WeatherBill let’s you construct an enormous variety of insurance contracts related to weather. For example, the screenshot embedded below shows how I might have insured my vacation at the New Jersey shore:
For $42.62 I could have arranged to be paid $100 per day of rain during my vacation.
(I didn’t actually purchase this mainly because the US government insists that I am a menace to myself and should not be allowed to enter into such a dangerous gamble — more on this later. And as Dan Reeves pointed out to me, it’s probably not rational to do for small sums.)
WeatherBill can also be thought of as a combinatorial prediction market with an automated market maker, a viewpoint I’ll expand on now.
On WeatherBill, you piece together contracts by specifying a series of attributes: date range, place, type of weather, threshold temperature or participation level, minimum and maximum number of bad-weather days, etc. The user interface is extremely well done: a straightforward series of adaptive menu choices and text entry fields guide the customer through the selection process.
This flexibility quickly leads to a combinatorial explosion: given the choices on the site I’m sure the number of possible contracts you can construct runs into the millions.
Once you’ve defined when you want to be paid — according to whatever definition of bad weather makes sense for you or your business — you choose how much you want to be paid.
Finally, given all this information, WeatherBill quotes a price for your custom insurance contract, in effect the maximum amount you will lose if bad weather doesn’t materialize. Quotes are instantaneous — essentially WeatherBill is an automated market maker always willing to trade at some price on any of millions of contracts.
Side note: On WeatherBill, you control the magnitude of your bet by choosing how much you want to be paid. In a typical prediction market, you control magnitude by choosing how many shares to trade. In our own prediction market Yoopick, you control magnitude by choosing the maximum amount you are willing to lose. All three approaches are equivalent, and what’s best depends on context. I would argue that the WeatherBill and Yoopick approaches are simpler to understand, requiring less indirection. The WeatherBill approach seems most natural in an insurance context and the Yoopick approach in a gambling context.
How does the WeatherBill market maker determine prices? I don’t know the details, but their FAQ says that prices change “due to a number of factors, including WeatherBill forecast data, weather simulation, and recent Contract sales”. Certainly historical data plays an important role — in fact, with every price quote WeatherBill tells you what you would have been paid in years past. They allow contracts as few as four days into the future, so I imagine they incorporate current weather forecasts. And the FAQ implies that some form of market feedback occurs, raising prices on contract terms that are in high demand.
Interface is important. WeatherBill shows that a very complicated combinatorial market can be presented in a natural and intuitive way. Though greater expressiveness can mean greater complexity and confusion, Tuomas Sandholm is fond of pointing out that, when done right, expressiveness actually simplifies things by allowing users to speak in terms they are familiar with. WeatherBill — and to an extent Yoopick IMHO — are examples of this somewhat counterintuitive principle at work.
There is another quote from WeatherBill’s FAQ that alludes to an even higher degree of combinatorics coming soon:
Currently you can only price contracts based on one weather measurement. We’re working on making it possible to use more than one measurement, and hope to make it available soon.
If so, I can imagine the number of possible insurance contracts quickly growing into the billions or more with prices hinging on interdependencies among weather events.
Finally, back to the US government treating me like a child. It turns out that only a very limited set of people can buy contracts on WeatherBill, mainly businesses and multi-millionaires who aren’t speculators. In fact, the rules of who can play are a convoluted jumble that I believe are based on regulations from the US Commodity Futures Trading Commission.
Luckily, WeatherBill provides a nice “choose your own adventure” style navigation flow to determine whether you are allowed to participate. Most people will quickly find they are not eligible. (I don’t officially endorse the CYOA standard of re-starting over and over again until you pass.)
Even if red tape locks the average consumer out of direct access, clever companies are stepping in to mediate. In a nice intro piece on WeatherBill, Newsweek mentions that Priceline used WeatherBill to back a “Sunshine Guaranteed” promotion offering refunds to customers whose trips were rained out.
Can you think of other end-arounds to bring WeatherBill functionality to the masses? What other forms of expressive insurance would you like to see?
8 thoughts on “WeatherBill shows the way toward usable combinatorial prediction markets”
That’s a nice piece on the emerging tradable prediction market. I agree with some of your other posts that the US should regulate most forms of betting (with economic purpose) and generate much needed tax revenue at the same time.
You might like to have a look at http://www.cityodds.com. This is a UK based tradable market prediction online service. Real money can be wagered (UK only) for tightly priced one day financial Binary bets and the terms of those bets determined by the user. Trades can be for as little as Â£5 or Â£10.
I’ll keep a close eye on the CFTC and gaming regulators in the US. I’d like to see all individuals who chose to trade or hedge risk to be given access to the capital markets as the professionals.
I play around with the quotes provided by Weatherbill, and it looks like you cannot win betting on weather because the cost of contracts they offer is ridiculously high. Even if I can correctly predict the sign of temperature anomaly, say, two months in advance for a given location, the payoff exceeds the cost of the contract only in about one third of the years, and the total payoff is about equal to the total amount I spent on the contracts. Since it is impossible to correctly predict the sign of the anomaly in 100% cases, I will definitely loose on the long run. There is no sense at all to buy their contracts at the prices they offer.
Mike: Thanks for the link: looks good.
Sergei: Good point, you’re right: I should have mentioned that the WeatherBill market maker, like other insurers, bakes in a significant markup, probably much greater than any pure prediction market or betting exchange could get away with.
I think the emerging prediction exchanges and market makers are the first of a breed and demonstrate what some call the “democratization of capital”. As with all products, pricing tends to be rich at the beginning of the cycle and as more competitors enter then prices tend to the point where demand and supply are satisfied. I think we are some way off that point for weather but you may find financial markets reach that point quicker.
Hedge Street (www.hedgestreet.com), recently bought by IG Index, a UK company now offers regulated fixed-odds bets on financial markets to US residents and regulated by the CFTC. I think this is a portent to some major changes to the way risks are priced. Many of these instruments rely on crowd theory pricing as there is no accurate “formula” for pricing these types of risk.
To determine the fair value of a weather derivative, demand and supply need to be satisfied. I see a huge market developing here as the utility function for weather is particularly personal. Someone getting married outside would place a much higher value on a hedge for a rainy day than a rowing competition organizer.
Lets say three cheers for any new business entering this field and making risk units tradable in small size – yes that does mean my company too (www.cityodds.com) 😉
Here’s a nice article on WeatherBill in Portfolio.com.
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