Entries in prediction markets (12)

Tuesday
Dec082009

Web capitalism doesn't need a bailout

Slightly self-promotional, yes, and the title is a bit inflammatory, but my Ignite DC talk was just posted to blip.tv. It is a rapid-fire 5 minute coverage of some of my favorite topics: p2p e-commerce (e.g., Etsy), crowdsourcing, social lending, and prediction markets, all powerful technology-driven platforms that advance free markets.

Monday
Aug102009

A stock market approach to public policy decisions

"We believe democracy's flattering lie that each voter's opinion is just as valid as anyone else's. But, in fact, most voters' opinions about what works are usually awful."

Therein is the basis for futarchy, an alternative governance system where democracy continues to be the mechanism to determine desired outcomes, but speculative markets determine the means. See Robin Hanson's article this month in BBC Focus Magazine (for the full text, see here).

This wild idea actually might actually have some appeal now with the massive failure of democratic town hall meetings to achieve any type of thoughtful discourse on how to tackle challenges of healthcare and climate change. Would an objective evaluation of the impact of proposals on national welfare through an open market, as proposed in this model, help us reach a better outcome?

Friday
May292009

Ancillary benefits of corporate prediction markets

Adam Siegel, CEO of Inkling Markets, made an interesting comment today during our phone conversation: the ancillary benefits of prediction markets can often be more important that the predictions themselves.

Inkling, a prediction markets platform for companies, promises to help you gain "business intelligence from your human network" and they agree with a lot of the commonly cited benefits such as increasing collaboration across boundaries, gaining the "wisdom of crowds" etc., but Adam mentioned a few additional benefits. He cited a common challenge in talking about prediction markets (that I have faced as well) which is that the primary driver for many people is "did the prediction market get it right?" Did Intrade get the 2008 election right? Did the HP market accurately predict printer sales? The truth is that prediction markets offer probabilities, not absolutes, so even if Intrade got a certain event "right" with 52% of the vote, it could have done just as well with a coin toss.

So, while numbers are very important, the right/wrong dichotomy isn't necessarily. Here are some of the ancilliary non-forecasting benefits that came out of our conversation:

  • Building in social aspects into prediction markets, such as discussion threads, can lead the market framers (i.e., the management) to begin to ask the right questions
  • The purely quantitative results can drive increased emphasis placed on the value of transparent metrics in an organization
  • Market results can be an "eyebrow raising exercise" or gut-check to the expectations of management
  • When markets are on-going, they can constantly adjust to changing events, rather than providing just a snapshot in time

I was also intrigued by Adam's observation that Inkling's clients are overwhelmingly the"hell raisers within the company" i.e., managers who sense the real disconnect between their bosses and the employees that report to them and want to shake things up. He cited an example at Proctor & Gamble where the company market results proved that executives were consistently over-optimistic in their forecasts across the spectrum of future events from product roll-outs to competitor behaviors. The hard proof of this behavior helped them to stop killing their employees and bring some balance between their expectations and the realistic expectations of the folks on the ground.

Tuesday
Mar032009

Are you a hedgehog or a fox?

Philip Tetlock's book Expert Political Judgment seeks to explore what constitutes good judgment in predicting future events. His 20 years of research finds that when asked to forecast political phenomena experts fare only slightly better than informed dilettantes and worse than simple extrapolation models based upon current trends.

This is bad news for experts, pundits, and expensive consultants paid to give their opinions on what is going to happen. Indeed, Dr. Tetlock found that the more famous the expert, the less accurately he/she forecasted. He also found education and experience had little to say about a forecaster's skill. Forecasters systematically over-predicted unlikely events (longshot bias), exaggerate d the degree to which they "saw it coming all along" (hindsight bias) and committed a number of other mistakes, relying too often on intuition over logic.

This does not mean that expert opinions are only as reliable as a chimp throwing random darts (although it is close...). One thing does make a real impact on forecasting skill: how an expert thinks.

