
Review of Fortune’s Formula by William Poundstone: The stranger-than-fiction tale of how to invest
What is a better investment objective? Grow as wealthy as possible as quickly as possible, or Maximize expected wealth for a given time period and level of risk The question is at the heart of a fight between computer scientists and economists chronicled beautifully in the book Fortune’s Formula by Pulitzer Prize nominee William Poundstone. [...]
What is (and what good is) a combinatorial prediction market?
What exactly is a combinatorial prediction market? 2010 Update: Several of us at Yahoo! Labs, along with academic researchers, have theorized and written about combinatorial prediction markets for several years, as you’ll see below. But now we’ve gone beyond talking about them and actually built one. So the best way to answer the question is [...]
The right way to implement a multi-outcome prediction market: Linear programming
There are many examples of multi-outcome prediction markets, for example election markets with more than two candidates, or sports championship markets with dozens of teams. What is the best way to implement a multi-outcome prediction market? The simplest way is to effectively ignore the fact that there are multiple outcomes, breaking up the market into [...]
The wisdom of the ProbabilitySports crowd
One of the purest and most fascinating examples of the “wisdom of crowds” in action comes courtesy of a unique online contest called ProbabilitySports run by mathematician Brian Galebach. In the contest, each participant states how likely she thinks it is that a team will win a particular sporting event. For example, one contestant may [...]
Evaluating probabilistic predictions
A number of naysayers [Daily Kos, The Register, The Big Picture, Reason] are discrediting prediction markets, latching onto the fact that markets like TradeSports and NewsFutures failed to call this year’s Democratic takeover of the US Senate. Their critiques reflect a clear misunderstanding of the nature of probabilistic predictions, as many others [Emile, Lance] have [...]
Implementing Hanson's Market Maker
Robin Hanson invented a wonderful market maker well suited for use in prediction market applications with a long name: the logarithmic market scoring rule market maker, which I’ll abbreviate as LMSR. (In fact, Hanson invented an entire class of market scoring rule market makers, but the logarithmic variant seems the most useful.) Hanson’s two papers [...]
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Famous for 15 tweets
TV era: $quote = “In the future, everyone will be world-famous for 15 minutes”;
Search era: $quote =~ s/minutes/links/;
Social era: $quote =~ s/links/tweets/;
This month I’ve had five times more traffic than in any other month since I began blogging in Oct 2006, even during woblomo.
Why? I paid Paul Graham a compliment that struck a minor viral nerve, spreading through twitter, facebook, and blogs and sending over six thousand people my way on July 16 alone according to quantcast. Of course most have since dispersed.
Power on the web flows backward through referrals to the sites that people begin their day with, the sources of traffic. Referrals from social media, unpredictable and bursty though they may be, are inexorably on the rise. As they grow, power will shift away from search engines, today’s referral kings. Who knows, this may embolden publishers to take previously unthinkable steps like voluntary delisting, further eroding the value of search. This has all been said before, perhaps best by Mark Cuban starting in 2008. It would be a blow to openness and hurt users, but would spark a fascinating battle.
Another meta note: I installed a new WordPress theme: Suffusion. It’s fantastic: endlessly configurable, bug free, fast, and well designed. I happened upon it by accident when WP 3.0 broke my old theme and I couldn’t be happier. Apparently written by a teenager, I donated to his beer, er, coffee fund.