Designing Real Terrorism Futures

1. Designing Real Terrorism Futures Robin Hanson Department of Economics George Mason University

3. Information Markets = Idea Futures • Most speculative markets aggregate info well • Very hard to find info to beat average return • In direct comparisons, beat other institutions • Racetrack odds beat track experts (Figlewski 1979) • OJ futures improve weather forecast (Roll 1984) • Gas demand markets beat experts (Spencer 2004) • I.E.M. beat president polls 451/596 (Berg et al 2001) • HP market beat sales forecast 6/8 (Plott 2000) • Stocks beat Challenger panel (Maloney & Mulherin 2003)

4. Timeline - Policy Analysis Market 2000 DARPA conceives info market project Bush pres., RFP, begin Phase I ($100K) Poindexter heads IAO, with pet TIA Spring – start 2yr. Phase II ($750K) May – Congress report ex: Israel Bio Terror Plan: register 8/1, few test 9/1, open 1/1 7/28 – Senators complain: “repugnant" 7/29 – DARPA FutureMAP Killed 7/30 – Poindexter quits 2001 2002 2003

5. Policy Analysis Market • Every nation*quarter: • Political stability • Military activity • Economic growth • US $ aid • US military activity • & global, special • & all combinations

6. Return to Focus ? Trade IQcs4 IQcs4 < 85 85 03 03 SAum3 105-125 03 Update Payoffs: If & Ave. pay Select New Price 65% Max Up 95.13% +$34.74 -$85.18 -$19.72 Buy 10% Up 68.72% +$2.74 -$3.28 -$1.07 You Pick 65 % +1.43 -2.04 +0.34 Saudi Arabian Economic Health No Trade 62.47% $0.00 $0.00 $0.00 125 30 15 10% Dn 56.79% -$2.61 +$2.74 -$1.12 65 70 Sell Exit Issue 48.54% -$15.34 +$26.02 -$6.31 35 40 100 94 100 Max Dn 22.98% -$120.74 +$96.61 -$22.22 < 85 25 35 35 30 10 10 75 1 2 3 4 1 2 > 03 03 03 03 04 04 ? Return to Form Execute a Trade If US military involvement in Saudi Arabia in 3rd Quarter 2003 is not between 105 and 125, this trade is null and void. Otherwise, if Iraq civil stability in 4th Quarter 2003 is below 85, then I will receive $1.43, but if it is not below 85, I will pay $2.04. Abort trade if price has changed? Execute Trade Scenario

7. The Fuss: Analysts often use prices from various markets as indicators of potential events. The use of petroleum futures contract prices by analysts of the Middle East is a classic example. The Policy Analysis Market (PAM) refines this approach by trading futures contracts that deal with underlying fundamentals of relevance to the Middle East. Initially, PAM will focus on the economic, civil, and military futures of Egypt, Jordan, Iran, Iraq, Israel, Saudi Arabia, Syria, and Turkey and the impact of U.S. involvement with each. [Click here for a summary of PAM futures contracts] The contracts traded on PAM will be based on objective data and observable events. These contracts will be valuable because traders who are registered with PAM will use their money to acquire contracts. A PAM trader who believes that the price of a specific futures contract under-predicts the future status of the issue on which it is based can attempt to profit from his belief by buying the contract. The converse holds for a trader who believes the price is an over-prediction – she can be a seller of the contract. This price discovery process, with the prospect of profit and at pain of loss, is at the core of a market’s predictive power. The issues represented by PAM contracts may be interrelated; for example, the economic health of a country may affect civil stability in the country and the disposition of one country’s military may affect the disposition of another country’s military. The trading process at the heart of PAM allows traders to structure combinations of futures contracts. Such combinations represent predictions about interrelated issues that the trader has knowledge of and thus may be able to make money on through PAM. Trading these trader-structured derivatives results in a substantial refinement in predictive power. [Click here for an example of PAM futures and derivatives contracts] The PAM trading interface presents A Market in the Future of the Middle East. Trading on PAM is placed in the context of the region using a trading language designed for the fields of policy, security, and risk analysis. PAM will be active and accessible 24/7 and should prove as engaging as it is informative. Became:

8. PAM Press Of 500+ articles, these gave more favorable PAM impression: Article: later in time, more words, mentioned insider, news (not Editorial) style, not anonymous Publication: finance or science specialty, many awards, many readers

9. Terror Betting Is “Unthinkable” • We deny trade sacred for secular (P. Tetlock) • E.g., money vs. risk of death • Outraged at those we see do (really, we all do) • More outraged if they think a long time first • If catch ourselves, seek moral cleansing • PAM painted as crossing a moral boundary • “None of us should intend to benefit when they hurt some of us.” • So politicians must not think long before rejecting