To explore this idea, Dr. Tetlock borrows the famous line from Isaiah Berlin (who in turn had borrowed from a Greek poet): "The fox knows many things, but the hedgehog knows one big thing." According to the book, the better forecasters were foxes: self-critical, eclectic thinkers willing to update their beliefs when faced with contrary evidence, doubtful of grand schemes and  modest about their predictive ability. The less successful forecasters were hedgehogs: thinkers who tended to have one big  idea that they loved to stretch, sometimes to the breaking point. They tended to be articulate and very persuasive as to why their idea explained everything.

Unfortunately, because they often offer simpler, easily digestible messages, hedgehogs are far more likely to be the faces that we see interviewed on the major news circuits with theories of the future of global finance, American decline and other complex topics that often fit a little too neatly with past analogies.

Do prediction markets help at all with this problem? Can they help reduce forecasting bias? One challenge I see is that many of the incentivizing constructs offered on current platforms are leaderboards, appealing to the ego of the participants, and in turn, I would assume, increasing longshot bias. Experts make their names from BIG predictions that no one else has the "courage" to make. Sometimes they are right but usually not, and the payoff is far greater for eventually being right than the penalty is for continuously being wrong. If the same lopsized incentives exist in prediction markets, then the predictions made there will presumably also tend far more towards the extremes.

Here is some good advice from Dr. Tetlock on how amateurs like you and I can test our own hunches:

"Listen to yourself talk to yourself. If you're being swept away with enthusiasm for some particular course of action, take a deep breath and ask: Can I see anything wrong with this? And if you can't, start worrying; you are about to go over a cliff."

Flickr credit: ·Will·

Flickr credit: mikebaird

Monday
Mar022009

Predicting the technology future

In a crowd of emerging prediction market sites asking all sorts of frivolous pop culture questions of their participants, Nostradamical chooses to ask an interesting one: What will be the key milestones in computing technology over the next few years?

To think about this question, they first explore the past 100 years through the technology prediction market questions that would have been: Will Apple make phones?(2007) Will the Sony Walkman just be a teenage fad? (1977) Is there money in microchips? (1969)

Unfortunately, since Nostradamical's model is to allow its members to submit their own markets, the actual technology markets are often somewhat silly and poorly formed, e.g., Will AOL continue to worsen and die? Power.com won't succed (sic) in 2009. I would like to see Nostradamical moderate the site a bit more and even create "official" markets suggested by the site owners.

Still, the site is fun, intuitive, and creates a stronger sense of a "predicting" community than many of its competitors. It integrates a Digg-like function of moving interesting predictions to the top and an (somewhat) incentivizing pyramid scheme for top predictors to work their way to the top to become "oracles." You can join the conversation with their most popular prediction: Will Apple announce their own search engine in 2009?

Thursday
Feb262009

The future of corporate prediction markets

The Economist today discusses the "uncertain future" of prediction markets in corporate decision making. As the article states, "although they have spread beyond early-adopting companies in the technology industry, they have still not become mainstream management tools." A couple of challenges are raised:

  • Getting enough people to keep trading once the novelty wears off. While an important point (a prediction market, like all markets, can only thrive and reach equilibrium if there are enough players), a good incentivization structure (e.g., money, prizes) should both encourage participation and better results.
  • Keeping people interested if they can't see how the results are being used. If a company isn't planning on using the results of the prediction market to make real decisions, then why create it to begin with? Wells Fargo, for example, said that its most effective trials took place in areas where managers could "do something with their findings." This should be the standard, not the exception. Plenty of prediction markets out there now are simply fun and games, brag to the community ventures with no practical value (e.g., a current question on Hubdub: "Will Nadya Suleman's ex-boyfriend be confirmed as the father of her children?") Corporate markets run by businesses with a bottom line should have no tolerance for wasted time of their employees making silly bets. If the company is using the results, but it is just not clear to employees, then they have a simple strategic communication problem.
  • The wariness of bosses to rely on the recommendations of non-experts. This challenge seems to miss the point. Corporate prediction markets should be asking questions that the employees are experts in. Perhaps the junior staff does not have all of the program management knowledge of the managers who make the decisions, but they do have more insight into day-to-day operations. Gaining the collective judgment of employees who have windows into small pieces of the overall problem should, according to the Wisdom of Crowds argument, be worth more than any single expert.

