Tag Archives: Barack Obama

The HHS-Sebelius prediction market might be (yet) another case-in-point for documenting velocity.

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It is only today (February 19) that the New York Times emerges out of hibernation and headlines:

– Kansas Governor Seen as Top Choice in Health Post. &#8212- Gov. Kathleen Sebelius is emerging as President Obama’s top choice for secretary of health and human services.

Now, look at the red line in the HubDub chart below: the prediction markets nailed her since the beginning of February 2009.

Of course, a scientific comparison would have scrutinized more closely than I did all the news articles from the New York Times (and from other mass media). That&#8217-s what we are going to do with the &#8220-Open Institute Of Prediction Markets&#8220-. To this end, I will set up a portable and distributed &#8220-Prediction Markets Consortium&#8221- in the coming days. Then, I will try to anchor it in an institution of higher education, and, after that, I will try to gather support from think tanks and foundations. Not an easy task, but I know now that I can count on many prediction market people and companies. It should be an industry endeavor &#8212-and it should deliver results, in the end (demonstrating the social utility of the prediction markets by documenting velocity, and, from there, following a logical thread which I will talk you about later on).

PS: About velocity&#8230- Remember that we are about the prediction markets versus the mass media (The New York Times, The Times of London, NBC News, BBC News, etc.) &#8212-as opposed to the vertical media (Politico.com, Nate Silver&#8217-s blog, PoliticalBetting.com, etc.). The distinction is very important to keep in mind.

UPDATE: The only stuff I can find about Sebelius for HHS is that February 9 piece from the Associated Press (which didn&#8217-t get a mass audience since it was not-republished in the New York Times or other mass media), saying that she was &#8220-near the top&#8221- for the job. Well, &#8220-near the top&#8221- is not like saying she was &#8220-on top&#8221-.

UPDATE #2: The Sebelius story is picking steam in the mass media. See Nate Silver&#8217-s take.

ADDENDUM: Andrew Gelman tells me that he thinks that &#8220-the Associated Press is a mass medium. It is a cooperative organized by a bunch of newspapers.&#8221- I think that the AP news articles do indeed reach a big audience when they are re-published or cited in the mass media. But in the Sebelius case above, it was not the case.

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Previously: The truth about prediction markets

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Who will be the next nominee of the HHS, now that Daschle has withdrawn from consideration?

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No HHS contract on InTrade, BetFair or NewsFutures. :(

Prediction markets compute facts and expertise quicker that the mass media do.

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Political prediction markets react (with a small delay) to political polls &#8212-just like the political experts and the mass media do, too. Hence, in order to discover their true social utility, the prediction markets (which are tools of intelligence) should not be compared to the polls (which are just facts) but to the similar meta intelligence mechanisms (the averaged probabilistic predictions from a large panel of experts, or the averaged probabilistic predictions from the political reporters in the mass media, or else). My bet is that, in complicated situations (such as the 2008 Democratic primary), the prediction markets beat the mass media (in terms of velocity) &#8212-even though the prediction markets are not omniscient and not completely objective (but who is?).

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You might remember the research article that I have blogged about:

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Learning in Investment Decisions: Evidence from Prediction Markets and Polls – (PDF file) – David S. Lee and Enrico Moretti – 2008-12-XX

In this paper, we explore how polls and prediction markets interact in the context of the 2008 U.S. Presidential election. We begin by presenting some evidence on the relative predictive power of polls and prediction markers. If almost all of the information that is relevant for predicting electoral outcomes is not captured in polling, then there is little reason to believe that prediction market prices should co-move with contemporaneous polling. If, at the other extreme, there is no useful information beyond what is already summarized by the current polls, then market prices should react to new polling information in a particular way. Using both a random walk and a simple autoregressive model, we find that the latter view appears more consistent with the data. Rather than anticipating significant changes in voter sentiment, the market price appears to be reacting to the release of the polling information.

We then outline and test a more formal model of investor learning. In the model, investors have a prior on the probability of victory of each candidate, and in each period they update this probability after receiving a noisy signal in the form of a poll. This Bayesian model indicates that the market price should be a function of the prior and each of the available signals, with weights reflecting their relative precision. It also indicates that more precise polls (i.e. polls with larger sample size) and earlier polls should have more effect on market prices, everything else constant. The empirical evidence is generally, although not completely, supportive of the predictions of the Bayesian model.