10. PAM Concerns Terrorists themselves could drive up the market for an event they are planning and profit from an attack, or even make false bets to mislead intelligence authorities. U.S. Senators Wyden and Dorgan, Press Release, July 28, 2003. Would-be assassins and terrorists could easily use disinformation and clever trading strategies to profit from their planned misdeeds while distracting attention from their real target. Steven Pearlstein, Washington Post, July 30, 2003. Trading . . . could be subject to manipulation, particularly if the market has few participants – providing a false sense of security or . . . alarm. Joseph Stiglitz, Los Angeles Times, July 31, 2003.

11. Not Experts vs. Self-chosen Amateurs • Forecasting Institution Goal: • Given same participants, resources, topic • Want institution with accurate forecasts • Separate question: who let participate? • Can limit who can trade in market • Markets have low penalty for add fools • Hope: get more info from amateurs?

12. Six Design Issues • How avoid self-defeating prophecies? • How handle billions of possible combos? • What if terrorists lose $ to mislead us? • What if terrorists gain $ by give us info? • How not alarm public, inform terrorists? • Price can mislead if deciders know more.

13. 1. Self-Defeating Prophecies • Example • Speculators learn of possible airport attack • Market price of attack chance rises • Airport officials see price, close airport • Speculators are punished for their insight • Solution: predict outcome given choices • Predict terror attack given airport open

14. Security Policy Decision Advice $1 if Attack & Change Policy P(CP) $1 if Change Policy P(A | CP) $1 Compare! P(A | not CP) $1 if Not Change Policy $1 if Attack & Not Change Policy P(not CP)

15. Decision Market Applications E[ SA civil war | US moves troops out? ] E[ US terror deaths | dump Israel, Saudis ] E[ red team in | new building security ] E[ US terror deaths | halve DHS budget ] E[ firm stock price | fire CEO? ] Market costs start high, not depend on topic, so do big value questions first.

16. 2. Useful attack forecasts distinguish: • Thousands of possible locations • Hundreds of possible times • Dozens of methods of attack • Dozens of terrorism demographics • Dozens of policy responses • Many combinations for each attack • More combinations for many attacks

17. Simple Info Markets Market Scoring Rules Scoring Rules opinion pool problem thin market problem 100 .001 .01 .1 1 10 Best of Both Accuracy Estimates per trader

18. Combo Market Maker Best of 5 Mechs

19. 3. Manipulation • Lie (WorldCom) – hits all forecast institutions • Mix-it-up – slow reveal trade to max $ of info • Mislead – Terrorists lose $ to raise price error • Even if works, still useful if can calibrate accuracy • 0.1% prob. gain 0.1% of $500B/yr pays $1M PAM • Field, Lab agree: on ave manip. fails • Any trade not to info is “noise” trade • More noise trading => more accuracy! • Less error, more harm? Use price/harm linear

20. Simple Manipulation Model Kyle Style Market Microstructure Game Theory Market maker Manipulator Informed trader Noise trader Equilibrium

21. 4. Moral Hazard • Ever trading profits from sabotage? • Not: 9/11, ’82 Tylenol, ’02 PaineWebber • Yes: hacker extortion, life insurance kill • Hard to match willing capital & skilled labor • Terrorism futures differ: • Good: amounts of money very small • We’d pay $10 to know where robber hits next • Bad: individuals influence events more?

22. Solutions For High Stakes • Only play money, or winnings to charity • Limit who can play to trusted traders • Certified by reduce privacy? • Let investigators see trading records • Limit trading positions • E.g., gain no more than $20 if attack

23. 5. Hiding Prices • Prices may alarm public, inform bad guys • Traders not now know prices when order • Deal via: Limit orders, market orders, … • Can extend this to show less about price • Might hide prices re attack a week before • Orders specify how respond to price history • Trusted traders might see actual prices

24. 6. Decision Selection Bias • If traders think deciders will use info that traders do not have • Then market advice can contradict trader info • Solution: • Let some with decider info trade • Make decision time clear to traders

25. Change Chance attack if no policy change Apparent center Do not change True center Chance attack if policy change

26. Terrorism Futures Seem Feasible, Technically If Not Politically 0) Not about experts vs. self-chosen amateurs • How avoid self-defeating prophecies? • How handle billions of possible combos? • What if terrorists lose $ to mislead us? • What if terrorists gain $ by give us info? • How not alarm public, inform terrorists? • Price can mislead if deciders know more.