The most successful corporate prediction markets ask specific questions that the employee pool can offer diverse, informed opinions upon. The Koch Industries example cited in the article, then seems to be a poor example. In Koch's prediction markets, employees can bet on the future prices of raw materials and the liklihood of bank nationalization. The truth is that an internal Koch market is probably not the best place to answer these big questions. There is no reason to believe that the collective wisdom of the chemical conglomerate on the future of banks should be better than the judgement of economic experts.

HP, by contrast, had great success focusing on something that their employees did have unique insight into: projecting future sales of printers. Their internal market is quite complex: “We want to reduce the wisdom of crowds to the wisdom of 12 or 13 people,” said Bernardo A. Huberman, director of the social computing lab at Hewlett-Packard. Among the techniques, he said, are preliminary tests to assess the “behavioral risk characteristics” of participants to shade predictions from people who are inherently risk seekers or risk averse.

Google has created the largest corporate prediction market in the world. Google economic analyst Bo Cowgill explains that the trading system lets Google management discover its employees' uncensored opinions: "If you let people bet on things anonymously, they will tell you what they really believe because they have money at stake," Cowgill said. "This is a conversation that’s happening without politics. Nobody knows who each other is, and nobody has any incentive to kiss up." Traders can bet on such questions as: Will a project be finished on time? How many users will Gmail have? (In addition to some unrelated, political questions).

The primary benefit of a prediction market is that it allows information to be shared efficiently and at little cost. Improved information in turn leads to better decision making by management. The important thing is to ask the right questions.

For more on the subject of corporate prediction markets, see Robin Hanson and Tyler Cowen.

Wednesday
Feb252009

The Aftermath of the President's State of the Union speech: The Dow is down, but what do the prediction markets say?

Following President Obama's State of the Union address yesterday, the Dow is down by over 1%:

The Industry Standard on the other hand belives that prediction markets may be more optimistic on the state of the economy. Their prediction, Dow Jones rises to 8000 by March 20, 2009 is trading favorably with the current consensus at 65%.

Traders at Hubdub, on the other hand, are less optimistic. Most trades there are betting that the Dow will close below 7000 before it goes above 8000. Interestingly, few think that it will remain in place (likely partially the product of longshot bias):

At Intrade, the money is on the Dow falling below 7,000 sometime this year:


On balance, the reviews are fairly negative. And the Dow itself is the one that really counts.

Tuesday
Feb242009

How Do Companies Harness the Power of Web 2.0 Technologies like Prediction Markets?

Broad participation is key to successful prediction markets: the more the better!Web 2.0 technologies are tools that utilize broad participation, collaborative creativity, and social mapping as a means to generating value. They include blogs, wikis, social networks, podcasts, information tagging, and prediction markets. When properly implemented, these tools have the ability to create great value for companies. However according to a group of surveys conducted by McKinsey, the number of executives dissatisfied with their company’s adoption of Web 2.0 technologies is the same as the number of those who are satisfied.

McKinsey’s recent publication points out that one important factor for effective Web 2.0 adoption is to clearly understand the differences between today’s Web 2.0 technologies and the corporate technology adoptions of the 1990s (such as supply chain management and or customer relationship management):

Corporate Technology of the 1990s

Web 2.0 Technologies

  • Direction given from the top
  • Engages fewer and more senior individuals
  • Does not require interactive participation
  • Technically complex to implement
  • Strong bottom-up element
  • Engage a broad base of workers
  • Require high degree of participation to be effective
  • Requires users to generate new information or edit content
  • Technically simple to implement

 

 

 

 

 

 

 

Based on the unique nature of Web 2.0 tools, McKinsey suggests the following six tips for making Web 2.0 technologies work:

  1. The transformation to a bottom-up culture needs help from the top.
  2. The best uses come from users—but they require help to scale.
  3. What’s in the workflow is what gets used.
  4. Appeal to the participants’ egos and needs—not just their wallets.
  5. The right solution comes from the right participants.
  6. Balance the top-down and self-management of risk.