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polls-prediction-markets

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You might also have watched Emile Servan-Schreiber&#8217-s videos. Emile is a smart man, and those videos are truly instructive.

  1. In the first part (the lecture), our good doctor Emile Servan-Schreiber sold the usual log lines about the prediction markets &#8212-blah blah blah blah blah.
  2. In the second part, Emile Servan-Schreiber took questions from the audience in the room. &#8220-Aren&#8217-t political prediction markets just following the polls?&#8221-, asked one guy. Emile&#8217-s answer was long and confused. However, in my view, Emile actually did answer that question (before it was ever asked) in his preceding lecture when, at one point, he made the point that the media were slower than the prediction markets to integrate all the facts about the 2008 Democratic primary, around May 2008. That is the right answer to give to a conference attendee who enquires about prediction markets &#8220-following&#8221- the polls. Both the mass media and the prediction markets do follow the polls (since the polls are facts that can&#8217-t be ignored), during political campaigns. Let&#8217-s compare the prediction markets with the mass media, instead, and let&#8217-s see who&#8217-s quicker to deliver the right intelligence..

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Lance Fortnow gives a good insight about the relationship between polls and prediction markets (see his last paragraph).

Yesterday the Electoral College delegates voted, 365 for Barack Obama and 173 for John McCain. How did the markets do?

To compare, here is my map the night before the election and the final results. The leaning category had Obama at 364. The markets leaned the wrong way for Missouri and Indiana, their 11 electoral votes canceling each other out. The extra vote for Obama came from a quirk in Nebraska that the Intrade markets didn&#8217-t cover: Nebraska splits their votes based on congressional delegations, one of which went to Obama.

Indiana and Missouri were the most likely Republican and Democratic states to switch sides according to the markets, which mean the markets did very well this year again. Had every state leaned the right way (again), one would wonder if the probabilities in each state had any meaning beyond being above or below 50%.

Many argue the markets just followed the predictions based on polls like Nate Silver&#8217-s fivethirtyeight.com. True to a point, Silver did amazingly well and the markets smartly trusted him. But the markets also did very well in 2004 without Silver. [Chris Masse’s remark: In 2004, Electoral-Vote.com (another poll aggregator) was all the rage.] One can aggregate polls and other information using hours upon hours of analysis or one can just trust the markets to get essentially equally good results with little effort.

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The polls are facts. Prediction markets are meta to facts. Prediction markets are intelligence tools. Let&#8217-s compare them with similar intelligence tools.

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Lance Fortnow&#8217-s post attracted an interesting comment from one of his readers:

to provide an exciting collection of political and other prediction markets.

These markets are as much a &#8220-prediction&#8221- tool as a wind vane or outdoor thermometer are. They moved up and down according to the daily trends, with very little insight of the longer place phenomena underlying them.

When the weather was hot (Palin&#8217-s nomination announcement) the market swinged widely towards McCain, while ignoring the cold front on the way here (the economic recession + Palin inexperience).

The value of weather forecast is in telling us things we didn&#8217-t know. We don&#8217-t need to trade securities to believe that if McCain is closing on the polls then his chances of wining are higher (duh!), which is what the markets did. We need sophisticated prediction mechanisms to tell us how the worsening economic conditions, the war in Iraq and Palin ineptitude (which in pre-Couric days wasn&#8217-t as well established) will impact this election, today poll&#8217-s be damned.

Looking at the actions by the republican teams, who were trying to read past the daily trend all the way to November 4th, it is clear that they thought all along they were losing by a fair margin. Because of this is they choose moderate, maverick McCain, went for the Palin hail mary fumble^H^H^H^H^H pass and the put-the-campaign-on-hold move.

A full two weeks before the election the McCain team concluded the election was unwinnable, while the electoral college market was still giving 25-35% odds to McCain.

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As highlighted in bold, the commenter says two things:

  1. The prediction markets are just following the polls.
  2. The prediction markets have a minimal societal value.

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My replies to his/her points:

  1. That&#8217-s not the whole truth. The polls are just a set of facts, whereas the prediction markets are intelligence tools that aggregate both facts and expertise. The commenter picks up a simple situation (the 2008 US presidential election) where, indeed, anybody reading the latest polls (highly favorable to Barack Obama) could figure out by himself/herself what the outcome would be (provided the polls wouldn&#8217-t screw it).
  2. That&#8217-s true in simple situations, but that&#8217-s wrong in complicated situations (such as the 2008 Democratic primary).

