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Who Gets What — and Why: The New Economics of Matchmaking and Market Design by Alvin E. Roth
Affordable Care Act / Obamacare, Airbnb, algorithmic trading, barriers to entry, Berlin Wall, bitcoin, Build a better mousetrap, centralized clearinghouse, Chuck Templeton: OpenTable:, commoditize, computer age, computerized markets, 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, uber lyft, undersea cable
When my wife and I bought a house that we found without a broker, the seller had already signed a contract with a broker that fixed the total brokerage fee. When it came time to close the deal, we engaged a broker from the firm Redfin, which refunds half of its share of the fee to the buyer. That is far from an efficient adaptation to a changing world, but it’s a start. Computerized Markets Although the Internet has so far failed to transform the housing market, computerized markets have, as we have seen, made enormous changes in other areas. Computers not only make markets ubiquitous and fast; they also make it possible to operate “smart markets” that depend on computational power. Neither kidney exchanges nor “package bidding” auctions would be possible if computers weren’t there to handle the gnarly calculations needed to find the best way to match lots of patient-donor pairs with one another, or to find the set of packages of spectrum licenses that will raise the most revenue at each point in the bidding.
The English language gives us a head start on that, speaking as it does not only of job markets but also of marriage markets. Index Abdulkadiroğlu, Atila, 35, 107, 153 on school choice, 126–28, 165, 241, 243 activity rules, 187–88 advertising, targeted, 189–92 “Advice to a Young Tradesman, Written by an Old One” (Franklin), 200–201 Affordable Care Act, 224 Airbnb, 99–103, 116 algorithms Boston Public Schools, 122–28 computerized markets and, 225–26 deferred acceptance, 141–44 in Boston Public Schools system, 162–65 in New York school choice program, 155–61 for financial marketplaces, 82–89 Internet dating sites, 176–77 kidney exchange, 35–38, 39–41 for medical residencies, 136–43 Roth-Peranson, 148–49 stable outcomes from, 139–43 Alliance for Paired Donation, 44, 49 Amazon, 20–21, 22 congestion management in, 24 simplicity in, 26 American Economic Association, 174, 175 Android, 21–22 anonymity, in commodity markets, 19–20 antibiotics, 133–34 Apple, 19 iPhone, 21–22, 24 application and selection processes, 5.
See also National Resident Matching Program (NRMP) for British medical interns, 140–41 for medical residencies, 136–50 New York City school system, 112 in New York school choice program, 155–61 preferences information for, 34 stable outcomes with, 139–43 trading cycles and, 32–41 Coca-Cola, 25 coercion, 203, 208 coffee, 17–19 Coles, Peter, 244 college admissions, 5–6 acceptance rates in, 172 campus visits in, 178 deferred acceptance algorithm in, 141–43 early, 171–72 signaling in, 169, 170–73 strategic decision making in, 10 “College Admissions and the Stability of Marriage” (Gale & Shapley), 141–43, 158, 241, 242 college bowl games, 59–65 College Football Playoff, 64 Commodity Futures Trading Commission, 85 commodity markets, 228 coffee, 17–19 congestion in, 111–12 differentiation and, 18–20 financial, 82–89 grading systems for, 16–18 markets for, 5 price-based markets for, 9–10 standardization of, 17–18, 19–20 wheat, 15–17 Common Application, 170–73 communication, 169–92. See also information; signals and signaling cheap talk in, 176–77 costly signals in, 177–89 speed of, 99–106 competition early transactions and, 57–80 exploding offers and, 9–10 for medical school graduates, 135–36 price-based vs. speed-based, 85–88 simplicity in, 26–27 speed in, 81–99 computerized markets, 225–26 “Confessions of a Bad Apple” (Kozinski), 93 congestion, 9–10, 92–93, 99–112 commodity markets and, 17 credit cards and, 24 dangers of, 106 in economics job market, 174–75 for judicial clerkships, 91–93 kidney exchanges and, 51, 52 in limited-time markets, 80 New York City school system, 106–10, 112 in the Oklahoma Land Rush, 57–59 in restaurants, 218–20, 221 signaling and, 179 conscription, 203 contract law, 222, 225 Cook, Gareth, 126, 241 Cook, Walter, 58, 59, 80 cookies, Internet, 191–92 costly signals, 177–89.
