1 / 10

The Gjerstad Dickhaut (GD) Auction Strategy

The Gjerstad Dickhaut (GD) Auction Strategy. as presented in the paper: “Price Formation in Double Auctions” by Steven Gjerstad and John Dickhaut Presented by Marek Marcinkiewicz. GD – The main idea. Use previous bids to determine the probability that future bids will be accepted

ion
Download Presentation

The Gjerstad Dickhaut (GD) Auction Strategy

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. The Gjerstad Dickhaut (GD) Auction Strategy as presented in the paper: “Price Formation in Double Auctions” by Steven Gjerstad and John Dickhaut Presented by Marek Marcinkiewicz

  2. GD – The main idea • Use previous bids to determine the probability that future bids will be accepted • Combine this probability with profit to estimate how to place bids to maximize expected profit

  3. History • The algorithm requires previous bids made by all traders • Since the agent has limited memory, a memory length L is specified • L last trades and any shouts between them are stored

  4. Frequency of Takes • If there were many bids made at each price point than the probability could simply be the number of shouts accepted at a particular price point • In a more likely sparse market this is not possible though since there are few bids • But not only bids at some price point provide information to us

  5. What do bids reveal? • TBL – taken bids lower than some price would also be taken at this price • AL – asks lower than some price would match a bid at this price • RBG – rejected bids greater than some price make it less likely that this price will be accepted because if they are rejected then why take this even lower offer?

  6. Probability of bid P(b) = TBL(b) + AL(b) ------------------------------- TBL(b) + AL(b) + RBG(b)

  7. Spread reduction rule • All bids must be higher than the last outstanding bid and all asks must be lower than last outstanding ask • Minimum price is 0 • Maximum price is M (a value that nobody is willing to pay)

  8. Interpolation • Since probability is only defined at shout points that where already made, we have to interpolate these into the real space P(bk) = calculated P(bk) P(bk+1) = calculated P (bk+1) P’(bk) = 0 P’(bk+1) = 0

  9. Interpolated Probability P(b) = α3b3 + α2b2 + α1b1 + α0 Use previous 4 equations to solve for α.

  10. Expected Profit • Bid = max(p(b) * (b – private value)) Use the same type of strategy for asks

More Related