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The emergence of the social utility of the prediction markets will come more clearly to people once we:

  1. Highlight the complicated situations-
  2. Code the mass media&#8217-s analysis of those complicated situations, and compare that with the prediction markets.

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APPENDIX:

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Gary Gensler will head the Commodity Futures Trading Commission in 2009.

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Barack Obama has named Gary Gensler, a former Treasury official under President Bill Clinton, to take over the Commodity Futures Trading Commission (CFTC).

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New York Times:

Mr. Obama has vowed to reverse the deregulatory stance of the Bush administration and overhaul the entire system of financial supervision. Though Mr. Obama’s team has not mapped a specific plan, advisers on his transition team said reining in derivatives would be one of the biggest and most complicated parts of that effort.

gary-gensler

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Wall Street Journal:

team

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Is deregulation to blame? – by Reason Magazine

2) The Commodity Futures Modernization Act of 2000 guaranteed that high-risk tools such as credit default swaps remained unregulated, opting instead to encourage a “self-regulation” that neverhappened.

In late September, Securities and Exchange Commission (SEC) Chairman Christopher Cox estimated the worldwide market in credit default swaps —pieces of paper insuring against the default of various financial instruments, especially mortgage securities— at $58 trillion, compared with $600 billion in the first half of 2001. This is a notional value- only a small fraction of that amount has actually changed hands in the market. But the astounding growth of these instruments contributed to the over-leveraging of nearly all financial institutions.

In the late 1990s, the fight over these and other exotic new derivatives pitted a committed regulator named Brooksley E. Born, head of the Commodity Futures Trading Commission, against the powerhouse triumvirate of Federal Reserve Chairman Alan Greenspan, Treasury Secretary Robert E. Rubin, and Securities and Exchange Commission Chairman Arthur Levitt Jr. Unsurprisingly, Greenspan, Rubin, and Levitt won. The result was the Commodity Futures Modernization Act of 2000, which gave the SEC only limited anti-fraud oversight of swaps and otherwise relied on industry self-regulation. The Washington Post has closely chronicled the clash, concluding that “derivatives did not trigger what has erupted into the biggest economic crisis since the Great Depression. But their proliferation, and the uncertainty about their real values, accelerated the recent collapses of the nation’s venerable investment houses and magnified the panic that has since crippled the global financial system.” In other words: The absence of a regulation didn’t cause the crisis, but it may have exacerbated it.

Part of the problem was a technicality. Instruments such as credit default swaps aren’t quite the same thing as futures, and therefore do not fall under the Commodity Commission’s purview. But the real issue was that Greenspan, Rubin, and Levitt were concerned that the sight of important figures in the financial world publicly warring over the legality and appropriate uses of the derivatives could itself create dangerous instability. The 2000 law left clearing-house and insurance roles to self-regulation. Without a clearinghouse, the market for credit default swaps was opaque, and no one ever really knew how extensive or how worthless the derivatives were.

In congressional testimony on October 23, Greenspan seems to have admitted error: “Those of us who have looked to the self-interest of lending institutions to protect shareholders’ equity, myself included, are in a state of shocked disbelief,” he told the House Committee on Oversight and Government Reform. But Greenspan still wasn’t convinced that regulation is the solution: “Whatever regulatory changes are made, they will pale in comparison to the change already evident in today’s markets,” he said at the same event. “Those markets for an indefinite future will be far more restrained than would any currently contemplated new regulatory regime.”

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Previously: New SEC Chief

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BACKGROUND INFO:

– CFTC’s Concept Release on the Appropriate Regulatory Treatment of Event Contracts&#8230- notably how they define &#8220-event markets&#8221-, how they are going to extend their &#8220-exemption&#8221- to other IEM-like prediction exchanges, and how they framed their questions to the public.

– American Enterprise Institute’s proposals to legalize the real-money prediction markets in the United States of America

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Barack Obama has chosen Mary Schapiro, chief executive of a non-governmental regulator for securities firms (Financial Industry Regulatory Authority), to chair the Securities and Exchange Commission.