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
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. That’s a pretty powerful argument in favor of computerization. No wonder Lewis buried it under a pile of fractions, and then topped the grave with a non sequitur about liquidity. Lewis doesn’t want to dwell on the possibility that high-frequency market-makers have made the trading costs of the bid-offer spread six times lower for investors. Instead, he quickly launches into a meaningless tangent to say that increased trading volume doesn’t mean better markets.
He dismisses the role of high-frequency trading in this improvement with the claim that the spread would have narrowed anyway “with the automation of the stock market.” What does this mean? Exchanges, automated or not, don’t make prices – market participants do. Presumably, then, Lewis means the automation of stock market participants caused trading costs to plummet. If he is arguing that market participants started using computers to automate trading and this resulted in narrower spreads, then he is right – and these automated, computerized market-makers sound an awful lot like high-frequency traders. It’s no coincidence that one of the original high-frequency trading firms was called Automated Trading Desk. So, yes, automation in the stock market has narrowed spreads. That’s exactly what high-frequency market-makers do. Lewis’ final fallback position is that the narrower spreads today aren’t really real, but are “an illusion.” His complaint is the same as in Chapter 2: “the minute you went to buy or sell at the stated market price, the price moved.”
In an industry awash in data, where millions of trades are analyzed every day, Lewis offers the lame excuse that he can’t find any data to prove his case because the data doesn’t exist. This is simply not credible. Lewis’ hypothetical examples of front-running also don’t work. Misunderstanding basic principles built-in to today’s markets, such as trade-through protection, price-time priority, and protection of order information, he conjures up scenarios that are impossible. The tricks of thirty years ago simply aren’t possible in today’s computerized markets, which automatically enforce these rules. Brokers can no longer stick a customer with an off-market price. All trades, broker or customer, must occur only at the prices set by the entire national market. Customer order information is only revealed if the customer chooses to do so. Lewis never even attempts to explain how a would-be front-runner guesses the quantity and price of a customer’s order, because he has no plausible explanation.
The Black Box Society: The Secret Algorithms That Control Money and Information by Frank Pasquale
Affordable Care Act / Obamacare, algorithmic trading, Amazon Mechanical Turk, American Legislative Exchange Council, asset-backed security, Atul Gawande, bank run, barriers to entry, basic income, Berlin Wall, Bernie Madoff, Black Swan, bonus culture, Brian Krebs, business cycle, call centre, Capital in the Twenty-First Century by Thomas Piketty, Chelsea Manning, Chuck Templeton: OpenTable:, cloud computing, collateralized debt obligation, computerized markets, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, crowdsourcing, cryptocurrency, Debian, don't be evil, drone strike, Edward Snowden, en.wikipedia.org, Fall of the Berlin Wall, Filter Bubble, financial innovation, financial thriller, fixed income, Flash crash, full employment, Goldman Sachs: Vampire Squid, Google Earth, Hernando de Soto, High speed trading, hiring and firing, housing crisis, informal economy, information asymmetry, 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, Marc Andreessen, Mark Zuckerberg, mobile money, moral hazard, new economy, Nicholas Carr, offshore financial centre, PageRank, pattern recognition, Philip Mirowski, precariat, profit maximization, profit motive, quantitative easing, race to the bottom, recommendation engine, regulatory arbitrage, risk-adjusted returns, Satyajit Das, search engine result page, shareholder value, Silicon Valley, Snapchat, social intelligence, 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, zero-sum game
The think tank Dēmos estimates that, over a lifetime, retirement account fees “can cost a median-income two-earner family nearly $155,000.”122 Investor John Bogle notes that a 2 percent fee applied over a 50-year investing lifetime would erode 63 percent of the value of an average account.123 Note, too, how the finance sector as a whole has little interest in stopping such wasteful activities. The more treacherous it becomes for outsiders to trade in the brave new world of computerized markets, the more they have to pay some knowledgeable insider a fee to fend off the piranhas. Also note here how signals about value are being transmitted. HFT’ers merely anticipate and mimic what others are doing, without exploring the underlying value of the company whose shares are being traded. This bare signaling is another version of the black box problems illuminated in credit ratings or credit default swaps.
