The Borg-Yahoo merger wont work.

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It&#8217-s like taking the two guys who finished second and third in a 100-yard dash and tying their legs together and asking for a rematch, believing that now they&#8217-ll run faster.

Fake Steve Jobs

The cultures will never fit together. And the deal is too big. It&#8217-s not manageable. And it&#8217-s completely anathema to Microsoft. It&#8217-s totally out of character for them. It goes against everything the company has ever stood for.

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Psstt&#8230- On a related note&#8230- If you haven&#8217-t seen yet the Fake Steve Jobs address at the Crunchies 2008, (an &#8220-acceptance speech&#8221- he gave coz Apple didn&#8217-t send any representative at the event), you should. Hilarious.

Previous blog posts by Chris F. Masse:

  • No Trades (other than at the start) —-> Not a reliable predictor, as of today
  • How you should read Midas Oracle
  • The best prediction exchanges
  • “There will be no media consumption left in ten years that is not delivered over an IP network. There will be no newspapers, no magazines that are delivered in paper form. Everything gets delivered in an electronic form.”
  • Hillary Clinton won’t be on the Democratic ticket. — It’s not going to happen. — N-E-V-E-R. — Not a chance. — Period.
  • Suggestion for WordPress — Subscribers’ Capabilities
  • This is why I said that those who believe that Hillary Clinton has a chance to be on the Democratic ticket are “clueless”.

Merger Markets on Microsoft-Yahoo

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HP began to explore prediction markets in 1996, but did not even consider applying them to the 2002 HP-Compaq merger. Similarly, Yahoo and Microsoft are two of the companies mentioned most often as being involved in prediction markets (along with their main competitor Google), but I&#8217-ll bet none are considering the by-far-most-valuable markets they could create, on their just-announced proposed merger.

Decision markets could say whether this merger is good for shareholders, by estimating the combined stock price given a merger, and given no merger. Similarly, decision markets could say whether this merger is good for these firms&#8217- customers, by estimating the price and/or quantity of web ads given a merger, and given no merger. This might help convince regulators to approve the merger.

My main doubt here is whether ad price and quantity are good enough measures of the merger&#8217-s social benefits – what other outcomes could such markets estimate, to speak more clearly? And this is a very clear demonstration that these companies are just not serious about finding the highest value applications of prediction markets.

Cross-posted from Overcoming Bias.

Search engine futures!

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Cross posted from Oddhead Blog.

I am happy to report that on my suggestion intrade has listed futures contracts for 2008 search engine market share.

Here is how they work:

A contract will expire according to the percentage share of internet searches conducted in the United States in 2008. For example, if 53.5% of searches conducted in the United States in 2008 are made using Google then the contract listed for Google will expire at 53.5&#8230-

&#8230-Expiry will be based on the United States search share rankings published by Nielson Online.

I think this could be a fascinating market because:

  • Search engine market share is very important to these major companies, with dramatic effects on their share prices.
  • Search engine market share is fluid, so far with Google growing inexorably. However, Microsoft has cash, determination, Internet Explorer, and the willingness to experiment. Ask.com has erasers, 3D, ad budgets, and The Algorithm. Yahoo!, second in market share, often tests equal or better than Google, and new features like Search Assist are impressive.
  • The media loves to write about it.
  • A major search company might use the market to hedge. Well, this seems far-fetched but you never know. Certainly, from an economic risk management standpoint it would seem to make a great deal of sense. (Here, as always on this blog, I speak on behalf of myself and not my company.)

Finally, I have to comment on how refreshingly easy the process was in working with intrade. They went from suggestion to implementation in a matter of days. It&#8217-s a shame that US-based companies are in contrast stuck in stultifying legal and regulatory mud.

InTrade-TradeSports and BetFair-TradeFair are barred from advertising on Google, Yahoo! and MicroSofts networks of websites.

Via Jason Ruspini and Daniel Horowitz, The Associated Press &amp- Reuters.

But I will remark that Google Ads serve both InTrade and TradeSports. [I don&#8217-t mind. Just a remark.]


