Prophecy: Prediction, Power, and the Fight for the Future, from Ancient Oracles to AI
by Carissa Véliz · 21 Apr 2026 · 503pp · 129,255 words
together).” Not content with such a bold statement, he went for an even more audacious prediction: “Consequently I think AI forecasters will soon automate most prediction markets.”[7] Less than a day later, the post had more than half a million views. And a rebuttal. Another AI researcher had tried their code
Stocks for the Long Run, 4th Edition: The Definitive Guide to Financial Market Returns & Long Term Investment Strategies
by Jeremy J. Siegel · 18 Dec 2007
recessions! PA U L S A M U E L S O N , 1 9 6 6 1 I’d love to be able to predict markets and anticipate recessions, but since that’s impossible, I’m as satisfied to search out profitable companies as Buffett is. P E T E R
Networks, Crowds, and Markets: Reasoning About a Highly Connected World
by David Easley and Jon Kleinberg · 15 Nov 2010 · 1,535pp · 337,071 words
Markets with Exogenous Events . . . . . . . . . . . . . . . . . . . . . . . . . 702 22.2 Horse Races, Betting, and Beliefs . . . . . . . . . . . . . . . . . . . . . . . . 704 22.3 Aggregate Beliefs and the “Wisdom of Crowds” . . . . . . . . . . . . . . . . 710 22.4 Prediction Markets and Stock Markets . . . . . . . . . . . . . . . . . . . . . 714 22.5 Markets with Endogenous Events . . . . . . . . . . . . . . . . . . . . . . . . 717 22.6 The Market for Lemons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 719 22.7 Asymmetric Information in Other Markets
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influence on how Web content is created. 26 CHAPTER 1. OVERVIEW 100 90 80 70 60 50 40 30 20 10 0 Figure 1.13: Prediction markets, as well as markets for financial assets such as stocks, can synthesize individual beliefs about future events into a price that captures the aggregate of
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restricted to markets for financial assets such as stocks. Recent work, for example, has explored the design of 1.2. CENTRAL THEMES AND TOPICS 27 prediction markets that use a market mechanism to provide predictions of future events such as the outcomes of elections. Here, participants in the market purchase assets that
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opinions about events in settings where the underlying events are exogenous — the probabilities of the events are not affected by the outcomes in the market. Prediction markets are one basic example of this setting. These are markets for (generally very simple) assets which have been created to aggregate individuals’ predictions about a
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the most well-known uses of prediction markets has been for the forecasting of 22.1. MARKETS WITH EXOGENOUS EVENTS 703 election results. For example, the Iowa Electronic Markets1 ran a market (one
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belief. Betting markets for sporting events such as horse races are also markets that aggregate diverse opinions into a price. As is the case with prediction markets, the outcome of the sporting event is independent of the betting behavior of the participants. Of course, some bettors may have more accurate beliefs than
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there is no cheating, what happens in the betting market does not affect the outcome of the sporting event. Markets for stocks are similar to prediction markets or betting at horse races, and we will use the understanding we develop for these betting markets to help us understand how the stock market
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B winning will converge to b. The state prices are weighted averages of these beliefs, so they too converge to a and b. 22.4 Prediction Markets and Stock Markets Thus far we have been telling a story about horse races, but there is a direct analogy to any market where participants
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purchase assets whose future value depends on the outcome of uncertain events. Two specific examples are prediction markets and — by far the most consequential application of these ideas — stock markets. In both cases, we will see that state prices play a key role
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in how we reason about what takes place in the market. Prediction Markets. In a prediction market, individuals trade claims to a one-dollar return conditional on the occurrence of some event. For example, as we discussed at the beginning of
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return in the event that a Democrat wins the next U.S. Presidential election. The institutional structure of prediction markets differs from the structure of a betting market at a race-track. In a prediction market individuals trade with each other through the market, while at a race track individuals place bets directly with
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cases the prices reflect an averaging of the beliefs of the participants in the market. Here, we will ignore the various institutional structures of prediction markets and instead see how much we can discover about them by applying our analysis of horse races via state prices. Consider, for example, the