Here, buy and sell signals can take on a life of their own, leading to momentum trading and herding.124 Algorithmic trading can create extraordinary instability and frozen markets when split-second trading strategies interact in unexpected ways.125 Consider, for instance, the flash crash of May 6, 2010, when the stock market lost hundreds of points in a matter of minutes.126 In a report on the crash, the CFTC and SEC observed that “as liquidity completely evaporated,” trades were “executed at irrational prices as low as one penny or as high as $100,000.”127 Traders had programmed split-second algorithmic strategies to gain a competitive edge, but soon found themselves in the position of a sorcerer’s apprentice, unable to control the technology they had developed.128 Though prices returned to normal the same day, there is no guarantee future markets will be so lucky. The Computerized Market HFT is the ultimate in fi nancial self-reference, where perceptions of value come entirely from signals encoded on trading terminals. Lately, the limiting factor in fast trading the speed of light in fiber optic cables. Thus fi rms are paying to construct ultrafast cables between fi nancial centers.129 Spread Networks spent over $200 million to lay a cable between Chicago and New York-area exchanges, estimating that fi rms could make $20 billion in a year exploiting price discrepancies (lasting less than a second) between the two cities.130 Modelers have devised more extreme solutions to the time delay problem.
Flash Boys: A Wall Street Revolt by Michael Lewis
automated trading system, bash_history, Berlin Wall, Bernie Madoff, collateralized debt obligation, computerized markets, drone strike, Fall of the Berlin Wall, financial intermediation, Flash crash, High speed trading, latency arbitrage, pattern recognition, risk tolerance, Rubik’s Cube, Sergey Aleynikov, Small Order Execution System, Spread Networks laid a new fibre optics cable between New York and Chicago, the new new thing, too big to fail, trade route, transaction costs, Vanguard fund
The argument in favor of high-frequency traders had beaten the argument against them to the U.S. regulators. It ran as follows: Natural investors in stocks, the people who supply capital to companies, can’t find each other. The buyers and sellers of any given stock don’t show up in the market at the same time, so they needed an intermediary to bridge the gap, to buy from the seller and to sell to the buyer. The fully computerized market moved too fast for a human to intercede in it, and so the high-frequency traders had stepped in to do the job. Their importance could be inferred from their activity: In 2005 a quarter of all trades in the public stock markets were made by HFT firms; by 2008 that number had risen to 65 percent. Their new market dominance—so the argument went—was a sign of progress, not just necessary but good for investors.
The Investopedia Guide to Wall Speak: The Terms You Need to Know to Talk Like Cramer, Think Like Soros, and Buy Like Buffett by Jack (edited By) Guinan
Albert Einstein, asset allocation, asset-backed security, Brownian motion, business cycle, business process, buy and hold, capital asset pricing model, clean water, collateralized debt obligation, computerized markets, correlation coefficient, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, discounted cash flows, diversification, diversified portfolio, dividend-yielding stocks, dogs of the Dow, equity premium, fixed income, implied volatility, index fund, intangible asset, interest rate swap, inventory management, London Interbank Offered Rate, margin call, money market fund, mortgage debt, Myron Scholes, passive investing, performance metric, risk tolerance, risk-adjusted returns, risk/return, shareholder value, Sharpe ratio, short selling, statistical model, time value of money, transaction costs, yield curve, zero-coupon bond
This regulation requires that lists be published that track stocks with unusually high trends in “fail to deliver” shares. Some analysts point to the fact that naked shorting, albeit inadvertently, may help markets stay in balance by allowing negative sentiment to be reflected in certain stocks’ prices. 193 194 The Investopedia Guide to Wall Speak Related Terms: • Margin • Regulation T—Reg T • Short Squeeze • Option • Stock Option Nasdaq What Does Nasdaq Mean? A computerized market or exchange that facilitates trading by providing price quotations on more than 5,000 actively traded overthe-counter stocks. Created in 1971, the Nasdaq was the world’s first electronic stock market. Stocks on the Nasdaq traditionally are listed by using four or five letters as their ticker symbols. If a company is a transfer from the New York Stock Exchange, the symbol may consist of three letters.