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What a great pick.

Out of the gate, Ms. Schapiro faces potential controversy. In 2001 she appointed Mark Madoff, son of disgraced financier Bernard Madoff, to the board of the National Adjudicatory Council, the national committee that reviews initial decisions rendered in Finra disciplinary and membership proceedings. Both sons of Mr. Madoff have denied any involvement in the massive Ponzi scheme their father has been accused of running.

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What a visionary regulator: inviting the fox inside the chicken house, that&#8217-s clever, indeed.

Jason Ruspini, will Barack Obama replace the CFTC head, too?

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The Intrade bettors expected Mr. Obama to end up with 364 votes in the Electoral College -one less than he actually got.

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My remark to John Tierney:

InTrade got it [almost] spot on because they were wrong on Missouri (which was predicted to go for Obama but went to McCain) and wrong too on Indiana (which was predicted to go for McCain but went to Obama) —and those 2 opposite mistakes canceled themselves because those 2 states have the exact same number of electoral votes (11). Hence, I disagree with your method.

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APPENDIX:

Here&#8217-s a visual post-mortem of the 2008 US presidential elections.

Pay attention to Missouri and Indiana.

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A) InTrade, on November 5, 2008 (screen shot taken at 2:00 am):

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Prediction Markets &amp- State Polls, on November 4, 2008:

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B1) Prediction Markets (on November 4, 2008)

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InTrade (screen shot taken at mid-day ET, November 4, 2008):

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InTrade (screen shot taken in the morning, November 4, 2008):

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BetFair (screen shot taken in the morning, November 4, 2008):

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HubDub (screen shot taken in the morning, November 4, 2008):

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B2) State Polls (on November 4, 2008)

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Karl Rove (on November 4, 2008):

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CNN (on November 4, 2008):

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Pollster (on November 4, 2008):

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Electoral-Vote.com (on November 4, 2008):

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Nate Silver (on November 4, 2008):

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PREDICTION MARKET PROBABILITIES

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Explainer On Prediction Markets

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A prediction market is a market for a contract that yields payments based on the outcome of a partially uncertain future event, such as an election. A contract pays $100 only if candidate X wins the election, and $0 otherwise. When the market price of an X contract is $60, the prediction market believes that candidate X has a 60% chance of winning the election. The price of this event derivative represents the imputed perceived likelihood of the partially uncertain event (i.e., its aggregated expected probability). A 60% probability means that, in a series of events each with a 60% probability, the favored outcome is expected to occur 60 times out of 100, and the unfavored outcome is expected to occur 40 times out of 100.

Each prediction exchange organizes its own set of real-money and/or play-money markets, using either a CDA or a MSR mechanism &#8212-with or without an automated market maker.

Prediction markets enable us to attain collective intelligence. Prediction markets produce dynamic, objective probabilistic predictions on the outcomes of future events by aggregating disparate pieces of information that the traders bring when they agree on prices. The event derivative traders are informed by the primary indicators (i.e., the primary sources of information), like the polls, for instance. These informed speculators then execute their transactions based on their anticipations about the future &#8212-anticipations that will be either confirmed or infirmed.

The value of a set of prediction markets consists in the added accuracy that these prediction markets provide relative to the other forecasting mechanisms, times the value of accuracy in improved decisions, minus the cost of maintaining these prediction markets, relative to the cost of the other forecasting mechanisms. According to Robin Hanson, a highly accurate prediction market has little value if some other forecasting mechanism(s) can provide similar accuracy at a lower cost, or if very few substantial decisions are influenced by accurate forecasts on its topic.

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More Info:

– The Best Resources On Prediction Markets = The Best External Web Links + The Best Midas Oracle Posts

– Prediction Market Science

– The Midas Oracle Explainers On Prediction Markets

– All The Midas Oracle Explainers On Prediction Markets

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Would InTrade or BetFair have done a better job predicting how many people would see the Barack Obama infomercial?

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As I disclose on the other blog (Midas Oracle .COM), the HubDub traders wrongly thought that the (Socialist) Barack Obama informercial would have be seen by &#8220-more than 50 million&#8221-. No, no, no, no. It was 33.5 million, according to Nielsen. The HubDub traders were too optimistic.