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prediction market for the 2008 U.S. Presidential election with two possible outcomes: a Democrat wins or a Republican wins. (The same analysis can handle prediction markets with many plausible outcomes, such as the earlier prediction market for the identity of the Democratic and Republican nominees for
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President in 2008.) 22.4. PREDICTION MARKETS AND STOCK MARKETS 715 Let fn be the share of the total wealth bet
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on how wealth shares are distributed across those investors. One way to address this question empirically is to look at the predictions made by real prediction markets and ask how well they have done at predicting the outcome of actual events. An interesting paper by Berg, Nelson, and Rietz [50] shows that
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here is that stock markets, prediction markets, and betting markets are all essentially the same. They each give individuals the opportunity to place bets, and they all produce prices which can be
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advertise via search engines. 22.10 Advanced Material: Wealth Dynamics in Mar- kets When we considered markets for assets such as stocks, shares in a prediction market, or bets in a horse race, we observed that market prices serve to aggregate the beliefs of the market participants — essentially, the market produces a
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selects for the trader with the most accurate beliefs, and asymptotically prices assets according to these beliefs, applies equally well in other settings such as prediction markets. Notice that the argument here about the performance of the market is not based on the benefits of averaging, as in our previous discussion of
Trade Your Way to Financial Freedom
by van K. Tharp · 1 Jan 1998
predictable, then one would expect sunspot activity to have a strong effect on what happens in the market. There are numerous attempts to correlate and predict markets based upon major physical systems such as the activity of the sun. It is very easy to put together enough best-case examples to prove
Principles of Corporate Finance
by Richard A. Brealey, Stewart C. Myers and Franklin Allen · 15 Feb 2014
about issues as diverse as a presidential election, the weather, or the demand for a new product. FINANCE IN PRACTICE ● ● ● ● ● Prediction Markets Stock markets allow investors to bet on their favourite stocks. Prediction markets allow them to bet on almost anything else. These markets reveal the collective guess of traders on issues as diverse
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as New York City snowfall, an avian flu outbreak, and the occurrence of a major earthquake. Prediction markets are conducted on the majorfutures exchanges and on a number of smaller online exchanges such as Intrade (www.intrade.com) and the Iowa Electronic Markets
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by the fall of 2011 the price had climbed to $.66. Investors, it seemed, had become increasingly pessimistic about the currency’s prospects. Participants in prediction markets are putting their money where their mouth is. So the forecasting accuracy of these markets compares favorably with those of major polls. Some businesses have
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also formed internal prediction markets to survey the views of their staff. For example, Google operates an internal market to forecast product launch dates, the number of Gmail users, and
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other strategic questions.* *Google’s experience is analyzed in B. Cowgill, J. Wolfers, and E. Zitzewitz, “Using Prediction Markets to Track Information Flows: Evidence from Google,” Working paper, Dartmouth College, January 2009 Lesson 4: There Are No Financial Illusions In an efficient market there
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, 865 Forecasts cash flow, 24–25, 107–108, 138, 488 earnings per share, 312–313 economic rents in, 278–288 market values in, 273–278 prediction markets, 338 Foreign bonds, 616–617 Foreign Credit Insurance Association (FCIA), 786 Foreign exchange risk, 693–710 basic relationships, 695–704 economic exposure, 705–706 foreign
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–170, 171–174 Position diagrams, 514–515, 516–517 Postaudits, in capital budgeting process, 247–248 Postbank, 844 Poterba, J. M., 332n Powers, E., 842n Prediction markets, 338 Preferred stock, 356, 372 floating-rate, 797, 797n Premium, bond, 47 Prenegotiated bankruptcies, 854 Prepackaged bankruptcies, 854 Prescott, E. C., 184 Present value (PV
Learn Algorithmic Trading
by Sebastien Donadio · 7 Nov 2019
Stocks for the Long Run 5/E: the Definitive Guide to Financial Market Returns & Long-Term Investment Strategies
by Jeremy Siegel · 7 Jan 2014 · 517pp · 139,477 words
the Business Cycle The stock market has predicted nine out of the last five recessions. —PAUL SAMUELSON, 19661 I’d love to be able to predict markets and anticipate recessions, but since that’s impossible, I’m as satisfied to search out profitable companies as Buffett is. —PETER LYNCH, 19892 A well
On the Edge: The Art of Risking Everything
by Nate Silver · 12 Aug 2024 · 848pp · 227,015 words