How does this apply to prediction markets and internal corporate information markets? Some of the tips above are relevant: scale and quality of participation are key to effective prediction markets. Participation can be fostered when the use of a prediction markets bears relevance to employees’ daily responsibilities and also when employees recognize that senior management values the results of the prediction market. However, unlike other Web 2.0 tools, appealing to a participant’s ego instead of wallet, works against the logic of prediction markets which require an environment of anonymity and a fertilizer called “putting your money where you mouth is” in order to bear fruit.

Another interesting question that comes up from this McKinsey publication is whether combining prediction markets with certain other Web 2.0 technologies can help to make them more effective and widely used?

For more information read the McKinsey’s article here.

Flicker credit: ChrisL_AK

 

Thursday
Feb052009

Perhaps Intrade isn’t doomed after all…

Barney Frank, Chairman of the House Financial Service Committee, told the Financial Times today that he will introduce a bill to establish a licensing and regulatory framework for online betting operators. Under Frank’s proposal, the Unlawful Internet Gambling Enforcement Act of 2006, the law that forced Tradesports to shut down and currently threatens all online sites where real money is exchanged, would be relaxed.

This is good news for prediction markets. Less regulation means that more prediction markets can operate with the component that market theory says is so important: financial incentive. Tradesports and IEM are so effective now in their predictive power because betters have real money at stake. SimExchange, Hollywood Stock Exchange, and others use a variety of other incentive mechanisms including public leaderboards, faux currency, and bragging rights, but none of these equal the power of cash.

This is also good news for those interested in freedom and commonsense policy. Barney rightly compares the stringent gambling penalties to those encountered during the age of prohibition. And if Maryland is going to grant waivers for slot machines, then doesn’t it make sense to allow betting that actually involves some brainpower and might influence decision making around something of consequence?

Monday
Feb022009

What is a prediction market?

See our new primer.

Saturday
Jan242009

Other Prediction Markets...Installment 1

Especially due to Intrade’s wild success during the 2004 and 2008 election seasons, the major prediction exchanges have received a lot of hype and most people [interested in this sort of thing] generally know the big ones: Intrade, Hubdub, IEM, etc.

There are some intriguing and less well known ideas out there (some in practice and others theoretical) that utilize the concept of prediction markets. We will profile these occasionally [Let us know if you have ideas]. Here is the first installation.

Futarchy

 

A concept of government-by-prediction-market proposed by economist/philosopher/rationalist Dr. Robin Hanson where individuals would “vote on values but bet on beliefs”. The term itself got some attention following its selection as a New York Times buzzword of 2008 (never mind that it was first proposed by Hanson in 2000).

The gist is the legislators define a measurement of national welfare and then voters bet on the policies that they believe are most likely to raise national welfare according to the definition. This form of government disentangles values (which we can’t do much to change) from beliefs (which are too often biased by our values). By attaching a real incentive to predicting whether a certain policy will in fact increase national welfare, futarchy uses the information aggregation and bias reducing power of prediction markets.

 

To be clear, this concept is very different than government-by-referendum. Individuals do not vote on which policies they like or want but rather those that they would be willing to place money on to exceed a precisely defined measurement of national welfare. The main challenge to me seems to be how to define national welfare and whether legislators would be able to agree on a formula.


GDP would be a natural component of such a formula (due to its high correlation with so many signs of positive “national welfare”), but many other possible variables may be contentious (increased income equality? Increased diversity?). Defining a national welfare formula would ignite a fierce partisan debate that gets to the heart of the question of values. The concept of futarchy takes that into account; that is why we vote on values (i.e., we elect politicians whose most closely resemble our own). But then, we don’t ascribe too much confidence to the politicians’ ability to get things done to best advance our values; that is why we bet on beliefs (i.e., bet money in a prediction market on policies that will most raise national welfare as defined by the politicians we voted for). The “wisdom of crowds” should lead to the best policies…of course, if you lost the politician vote, then you won’t agree with the national welfare formula and then I suppose you either choose to sit out the betting round out or else bet money the wrong way in the hope of distorting the results.

For more, see HERE and HERE. There are also those who doubt the clear delineation between values and beliefs as seen HERE.


