flash crash, floating exchange rates, frictionless, frictionless market, high net worth, High speed trading, illegal immigration, income inequality, interest rate swap, invention of agriculture, Long Term Capital Management, moral hazard, mortgage debt, Northern Rock, obamacare, offshore financial centre, oil shock, pensions crisis, Plutocrats, plutocrats, Ponzi scheme, price anchoring, price stability, purchasing power parity, quantitative easing, risk tolerance, Robert Shiller, Robert Shiller, Ronald Reagan, too big to fail, trickle-down economics, value at risk, yield curve

Speaking as a financial expert, I’d say that $2 billion is quite a lot of money. Can you imagine operating a bank with risk management systems so slipshod that you can simply lose $2 billion? Do you not think that somebody might have noticed after, let’s say, the first few hundred million went missing? It’s astonishing how much money Wall Street handles – and how chaotic its control systems continue to be. 29 Javier Blas, ‘High-speed trading blamed for sugar rises,’ Financial Times, Feb. 8, 2011. 30 Peter Guest, ‘Volatility will go on in world’s largest cocoa supplier,’ CNBC News, April 28, 2011. Chapter 11: Collecting nickels in front of steamrollers 1 Michael Lewis, The Big Short (Allen Lane, 2010), p. 62. 2 Lewis, The Big Short, p. 61 3 Lewis, The Big Short, p. 63. See also Max Abelson, ‘Mr. Bubble bounces back,’ New York Observer, Sept. 7, 2011. 4 See an interesting discussion by Steven Malliaris and Hongjun Yan of the Yale School of Management: ‘Nickels versus black swans: reputation, trading strategies and asset prices,’ March 2009.

 

pages: 584 words: 187,436

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

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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, capital controls, Carmen Reinhart, collapse of Lehman Brothers, collateralized debt obligation, 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, Kenneth Rogoff, Long Term Capital Management, margin call, market bubble, market clearing, market fundamentalism, merger arbitrage, moral hazard, natural language processing, Network effects, new economy, Nikolai Kondratiev, pattern recognition, pre–internet, quantitative hedge fund, quantitative trading / quantitative finance, random walk, Renaissance Technologies, Richard Thaler, risk-adjusted returns, risk/return, rolodex, Sharpe ratio, short selling, Silicon Valley, South Sea Bubble, sovereign wealth fund, statistical arbitrage, statistical model, technology bubble, The Great Moderation, The Myth of the Rational Market, too big to fail, transaction costs

Whereas Morgan had searched for complex nonlinear patterns and found little of interest, Shaw quickly identified promising anomalies. Much as with the Simons team, the ghosts that Shaw discovered were hard to explain: When he found recurring patterns and printed them out, there were no familiar terms that could be used to make sense of the squiggles on the paper. The effects were so far from being intuitive that Shaw had no need for high-speed trading systems: He did not need to get orders to market faster than rivals because he was confident that he would have none.10 Pretty soon, the profits started to roll in, and Shaw outgrew the premises in Greenwich Village. He moved to a loft in the Flatiron District in 1989 and then to a futuristic tower on West Forty-fifth Street two years later; meanwhile, Morgan Stanley’s frustrated bosses closed down the Analytical Proprietary Trading unit.

 

pages: 677 words: 206,548

Future Crimes: Everything Is Connected, Everyone Is Vulnerable and What We Can Do About It by Marc Goodman

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23andMe, 3D printing, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, airport security, Albert Einstein, algorithmic trading, artificial general intelligence, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Bill Joy: nanobots, bitcoin, Black Swan, blockchain, borderless world, Brian Krebs, business process, butterfly effect, call centre, Chelsea Manning, cloud computing, cognitive dissonance, computer vision, connected car, corporate governance, crowdsourcing, cryptocurrency, data acquisition, data is the new oil, Dean Kamen, disintermediation, don't be evil, double helix, Downton Abbey, Edward Snowden, Elon Musk, Erik Brynjolfsson, Filter Bubble, Firefox, Flash crash, future of work, game design, Google Chrome, Google Earth, Google Glasses, Gordon Gekko, high net worth, High speed trading, hive mind, Howard Rheingold, hypertext link, illegal immigration, impulse control, industrial robot, Internet of things, Jaron Lanier, Jeff Bezos, job automation, John Harrison: Longitude, Jony Ive, Julian Assange, Kevin Kelly, Khan Academy, Kickstarter, knowledge worker, Kuwabatake Sanjuro: assassination market, Law of Accelerating Returns, Lean Startup, license plate recognition, litecoin, M-Pesa, Mark Zuckerberg, Marshall McLuhan, Menlo Park, mobile money, more computing power than Apollo, move fast and break things, Nate Silver, national security letter, natural language processing, obamacare, Occupy movement, Oculus Rift, offshore financial centre, optical character recognition, pattern recognition, personalized medicine, Peter H. Diamandis: Planetary Resources, Peter Thiel, pre–internet, RAND corporation, ransomware, Ray Kurzweil, refrigerator car, RFID, ride hailing / ride sharing, Rodney Brooks, Satoshi Nakamoto, Second Machine Age, security theater, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, Skype, smart cities, smart grid, smart meter, Snapchat, social graph, software as a service, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, Stuxnet, supply-chain management, technological singularity, telepresence, telepresence robot, Tesla Model S, The Wisdom of Crowds, Tim Cook: Apple, trade route, uranium enrichment, Wall-E, Watson beat the top human players on Jeopardy!, Wave and Pay, We are Anonymous. We are Legion, web application, WikiLeaks, Y Combinator, zero day

Chapter 16: Next-Generation Security Threats: Why Cyber Was Only the Beginning 1 “had become so fragmented”: Nina Golgowski, “ ‘Syrian Hackers’ Tweet FALSE Report of Explosions at White House and Send Panicked DOW Jones Plunging 100 Points,” Mail Online, April 23, 2013; Jim McTague, “Why High-Frequency Trading Doesn’t Compute,” Barron’s, Aug. 11, 2012; Shan Carter and Amanda Cox, “One 9/11 Tally,” New York Times, Sept. 8, 2011; Doug Stanglin and David Jackson, “Timeline of AP Hacking, Reaction,” USA Today, April 23, 2013; Will Oremus, “Would You Click the Link in This Email That Apparently Tricked the AP,” Slate, April 23, 2013; Tom Lauricella, Kara Scanell, and Jenny Strasburg, “How a Trading Algorithm Went Awry,” Wall Street Journal, Oct. 2, 2010; Bernard Condon, “Stocks Stumble After a Fake Tweet Announced White House Attack,” Associated Press, April 25, 2013; Nick Baumann, “Too Fast to Fail: Is High-Speed Trading the Next Wall Street Disaster?,” Mother Jones, Jan/Feb. 2013. 2 The legendary Silicon Valley entrepreneur: Vinod Khosla, “Do We Need Doctors or Algorithms?,” TechCrunch, Jan. 10, 2012. 3 Today, artificial intelligence e-discovery: Rachael King, “Artificial Intelligence May Reduce Soaring E-discovery Costs,” CIO Journal, Oct. 29, 2013. 4 Just one algorithm alone: Amy Biegelsen, “Unregulated FICO Has Key Role in Each American’s Access to Credit,” Center for Public Integrity, May 17, 2011. 5 In a study: Adam D.