its own terms. As you’ll see, I have complicated feelings about it. Act 4: Berkeley, California, September 2023. Set at Manifest, a conference on prediction markets—where you’ll meet everyone from a rationalist former OnlyFans model to a man who made hundreds of thousands of dollars betting on Biden even
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utilitarianism. The second is associated with Yudkowsky and the George Mason University economist Robin Hanson and a whole different cluster of topics: futurism, artificial intelligence, prediction markets, and being willing to argue about just about anything on the internet, including subjects that others often find taboo. Let’s start with the Singer
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MacAskill, Toby Ord Robin Hanson, Eliezer Yudkowsky, Nick Bostrom, Scott Alexander Favorite Subjects Animal welfare, global poverty reduction, effective giving, existential risk Artificial intelligence, futurism, prediction markets, cognitive biases, existential risk Political Orientation Center left, progressive, relatively well aligned with U.S. Democratic Party Libertarian, eclectic, suspicious of major parties Ethical Philosophy
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make probabilistic bets on real-world events. This might seem like a relatively obscure interest, but people in the EA/rationalist community are obsessed with prediction markets. Why? Partly because of their economist-brain appreciation for markets in general. But also because they believe we’ll have more accurate and honest discussions
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mean, and you’ll often be criticized even if your probabilities are as accurate as advertised.) There’s another reason that EAs and rationalists think prediction markets are important. It gets at the very definition of rationality itself. If you look up “rational” in a thesaurus, you’ll find that it’s
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in The Signal and the Noise, making testable predictions is one of the only ways to know whether you’re epistemically rational. So in theory, prediction markets play an important role in making the world more rational. But what about in practice? My views are mostly sympathetic, but not without some reservations
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. That’s in part because of some scar tissue from too many arguments I’ve had on the internet about the accuracy of prediction markets versus FiveThirtyEight forecasts. The FiveThirtyEight forecasts have routinely been better—I know that’s what you were expecting me to say, but it’s true
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to happen if the markets are efficient. Then again, maybe this doesn’t tell us that much. Elections are quite literally the Super Bowl of prediction markets—there’s so much dumb money out there (lots of people who have very strong opinions about politics) that there isn’t necessarily enough smart
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bet millions on Donald Trump after Joe Biden had already been declared the winner (we’ll get to that shortly). In many other circumstances, though, prediction markets are clearly quite useful. As news organizations scrambled to correct their coverage, for instance, traders at Manifold determined that the IDF probably hadn’t been
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responsible for whatever had happened on that particular night at the Gaza hospital.[*19] But the bigger concern I have, ironically enough, is that prediction markets may become less reliable if people trust them too much. When I spoke with MacAskill after the FTX collapse and asked him whether he ought
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had a debate on AI risk at Jane Street Capital in 2011, the firm that would later employ SBF. Some of the rationalist interest in prediction markets also stems from Hanson, who has expressed his support for futarchy, a system of government where decisions are made by betting markets. These various strands
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you’re going to get out of any one bite of the EA/rationalist cookie.[*24] If you’re someone like me who (mostly) likes prediction markets and thinks the concerns about existential risk and effective giving are well-placed, but is uncertain about futurism and downright wary about utilitarianism, it’s
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to Polymarket. The negotiations were not underway at the time I originally researched and wrote this chapter. *19 I’m also skeptical that play-money prediction markets can be as efficient as real-money ones. Still, as Austin Chen pointed out to me, rationalists are exactly the sort of people who care
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—although Riverians do have some similar ideas of their own. See also: Chesterton’s fence. Prediction market: A platform where people may bet on the outcome of real-world events, from presidential elections to personal occurrences. Prediction markets are highly regarded in the River because they are seen as promoting epistemic rationality, i.e
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: Kevin Roose, “The Wager That Betting Can Change the World,” The New York Times, October 8, 2023, sec. Technology, nytimes.com/2023/10/08/technology/prediction-markets-manifold-manifest.html. GO TO NOTE REFERENCE IN TEXT Magic: The Gathering: “Zvi Mowshowitz,” MTG Wiki, December 30, 2023, mtg.fandom.com/wiki/Zvi_Mowshowitz