Futarchy is only a theoretical concept at present and has yet to be tried in practice, although Dr. Hanson stands ready to assist any government willing to give it a try.

Sunday
Jan182009

What are alternative markets and what elements tie them together?

 

Peer-to-Peer lending markets, local stock exchanges, prediction markets, direct buyer-seller community markets…Innovative re-inventions of the traditional marketplace, all made possible by web technology.

 

While the current financial crisis shakes the confidence of many free market believers, there glows a series of alternative market movements still enthusiastically embracing the core market essentials. These markets connect buyer to seller while rejecting the opacity and complication that characterizes much of our current financial framework. Their missions are generally simple and focused, encouraging participants to be knowledgeable of the market dynamics, with the end goal of fair and efficient trades between individuals and better information. These alternative markets can be classified into four major types:

  1. Peer-to-Peer (aka Social) Lending Markets.  This concept is a type of financial transaction where two parties can enter into a borrowing/lending agreement without the intermediation of a traditional financial services provider. See: Prosper, Lending Club, Kiva.

  2. Prediction Markets.  With the marketplace able to tap into the “wisdom of crowds”, prediction markets have emerged as a venue for speculating about the future. See: Intrade, Betfair, Futarchy.

  3. Community Markets.These sites allow buyers to get to know and interact with their sellers and buy from them directly. See: Etsy.

  4. Local Markets.  As the stock marketplace has moved increasingly global over the years, local investing enables individuals to instead invest in community companies that they know and trust. See: Locavesting.

Utilizing the efficiency of the market for the traditional purpose of exchanging goods, services, and information, these emerging concepts spin the concept to meet their niche purposes. The rise of alternative markets indicates some interesting trends of our society that have implications well beyond the marketplace.

First, there is a clear desire by market participants to introduce a level of transparency in financial dealings. Each of the social lending services works on a peer-to-peer basis, so you as an individual loaner know who is receiving your loan. This is a very different operating model than giving your money to a black box financial services company that makes decisions on your behalf. As we have seen, that model does not always make the decisions that are in the best interest of the lender. Similarly, with locavesting, rather than invest in a large corporation where you have no insights into its inner dealings (e.g., Enron, Worldcom, Global Crossing), you can invest in a neighborhood store or local company where you may actually know the management, see the customers, and build a more rounded perspective of the entity’s value.


This leads to a second trend, a lack of faith in experts.  Recent events point to the danger of trusting an individual (e.g., Bernie Madoff) while past events warn of ascribing too much faith to a group (e.g., the whiz kids of Long Term Capital Management). With economic experts and pundits of all stripes constantly pontificating their chosen strategies and predictions, it is hard to sort through the noise. This challenge was perhaps best illustrated during the November election when news agencies released daily polls accompanied by salient expert analysis that were often contradictory, repetitive, or incoherent. One of the best and simplest resources to get to the bottom of the single question, “Who will win in November?” was the prediction market Intrade, which harnessed the collective knowledge of its users to produce a startling accurate prediction of the final results (prediction of Democrats-Republicans 365-173 versus actual results of 364-174). The concept of futarchy takes faith in this concept a step further and suggests that prediction markets can be used to guide public policy decisions. Social lending services also indicate a desire for individuals to take control of their financial decisions rather than relying on the recommendations of experts. There you can manage the risk, evaluating potential lenders (or investments) yourself.


While alternative market participants personally gain from increased transparency and better informed decisions, all of the markets also demonstrate a commitment to building a community. Some peer-to-peer lending service operate under a “family and friends” model and all of them stress that the investment is not just a personal investment for return, but also a way to help fellow market community members achieve their financial objectives. Similarly, the direct artist-consumer model integrates social networking to make purchases more of an experience where you can get to know the person you choose to buy from, and in the process strengthen the artist community. Locavesting is at its core investment choices that support and sustain the local community.


Emerging market movements indicate that even in a time of bailouts and stimulus packages, capitalism is still alive and growing. Markets are evolving and individuals are having a say in that evolution. Many of these markets are now facing challenging times, however, and their future will say a lot about how our society and government value the marketplace.