This Machine Kills Secrets: Julian Assange, the Cypherpunks, and Their Fight to Empower Whistleblowers by Andy Greenberg
Apple II, Ayatollah Khomeini, Berlin Wall, Bill Gates: Altair 8800, Burning Man, Chelsea Manning, computerized markets, crowdsourcing, cryptocurrency, domain-specific language, drone strike, en.wikipedia.org, fault tolerance, hive mind, Jacob Appelbaum, Julian Assange, Mahatma Gandhi, Mitch Kapor, MITM: man-in-the-middle, Mohammed Bouazizi, nuclear winter, offshore financial centre, pattern recognition, profit motive, Ralph Nader, Richard Stallman, Robert Hanssen: Double agent, Silicon Valley, Silicon Valley ideology, Skype, social graph, statistical model, stem cell, Steve Jobs, Steve Wozniak, Steven Levy, undersea cable, Vernor Vinge, We are Anonymous. We are Legion, We are the 99%, WikiLeaks, X Prize, Zimmermann PGP
Interactions over networks will be untraceable, via extensive re-routing of encrypted packets and tamper-proof boxes which implement cryptographic protocols with nearly perfect assurance against any tampering. . . . The State will of course try to slow or halt the spread of this technology, citing national security concerns, use of the technology by drug dealers and tax evaders, and fears of societal disintegration. Many of these concerns will be valid; crypto anarchy will allow national secrets to be traded freely and will allow illicit and stolen materials to be traded. An anonymous computerized market will even make possible abhorrent markets for assassinations and extortion. Various criminal and foreign elements will be active users of CryptoNet. But this will not halt the spread of crypto anarchy. Just as the technology of printing altered and reduced the power of medieval guilds and the social power structure, so too will cryptologic methods fundamentally alter the nature of corporations and of government interference in economic transactions.
How I Became a Quant: Insights From 25 of Wall Street's Elite by Richard R. Lindsey, Barry Schachter
Albert Einstein, algorithmic trading, Andrew Wiles, Antoine Gombaud: Chevalier de Méré, asset allocation, asset-backed security, backtesting, bank run, banking crisis, Black-Scholes formula, Bonfire of the Vanities, Bretton Woods, Brownian motion, business cycle, business process, butter production in bangladesh, buy and hold, buy low sell high, capital asset pricing model, centre right, collateralized debt obligation, commoditize, computerized markets, corporate governance, correlation coefficient, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, discounted cash flows, disintermediation, diversification, Donald Knuth, Edward Thorp, Emanuel Derman, en.wikipedia.org, Eugene Fama: efficient market hypothesis, financial innovation, fixed income, full employment, George Akerlof, Gordon Gekko, hiring and firing, implied volatility, index fund, interest rate derivative, interest rate swap, John von Neumann, linear programming, Loma Prieta earthquake, Long Term Capital Management, margin call, market friction, market microstructure, martingale, merger arbitrage, Myron Scholes, Nick Leeson, P = NP, pattern recognition, Paul Samuelson, pensions crisis, performance metric, prediction markets, profit maximization, purchasing power parity, quantitative trading / quantitative ﬁnance, QWERTY keyboard, RAND corporation, random walk, Ray Kurzweil, Richard Feynman, Richard Stallman, risk-adjusted returns, risk/return, shareholder value, Sharpe ratio, short selling, Silicon Valley, six sigma, sorting algorithm, statistical arbitrage, statistical model, stem cell, Steven Levy, stochastic process, systematic trading, technology bubble, The Great Moderation, the scientific method, too big to fail, trade route, transaction costs, transfer pricing, value at risk, volatility smile, Wiener process, yield curve, young professional