Author Profile&nbsp-Editor and Publisher of Midas Oracle .ORG .NET .COM &#8212- Chris Masse&#8217-s mugshot &#8212- Contact Chris Masse &#8212- Chris Masse&#8217-s LinkedIn profile &#8212- Chris Masse&#8217-s FaceBook profile &#8212- Chris Masse&#8217-s Google profile &#8212- Sophia-Antipolis, France, E.U. Read more from this author&#8230-


Read the previous blog posts by Chris. F. Masse:

  • Comments are now completely open on Midas Oracle.
  • Albert Einstein, Chairman of the Midas Oracle Advisory Board
  • Erratic –but not Stochastic– Charts
  • Barack Obama is the 44th US president.
  • We already have prediction markets in future tax rates. It’s called the municipal bond yield curve.
  • DELEGATES AND SUPERDELEGATES ACCOUNTANCY
  • O’Reilly – Money-Tech Conference

Predictocracy: Market Mechanisms for Public and Private Decisionmaking – THE MARKET WEB

Predictocracy: Market Mechanisms for Public and Private Decisionmaking &#8211- by Michael Abramowicz &#8211- 2007-xx-xx &#8211- (fall)

Chapter: The Market Web &#8211- (towards the end of the book)

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Michael Abramowicz:

If prediction markets should become commonplace, decisionmakers might link to them in their own analyses.

Will trading play-money and/or real-money event derivative contracts become commonplace? It&#8217-s likely, at the contrary, that trading will remain an elite occupation and that prediction markets with appropriate liquidity will remain scarce. Unless Google, Yahoo! (with Yootopia) and/or MicroSoft has/have a secret plan to popularize betting exchanges &#8212-which could well be since Bo Cowgill, David Pennock and Todd Proebsting are ambitious guys.

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Michael Abramowicz:

For example, suppose that a corporation is deciding whether to build a new factory in a particular area. That decision might depend on variables like future interest rates and geographic patterns. And so, a decisionmaker might build a spreadsheet containing live links to prediction markets assessing these issues.

Interest rate prediction markets would help, for sure. As for geographic forecasting, maybe non-trading mechanisms could help &#8212-for real estate, I&#8217-m thinking of Zillow, or some improved mechanisms derived on Zillow.

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Michael Abramowicz:

The Market Web

If prediction markets should become commonplace, decisionmakers might link to them in their own analyses. For example, suppose that a corporation is deciding whether to build a new factory in a particular area. That decision might depend on variables like future interest rates and geographic patterns. And so, a decisionmaker might build a spreadsheet containing live links to prediction markets assessing these issues. That way, as the market predictions change, the spreadsheet&#8217-s bottom line would change as well. Predictions in many prediction markets may be interrelated, and so market participants in one prediction market will often have incentives to take into account developments in other prediction markets. Prediction markets thus can affect one another indirectly, as participants in one update their models based on developments in another.

Sometimes, however, it might be desirable to construct links among prediction markets so that changes in one automatically lead to changes in another. Consider, for example, the possibility of a market-based alternative to class action litigation. In Chapter 8, each adjudicated case represented a separate prediction market, but often there will be issues in common across cases. Many thousands of cases may depend in part on some common factual issues, as well as on some distinct issues. Legal issues also may be the same or different across cases. Someone who improves the analysis of any common factual or legal issue can thus profit on that only by changing predictions in a very large number of cases. A better system might allow someone to make a change across a single market and have that change propagate automatically to individual cases.

The critical step needed to facilitate creation of the market web is to allow a market participant to propose a mathematical formula to be used for some particular prediction market. Some of the variables in that formula could be references to other, sometimes new, prediction markets. For example, a market participant might propose in a market determining how much amages the plaintiff should receive a formula dependent on variables such as the probability that the plaintiff states a cause of action, the probability that the plaintiff was in fact injured, the probability given injury that the defendant caused the injury, the probability given a cause of action that the defendant is subject to strict liability, the probability given no strict liability that the defendant was negligent, and the damages that the plaintiff should be awarded if liability is proved. This formula, for example, presumably would allow for no damages where the plaintiff probably does not state a cause of action. Each of the components of this formula might be assessed with a separate prediction market. We can easily build the market web by combining three existing tools. The first tool is a text-authoring market. The relevant text would be the formula itself, including specifications of other prediction markets that would be used to calculate specific variables. As with any text-authoring market, a timing market would determine when a proposal to change the text should be resolved. Other markets might become live only once proposals to take them into account were approved. Ex post decisionmakers would assess the wisdom of these markets&#8217- recommendations in some fraction of cases to discipline the market&#8217-s functioning.