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spoke with Habryka in an interview we arranged after Manifest, not during the event. GO TO NOTE REFERENCE IN TEXT prices that implied: Vitalik Buterin, “Prediction Markets: Tales from the Election,” Vitalik Buterin’s Website (blog), February 18, 2021, vitalik.eth.limo/general/2021/02/18/election.html. GO TO NOTE REFERENCE
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, 414 optimism and, 407–8, 413 poker and, 40, 46–48, 60–61, 430–33, 437, 439, 507n poor interpretability of, 433–34, 437, 479 prediction markets and, 369, 372 probabilistic thinking and, 439 randomization and, 438 rationalism and, 353, 355 regulation of, 270, 458, 541n religion and, 434 risk impact and
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and, 358–59, 366–67, 377 independence and, 358 overfitting/underfitting and, 361, 361, 362–68 poker and, 347–48, 367 politics and, 377–78 prediction markets and, 369 quantification and, 345–51, 359–60 rationalism and, 354–55 River and, 343 River-Village conflict and, 377 SBF and, 20, 340–42
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, 135–37, 158, 180 MacAskill, Will effective altruism brand and, 352 futurism and, 380 impartiality and, 359 longtermism and, 488 Elon Musk and, 344 on prediction markets, 373–74 quantification and, 347–48 SBF and, 20, 340, 341 on statistical modeling, 360–61 utilitarianism and, 378 Mac Aulay, Tara, 338, 400 Machine
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–21, 511n Elon Musk’s strategy, 251 origins of, 40 personality and, 111–17, 129–30 PokerGO studio, 48–49 post-oak bluffing, 64–65 prediction markets and, 370–71 preparation and, 233 prisoner’s dilemma and, 56–57, 508n privilege and, 82–83, 120–21 probabilistic thinking and, 41, 104–5
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forecasting, 13–14, 16–17, 27, 137, 182n, 433, 448n EV maximizing and, 14–15 expertise and, 272 gambling and, 17, 504n NFTs and, 326 prediction markets and, 373, 374–75, 535n probabilistic thinking and, 15, 17 reference classes and, 448n River-Village conflict and, 27–28, 29, 30, 267–68, 271
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(poker), 493 Pot-Limit Omaha (PLO), 487, 493 Poundstone, William, 396 Power Law, The (Mallaby), 286 precautionary principle, 493 Precipice, The (Ord), 369–70, 443 prediction markets, 369–75, 380, 493, 535n preflop (poker), 41, 493 preparation, 232–33 price discovery, 493 priors, 493–94; see also Bayes’ theorem prisoner’s dilemma
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, 264, 482 distribution, 9, 491 effective altruism and, 367 importance of, 15–16 poker and, 41, 104–5, 127, 154n, 237 politics and, 15, 17 prediction markets, 369–75, 493, 535n slots and, 153–55, 155 sports betting and, 16–17 theory invention, 22 See also EV maximizing probability distribution, 494 process
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existential risk and, 21, 457 defined, 352–53, 354, 495 effective hedonism and, 376 futurism and, 379 impartiality and, 377 politics and, 17, 377–78 prediction markets and, 369, 372–73, 380 River and, 343 tech sector and, 21 Upriver and, 20 utilitarianism and, 364 varying streams of, 355–56, 356, 380
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, 29, 117, 506n Las Vegas veneration of, 139 map of, 18, 19, 20–26 megalothymia and, 468 name of, 18, 42, 504n obsession and, 196 prediction markets and, 371–72, 493 process-oriented thinking and, 495 quantification and, 352 race and, 29, 506n rationalism and, 343 SBF’s presence in, 299 self
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, 346, 357, 400, 499 Truman, Harry S., 409 Trump, Donald casinos and, 142, 145, 146, 150–52, 514n effective altruism on, 378 NFTs and, 326 prediction markets and, 373, 375, 535n River and, 299 River-Village conflict and, 267–68 Silicon Valley and, 272 Peter Thiel and, 254n Village on, 30 Billy
Blockchain Revolution: How the Technology Behind Bitcoin Is Changing Money, Business, and the World
by Don Tapscott and Alex Tapscott · 9 May 2016 · 515pp · 126,820 words
Retail Banking Google Translate for Business: New Frameworks for Accounting and Corporate Governance Reputation: You Are Your Credit Score The Blockchain IPO The Market for Prediction Markets Road Map for the Golden Eight CHAPTER 4: Re-architecting the Firm: The Core and the Edges Building ConsenSys Changing the Boundaries of the Firm
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company. They can represent equity, bonds, or, in the case of Augur, market-maker seats on the platform, granting owners the right to decide which prediction markets the company will open. Ethereum was an even greater success than Augur, funding the development of a whole new blockchain through a crowd sale of
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financial record keeping while making it cheaper and more accurate,”81 but evidently NASDAQ and other incumbents have bigger plans. THE MARKET FOR PREDICTION MARKETS Augur is building a decentralized prediction market platform that rewards users for correctly predicting future events—sporting events, election results, new product launches, the genders of celebrity babies. How
