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Choosing Between Order Books and Automated Market Makers for Prediction Markets

Article Quant Q&A · Author: user3587

Summary

The document compares two ways to run a prediction market: a limit order book, where participants post orders that wait for counterparties, and an automated market maker that quotes prices and accepts trades. Order books are described as straightforward to build, but may have wide bid–ask spreads and orders that remain unfilled. An automated market maker offers immediate trading access, while requiring more sophisticated mathematics and potentially incurring bounded losses.

The answer notes that combining the two designs is possible but adds complexity, especially when continuously changing market-maker prices interact with standing orders. It also explains that an automated market maker can let traders buy claims on the opposite outcome instead of relying on borrowed shares for short selling. These are qualitative design tradeoffs rather than a detailed implementation guide. The response does not compare specific performance data, and it expresses uncertainty about the loss properties of alternatives to the cited market maker.

Key ideas

  • A limit order book is simple to implement but may have wide spreads and unfilled orders.
  • An automated market maker can provide immediate trades but requires more mathematical sophistication.
  • An automated market maker may incur losses that are bounded under the described design.
  • Combining a market maker with a limit order book can complicate price and order interactions.
  • Buying claims on the opposite outcome can provide an alternative to short selling in prediction markets.

Tags

Full text
# Which prediction market model is efficient and simple to use?


# Which prediction market model is efficient and simple to use?












For a college project I'm tasked with implementing prediction market. Which model of it I'd better choose?

I want something useful and simple enough for other people to quickly understand and use. (This project is to be used in campus internally).

For now on I'm considering binary option model, but as I understand buying in such model would require me to solve some kind of combinational optimization problem: if I want to buy up to x$ of contracts and there are available contracts with returns r_1, r_2, ... and prices p_1, p_2, ... which looks like a classical knapsack problem to me.

Would it be better to go with some model which uses market-maker?

## Answer by Todd Proebsting (score 5)

https://quant.stackexchange.com/a/5972

There are two excellent choices for implementing prediction markets: (1) Use book orders that stand until filled, just as intrade.com does. (2) Use an automated market maker (like Robin Hanson's) that stands ready to make trades.

The book orders model is very simple to implement, but can suffer from very wide Bid/Ask spreads. And, it can be tough to bet people to book orders that may never get filled.

Hanson's market maker, on the other hand, supports instant trades for anybody. The downside of automated market makers are two-fold: they often require a fair bit of sophisticated math, and they can lose (a bounded amount of) money. See http://blog.oddhead.com/2006/10/30/implementing-hansons-market-maker/

You can use book orders and a market-maker together, but it complicates some things. Hanson's market maker moves the prices continuously which makes things a little funny when you hit the price of a standing book order.

Pennock also has one or two market makers, but Hanson's is the only one that I'm well-versed in. I don't know if Pennock's market makers have fixed loss like Hanson's.

Short selling relies on the notion of borrowing shares, which is outside the scope of most prediction markets. When you have a market maker, you can always purchase the securities that represent the opposite outcome to the one you wanted to short, so there's really no need to short sell---another advantage to having a market maker.

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.