The second tool would be a simple normative prediction market corresponding to the text-authoring market. It might also be possible to have computer software that automatically parses the formula and consults various sources, but the market sponsor need not build this tool. Rather, ex post decisionmakers will assess the appropriate value for the normative prediction market based on the formula. An advantage of this approach is that it would make it easy to use complicated formulas, as well as formulas that depend in part on numbers from sources other than prediction markets, or from prediction markets of other types. In addition, this approach makes it easy to collapse a formula into a single prediction market, if that should prove desirable. The formula text simply would be changed to a description of the market to be created, such as &#8220-adjudication of plaintiff&#8217-s liability in a particular case.&#8221-

Finally, the third tool necessary is a mechanism for determining the market subsidy. A separate subsidy would be needed for the text-authoring market and the normative prediction market. Each of these subsidies could be determined by additional normative prediction markets, perhaps with fixed subsidies. The subsidy for the text-authoring market in turn would be distributed by the text-authoring market to individuals who have proposed particular amendments, and individuals who have participated in the assessment of particular amendments. The text-authoring market also could allocate a subsidy to the first individual who creates the market and proposes some text for it. When the text-authoring market produces a new formula reflecting additional prediction markets, the subsidy for the main prediction market would fall (since calculating a formula based on other prediction markets will often be relatively easy).

A single node in the market web would thus consist of a text-authoring market describing the node and providing a formula for calculating it, a normative prediction market, and a set of additional prediction markets for determining how to distribute a subsidy to the different components of the node. The nodes collectively create a web because the formulas link to other nodes- software, of course, could easily make these links clickable. At the same time, a mechanism is needed to determine what portion of the market subsidy each node should receive. A simple approach would be for a prediction market to be used for every link, to determine the portion of the subsidy for each node that should be allocated to each node linked to it. The total should add up to less than 1, leaving some portion of the subsidy for the node itself.

With these markets established, software could easily distribute a single subsidy for the market as a whole to market participants who have traded on individual nodes when the market closes. Market participants working on one portion of the web, meanwhile, would not have to assess the relative importance of one node to nodes that are only distantly related. It would also be straightforward to have a continuously open market, periodically collecting and distributing money in accordance with individual participants&#8217- success on the market.

This assumes that the market web would be arranged on a single server. It is possible, though, that a node on one market web might link to a node on another market web. If market sponsors allowed such links, it could promote competition among prediction market providers. It also partially answers one potential criticism of using prediction markets for decisionmaking, that a software engineer might hijack the government by faking some prediction market results. Market participants at least will have incentives to identify fake prediction markets and not link to them. In principle, it is possible to have government decisions based entirely on decentralized prediction markets. A caveat is that the government might want to subsidized individual market web providers, and it might use centralized prediction markets to accomplish that.

Whether or not the markets themselves are decentralized, they would allow market participants to make it easier to assess the basis for market predictions. Indeed, the market web is in some ways a substitute for deliberative prediction markets, because both provide means of helping observers understand the basis for the market&#8217-s predictions. An observer could look at any individual node of the market web and understand how it has been calculated, though inevitably there must be some &#8220-leaf&#8221- nodes that themselves do not contain any formulas. At the same time, software might allow an observer to find all of the nodes that link to a particular node. So a market participant addressing a factual issue relevant to many cases could link to all of the cases represented by that factual issue. As a particular issue becomes increasingly important, the subsidy for that node should rise, and market participants can profit on their analysis of the issues relevant to that node without worrying about details of individual cases.

[…]

Brainy stuff. I&#8217-ll mind this for a while. I&#8217-m sure that the Midas Oracle readers will find this idea original &#8212-and maybe, interesting.