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In other words, Augur brings the spirit of the market to bear on the accuracy of predictions. There have been a few attempts at centralized prediction markets, such as the Hollywood Stock Exchange, Intrade, and HedgeStreet (now Nadex), but most have been shut down or failed to launch over regulatory and legal
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: the more reputation points you have, the more markets you can make, and thus the more fees you can charge. In Augur’s words, “our prediction markets eliminate counterparty risks, centralized servers, and create a global market by employing cryptocurrencies including bitcoin, ether, and stable cryptocurrencies. All funds are stored in smart
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contracts by having a zero-tolerance policy for crime. To Augur’s leadership team, human imagination is the only practical limit to the utility of prediction markets. On Augur, anyone can post a clearly defined prediction about anything with a clear end date—from the trivial, “Will Brad Pitt and Angelina Jolie
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farmer in Nicaragua or Kenya who has no robust tools to hedge against currency risk, political risk, or changes to the weather and climate. Accessing prediction markets would allow that person to mitigate the risk of drought or disaster. For example, he could buy a prediction contract that pays out if a
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crop yield is below a certain level, or if the country gets less than a predetermined amount of rain. Prediction markets are useful for investors who want to place bets on the outcome of specific events such as “Will IBM beat its earnings by at least
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so-called expert analysts. By harnessing the wisdom of the crowds, we can form more realistic predictions of the future, leading to more efficient markets. Prediction markets can serve as a hedge against global uncertainty and “black swan” events: “Will Greece’s economy shrink by more than 15 percent this year?”84
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Today, we rely on a few talking heads to sound the alarms; a prediction market would act more impartially as an early warning system for investors globally. Prediction markets could complement and ultimately transform many aspects of the financial system. Consider prediction markets on the outcomes of corporate actions—earnings reports, mergers, acquisitions, and changes in
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management. Prediction markets would inform the insurance of value and the hedging of risk, potentially even
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Reddit discussion forum, plagued of late by controversy over its centralized control; a document formation and management system for self-enforcing contracts (aka smart contracts); prediction markets for business, sports, and entertainment; an open energy market; a distributed music model to compete with Apple and Spotify, though those two firms could use
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implement internal consensus mechanisms whereby all stakeholders vote on mission-critical decisions to end the chorus of ignorance and denial of prior knowledge. Or use prediction markets to test scenarios. If you’re an executive of a future Enron, no scapegoating. As for New Jersey governor Chris Christie, good luck telling a
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impractically costly. David Chaum, inventor of the concept, said random-sample polling could produce more representative and reliable results than elections today regularly achieve.53 Prediction Markets The company Augur is using the blockchain to aggregate many small wagers about future events into powerful predictive models. With the right application, it could
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help create collaborative democracy. Governments could use prediction markets to engage citizens in helping better understand future scenarios, enabling governments to make better policy choices. Ethereum’s Vitalik Buterin discusses an alternative model of
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their democratic representatives in a two-stage process: First, pick some metric to determine their country’s success (like literacy or unemployment rate). Then, use prediction markets to select government policies designed to optimize the elected metric. Augur’s style of prediction making could engage citizens in making small choices that contribute
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assess the potential impacts on a range of factors, ranging from health, to the environment, to the economy. Prediction Markets: As we explained in the case of Augur, there are countless opportunities to use prediction markets for trading the outcome of events. Governments can use them to gain insight into many substantive questions: When
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–79 Golden Eight of, 61–63, 64, 86 identity issues, 61, 64, 78–79 paradoxes of traditional finance, 55–57 players in blockchain ecosystem, 285 prediction markets, 84–85 reputation and credit score, 79–82 retail services, 71–73 smart devices and IoT, 159 from stock exchanges to block exchanges, 63, 65
