1 / 31

Insider Trading and Prediction Markets

Insider Trading and Prediction Markets. Robin Hanson Associate Professor of Economics, GMU Insider Trading Syposium GMU, January 2007. Coordination. Coordinator Aides: Schedule meetings Collect stats Monitor others Research options Write reports, talks Review proposals

Mia_John
Download Presentation

Insider Trading and Prediction Markets

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Insider Trading and Prediction Markets Robin Hanson Associate Professor of Economics, GMU Insider Trading Syposium GMU, January 2007

  2. Coordination

  3. Coordinator Aides: Schedule meetings Collect stats Monitor others Research options Write reports, talks Review proposals Screen candidates Predict outcomes Make choices Coordination But: Lose Control, Leak Info, Ins. Tr. Law?

  4. Costs Scare ave. investor Less control info/pay Risk, Sabotage Benefits Better assign capital Subsidize info ties Less signaling Well-Informed Traders (WIT) (If no obvious externalities, let firm decide.)

  5. SEC Rules On WIT • Regular reports required • Disclose info to all or none • No trade if info not “available” to all • “Insider” = Top boss, investor, director • No short sell, no sell <6mo., report trades Failures: Most info not at reports, insider trades profit, analysts are WIT, … Arguably hinder info process innovation

  6. Other ways to stop WIT profits • Announce WIT in advance • E.g., WIT level, trade volume day ahead • Easier to comply, yet far more protection! • Flag as WIT on trading offer • Allow trades orthogonal to firm price • Always show internal PM stock price • Let firms decide how/if to regulate

  7. “Pays $1 if Bush wins” Will price rise or fall? sell E[ price change | ?? ] buy price sell Lots of ?? get tried, price includes all! buy Buy Low, Sell High (All are “gambling” “prediction” “info”)

  8. Today’s Current Event Prices 45-47% The Departed Oscar Best Picture ’07 6-9% Bird Flu confirmed in US. By Apr. ’07 85-90% Min Wage Increase By Apr. ‘07 15-17% Bin Laden caught by ‘08. 7-12% US military act against N. Korea by ‘08. 18-26% US or Israel air strike on Iran by ‘08. 18-24% Dick Cheney Resigns by ’08 48-49% Hillary Democrat Pres. Nominee in ‘08. 55-56% Democrat President in ‘08. TradeSports.com

  9. In direct compare, beats alternatives • Vs. Public Opinion • I.E.M. beat presidential election polls 451/596 (Berg et al ‘01) • Re NFL, beat ave., rank 7 vs. 39 of 1947 (Pennock et al ’04) • Vs. Public Experts • Racetrack odds beat weighed track experts (Figlewski ‘79) • If anything, track odds weigh experts too much! • OJ futures improve weather forecast (Roll ‘84) • Stocks beat Challenger panel (Maloney & Mulherin ‘03) • Gas demand markets beat experts (Spencer ‘04) • Econ stat markets beat experts 2/3 (Wolfers & Zitzewitz ‘04) • Vs. Private Experts • HP market beat official forecast 6/8 (Plott ‘00) • Eli Lily markets beat official 6/9 (Servan-Schreiber ’05) • Microsoft project markets beat managers (Proebsting ’05)

  10. Hollywood Stock Exchange Science 291:987-988, February 9 2001

  11. Track Odds Beat Handicappers Figlewski (1979) Journal of Political Economy 14 Estimated on 146 races, tested on 46

  12. Economic Derivatives Market Wolfers & Zitzewitz “Prediction Markets” (2004) Journal of Economic Perspectives

  13. NFL Markets vs Individuals Average of Forecasts Servan-Schreiber, Wolfers, Pennock & Galebach (2004) Prediction Markets: Does Money Matter? Electronic Markets, 14(3). 1,947 Forecasters

  14. “Accuracy and Forecast Standard Error of Prediction Markets” Joyce Berg, Forrest Nelson and Thomas Rietz, July 2003.

  15. Iowa Electronic Markets vs. Polls “Accuracy and Forecast Standard Error of Prediction Markets” Joyce Berg, Forrest Nelson and Thomas Rietz, July 2003.

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

  17. 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

  18. 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:

  19. 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

  20. Source:

  21. Inputs Outputs Prediction Markets Theory For Same Compare! Status Quo Institution

  22. Not Experts vs. Self-chosen Amateurs • Forecasting Institution Goal: • Given same participants, resources, topic • Want most accurate institution 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?

  23. Advantages • Numerically precise • Consistent across many issues • Frequently updated • Hard to manipulate • Need not say who how expert when • At least as accurate as alternatives

  24. Play Personal Mood Real or Rated Work Outcome, Ability Incentives Strong Weak Decision Markets Key Topics Morale Markets Fun Money: Time: Shows:

  25. $1 if A p(A) $1 $1 if A&B p(A&B) $1 $ x if A E[x|A]*p(A) $1 $ x E[x] $1 $1 if A&B p(B|A) $1 if A $ x if A E[x|A] $1 if A Estimates from Prices

  26. $ Revenue if Switch $1 $1 if Switch P(S) E(R | S) E(R) Compare! $ Revenue E(R | not S) $ Revenue if not Switch $1 if not Switch Revenue if Switch Ad Agency

  27. Decision Market Applications E[ Revenue | Switch ad agency? ] E[ Revenue | Raise price 10%? ] E[ Project done date | Drop feature? ] E[ Project done date | Add personnel? ] E[ Stock price | Fire CEO? ] E[ Stock price | Acquire firm X? ]

  28. E[ GDP+ | Alternative ] >? E[ GDP+ | Status Quo ] Vote On Values But Bet On Beliefs

  29. Legal permission Outcome Measured Aggregate-enough Linear-enough Conditional-enough Decision Distinct options Important enough Enough influence Public credibility Traders Enough informed Decision-insiders Enough incentives Anonymity Prices Intermediate-enough Can show Decision Market Requirements

  30. Coordinator Aides: Schedule meetings Collect stats Monitor others Research options Write reports, talks Review proposals Screen candidates Predict outcomes Make choices Coordination But: Lose Control, Leak Info, Ins. Tr. Law?

  31. Other ways to stop WIT profits • Announce WIT in advance • E.g., WIT level, trade volume day ahead • Easier to comply, yet far more protection! • Flag as WIT on trading offer • Allow trades orthogonal to firm price • Always show internal PM stock price • Let firms decide how/if to regulate

More Related