Structuring the Prediction Markets
Chris F. Masse March 13th, 2007
[...] The drawback to this system is that in order for the market to work, there must be sufficient liquidity. If just a few people are trading, they simply may not come to agreement on a price and thus exchange contracts. Without liquidity, the market will just languish and be unsuccessful.
There are two particularly great benefits to a CDA market, however. One is that prices can make instantaneous jumps. If a presidential candidate makes a huge gaffe, a contract that represents their election chances can dive from 60 to 20 in one trade, something that is difficult to achieve with an algorithm. The second is that traders specify their opinions exactly, by placing bids or asks at specific prices. [...]
Jed Christiansen on MSR and DPMM:
[...] There are drawbacks to [MSR and DPMM], however, and they mirror the advantages of CDA’s. Firstly, it takes them more time and trading to respond to instantaneous price jumps. In thick markets, this largely doesn’t matter. But in thinner markets with less volume (such as many corporate markets), this could certainly become an issue. A second drawback is that to make the algorithm work it may take some financial subsidisation. In a play-money market this really shouldn’t matter, and specifically applies only to the MSR structure, which is currently a bit more common than the DPM structure. Finally, while algorithms deal nicely with contracts that range from 0-100, they can be difficult to use in other ranges because of how the prices are set to move with each share purchase.
The huge advantage to [MSR and DPMM] is that they offer infinite liquidity to traders. This can be a very important factor for new exchanges, particularly as new users want to get up and running immediately. Trading immediately, and seeing the effect of a price change, can be a very valuable tool in order to get prediction markets adopted in an organisation. [...]
Curious on how JC views the Sim Exchange.
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Somehow the phrase “infinite liquidity” came to be associated with the DPM, but this concept is orthogonal to auctions vs. algorithms and is only relevant to real vs. play money markets.
How do I view the SimExchange? Two ways:
First - I think it’s a great example of a new vertical prediction market, like what HSX does for films. There’s a built-in audience that is now learning about prediction markets, which helps everyone. And it meets the needs of that audience by serving as a unique information source for gamers when thinking about their next purchase.
Second - I’m a bit of a purist, but I prefer prediction markets where there is a final, judged outcome. The “lifetime sales of a game” metric just rubs me the wrong way, as there’s no definitive source to judge results (not to mention the no end-date issue). However, in Brian’s implementation he is consistent with what appears to be the best data source available, so he’s made the best of the situation. Plenty more has been said here earlier regarding this issue.
Jason,
I just saw your reply here. I think I understand where you’re coming from, but I’ll describe my thinking here (which assumes a fairly small-scale prediction market as would be commonly found in companies or organisations.)
I’m thinking about this from a user perspective. A new trader wants to trade on a contract, the chance of event X occurring by date Y. A prediction market with an algorithm ensures that they can trade immediately and not have to understand the concept of an order book. This will pay off with more trades and easier adoption for employees that don’t understand or aren’t willing to learn more about standard trading methods.
A prediction market with a CDA structure may or may not have a thick enough order book to allow a user to trade immediately at a price that is acceptable to them, and this could cause confusion if they don’t understand the concept. While there is liquidity through the order book, if there are a relatively small number of traders or orders (again, as you may find in corporate prediction markets) it doesn’t provide the same experience for the user. They think the chance should be higher than what the market says and want to trade, but aren’t willing to pay for the offers in the order book.
Perhaps I was a bit loose in my use of the word liquidity.
Algorithms are certainly more usable. Now, you could imagine a CDA market where the auction isn’t visible to new users and where liquidity is always provided by the house, but in that case either the liquidity will be provided according to an algorithm — or by discretion, in which case the information aggregation may be biased and broken.
Hi Jed Christiansen,
Good explainer. Thanks. I will add it in my list.
Explainers
http://www.chrisfmasse.com/3/3/explainers/
Implementing Hanson’s Market Maker
http://blog.oddhead.com/2006/1.....ket-maker/