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Political balkanization, 212–13 Political parties, 210–11 Political reputations, 210–11 Porter, Michael, 110–11, 314n Power grids, 145–50 Prahalad, C. K., 110 Prediction markets, 84–85, 98, 220, 224–25 Pretty Good Privacy (PGP), 40 Privacy, 27–28, 41–45, 141 bAirbnb and, 116 Big Brother, 244, 274–75
The Myth of the Rational Market: A History of Risk, Reward, and Delusion on Wall Street
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Cryptoassets: The Innovative Investor's Guide to Bitcoin and Beyond: The Innovative Investor's Guide to Bitcoin and Beyond
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The Business Blockchain: Promise, Practice, and Application of the Next Internet Technology
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The Permanent Portfolio
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Plenitude: The New Economics of True Wealth
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The Power of Passive Investing: More Wealth With Less Work
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Blockchain: Blueprint for a New Economy
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Here Comes Everybody: The Power of Organizing Without Organizations
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One Up on Wall Street
by Peter Lynch · 11 May 2012
Digital Bank: Strategies for Launching or Becoming a Digital Bank
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The Techno-Human Condition
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The Transparent Society: Will Technology Force Us to Choose Between Privacy and Freedom?
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Ctrl Alt Delete: Reboot Your Business. Reboot Your Life. Your Future Depends on It.
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The Meritocracy Myth
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Global Catastrophic Risks
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What Money Can't Buy: The Moral Limits of Markets
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A New History of the Future in 100 Objects: A Fiction
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The Volatility Smile
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Life After Google: The Fall of Big Data and the Rise of the Blockchain Economy
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The Bitcoin Guidebook: How to Obtain, Invest, and Spend the World's First Decentralized Cryptocurrency
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Terms of Service: Social Media and the Price of Constant Connection
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Griftopia: Bubble Machines, Vampire Squids, and the Long Con That Is Breaking America
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The Penguin and the Leviathan: How Cooperation Triumphs Over Self-Interest
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Loonshots: How to Nurture the Crazy Ideas That Win Wars, Cure Diseases, and Transform Industries
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Range: Why Generalists Triumph in a Specialized World
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The Infinite Machine: How an Army of Crypto-Hackers Is Building the Next Internet With Ethereum
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Attack of the 50 Foot Blockchain: Bitcoin, Blockchain, Ethereum & Smart Contracts
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Pax Technica: How the Internet of Things May Set Us Free or Lock Us Up
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The Myth of Capitalism: Monopolies and the Death of Competition
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The Bank That Lived a Little: Barclays in the Age of the Very Free Market
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Economic Gangsters: Corruption, Violence, and the Poverty of Nations
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The Internet of Us: Knowing More and Understanding Less in the Age of Big Data
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The Future Is Asian
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The Deep Learning Revolution (The MIT Press)
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The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant From Two Centuries of Controversy
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The Handbook of Personal Wealth Management
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Starstruck: The Business of Celebrity
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Windfall: The Booming Business of Global Warming
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This Is Not Normal: The Collapse of Liberal Britain
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Eat People: And Other Unapologetic Rules for Game-Changing Entrepreneurs
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Know Thyself
by Stephen M Fleming · 27 Apr 2021
Number Go Up: Inside Crypto's Wild Rise and Staggering Fall
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Bleeding Edge: A Novel
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Confessions of a Crypto Millionaire: My Unlikely Escape From Corporate America
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Collaborative Futures
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