Would the InTrade or BetFair traders have done a better job? Jesus, that&#8217-s a difficult question. Which boils down (mainly, but not uniquely) to whether some experts on TV business were quoted in the media with some predictions. To investigate that, I have run a Google News search for news articles published before October 30. I haven&#8217-t seen any expert predicting how many viewers would get that infomercial. However, here&#8217-s what I spotted in the New York Times article published in the morning preceding the airing of that infomercial:

Ross Perot, the last presidential candidate to run similar programming, broadcast eight long infomercials to an average of 13 million viewers, with one of them getting 16.5 million viewers.

Hummm&#8230- Obviously, the HubDub traders were too cocky with their &#8220-50 million&#8221- figure&#8230- but should we blame them when, obviously (too), the Barack Obama situation circa 2008 is very different than the Ross Perot situation circa 1992?

The HubDub traders were not informed by the Ross Perot history. They simply made the bet that the Barack Obama infomercial would get as many TV viewers as the Third Presidential debate got (56.5 million). They predicted in a gregarious fashion. They lost.

I don&#8217-t think that the BetFair or InTrade traders would have done better. Do you?

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How many people will watch Barack Obama&#8217-s primetime address on 10/29?

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The definitive proof that HubDub is an indispensable prediction exchange. [*]

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As I told you, I am blogging as often as possible on the other blog (Midas Oracle .COM) about the 2008 US presidential elections as seen thru the eyes of the prediction markets. As I wrote there this morning, I have just found out a truly interesting set of prediction markets at HubDub. (I wasn&#8217-t able to find its equivalent on InTrade, BetFair, or NewsFutures.) It&#8217-s trying to predict where the Dow Jones will be, come November 4, 2008. (As you may remember, the deeper the financial crisis, the more likely it is that Barack Obama will be elected president of the United States.)

As of this morning, the Dow Jones is barely above the 8,000 level (8,175.77), and the futures say that the stock market will rebound, at least in the first hours. However, I am bearish. I would bet that the Dow Jones will stay around the current level (or lower) until Election Day. In other words, I am betting on the red, on the chart below.

At what level will the Dow Jones Industrial Average close on Election Day?

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[*] And if Emile (whom we highly respect, overall) is pissed off by that statement, then, great, that&#8217-s a cool unintended collateral consequence. :-D

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The New York Times on InTrades US political election prediction markets

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The NYT writers discusses 2 (different?) issues.

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#1. There was market arbitrage opportunies in the recent past between InTrade and BetFair &#8212-unlike 4 years ago, and contrary to the laws of economics.

– The price of the Barack Obama event derivative was cheaper on InTrade than on BetFair and the Iowa Electronic Markets. Conversely, the price of the John McCain event derivative was more expensive on InTrade than on BetFair and the Iowa Electronic Markets.

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#2. The NYT writer reports (without linking to it) the findings of the InTrade investigation about the behavior of their unnamed &#8220-institutional investor&#8221-.

– InTrade CEO John Delaney suggests that that institutional investor:

  1. might operate on InTrade at specific times where it might not be able to find liquidity on BetFair and/or IEM-
  2. might be a bookmaker willing to hedge its risks on a prediction exchange (a.k.a. betting exchange).

– Justin Wolfers&#8217- PHD student remarks that that institutional investor is not making an effort to shop around for the best prices, within each InTrade political prediction market.

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RELATED: See the comments on Midas Oracle here, here, here, and here.

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Are recent historical charts now useless for short-term prediction market analysis because of the non-informational trades made by that institutional investor hedging its political risks on InTrades election prediction markets?

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How can you assess the impact of Colin Powell&#8217-s endorsement of Barack Obama? You can&#8217-t.

As Justin Wolfers noted, maybe there are today bigger practical obstacles to prediction market arbitrage.

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– Legal restrictions for US traders on foreign prediction exchanges (BetFair, etc.)-

– Transaction fees (you would need to operate on 2 exchanges)-

– Currency risks and cost for hedging on that.

Eric Crampton (a Canadian exiled in New Zealand) says he has managed to turn a buck, though, by arbitraging between InTrade and iPredict New Zealand. He also makes 2 theoretical points. Go read it.