Rahl received her undergraduate degree in computer science from MIT in 1971 and her MBA from the Sloan School at MIT in 1972. Evan Schulman is chairman of Upstream Technologies LLC. Before Upstream, Mr. Schulman cofounded Lattice Trading, which was acquired by State Street Global Advisors in 1996. Lattice is an advanced alternative trading system that integrates order-matching with order-routing and connects to global computerized markets. In 1975, as director of Computer Research at Keystone Funds in Boston, he completed what is generally regarded as the first equity program trade. During the 1980s, Mr. Schulman developed computerized investment and trading systems at Batterymarch Financial Management. Currently, he is a director of Net Exchange. Mr. Schulman served in the Royal Canadian Air Force, received his BA from the University of Toronto, and his MA from the University of Chicago.
Surveillance Valley: The Rise of the Military-Digital Complex by Yasha Levine
23andMe, activist fund / activist shareholder / activist investor, Airbnb, AltaVista, Amazon Web Services, Anne Wojcicki, anti-communist, Apple's 1984 Super Bowl advert, bitcoin, borderless world, British Empire, call centre, Chelsea Manning, cloud computing, collaborative editing, colonial rule, computer age, computerized markets, corporate governance, crowdsourcing, cryptocurrency, digital map, don't be evil, Donald Trump, Douglas Engelbart, Douglas Engelbart, drone strike, Edward Snowden, El Camino Real, Electric Kool-Aid Acid Test, Elon Musk, fault tolerance, George Gilder, ghettoisation, global village, Google Chrome, Google Earth, Google Hangouts, Howard Zinn, hypertext link, IBM and the Holocaust, index card, Jacob Appelbaum, Jeff Bezos, jimmy wales, John Markoff, John von Neumann, Julian Assange, Kevin Kelly, Kickstarter, life extension, Lyft, Mark Zuckerberg, market bubble, Menlo Park, Mitch Kapor, natural language processing, Network effects, new economy, Norbert Wiener, packet switching, PageRank, Paul Buchheit, peer-to-peer, Peter Thiel, Philip Mirowski, plutocrats, Plutocrats, private military company, RAND corporation, Ronald Reagan, Ross Ulbricht, Satoshi Nakamoto, self-driving car, sentiment analysis, shareholder value, side project, Silicon Valley, Silicon Valley startup, Skype, slashdot, Snapchat, speech recognition, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, Telecommunications Act of 1996, telepresence, telepresence robot, The Bell Curve by Richard Herrnstein and Charles Murray, The Hackers Conference, uber lyft, Whole Earth Catalog, Whole Earth Review, WikiLeaks
They believed that powerful encryption and anonymity technology, combined with untraceable digital currencies, would bring a revolution that swept away government power and established a decentralized global world order based on free markets and voluntary association.56 “The State will of course try to slow or halt the spread of this technology, citing national security concerns, use of the technology by drug dealers and tax evaders, and fears of societal disintegration. Many of these concerns will be valid; crypto anarchy will allow national secrets to be traded freely and will allow illicit and stolen materials to be traded. An anonymous computerized market will even make possible abhorrent markets for assassinations and extortion,” predicted Timothy May, a bearded, pioneering engineer at Intel and one of the key founders of the cypherpunk movement, back in 1992. May proselytized his ideas with a messianic zeal. By 1994, he was predicting that a global cryptorevolution was just around the corner and that it would create a new world free of governments and centralized control.