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Online Algorithms for Market Clearing

Online Algorithms for Market Clearing. Martin Zinkevich Joint Work with Avrim Blum and Tuomas Sandholm (SODA 2002). Introduction. E-Bay: Single Auction. Buy Bids: people wanting to buy Sell Bids: people wanting to sell. E-Bay: Single Auction. Buy Bids: people wanting to buy

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Online Algorithms for Market Clearing

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  1. Online Algorithms for Market Clearing Martin Zinkevich Joint Work with Avrim Blum and Tuomas Sandholm (SODA 2002)

  2. Introduction

  3. E-Bay: Single Auction Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  4. E-Bay: Single Auction Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  5. E-Bay: Single Auction Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  6. Improvement #1: Double Auction Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  7. Graphical Version Price Profit Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  8. Improvement #2:Bidding For Different Intervals

  9. Jane Toy’s R Us Mark Temporal Bidding Problem Introduction Time Expiration Time Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  10. How to Make Money • Buy the PS2 from one person for some money, and sell it to someone else for more than you bought it. • Keep no inventory, have sellers mail PS2 directly to buyers.

  11. Types of Algorithms • One can imagine two types of algorithms: • Offline: An algorithm which knows the whole sequence before making decisions. • Online: An algorithm which finds the type, price, and expiration time of a bid as it is introduced, and must act on a bid before it expires.

  12. Formalizing the Goal • Find a matching of concurrent buy and sell bids that maximizes profit

  13. The Maximal Matching Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  14. The Offline Problem Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  15. Convert to a Graph Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  16. Convert to a Graph Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  17. Convert to a Weighted Graph 5 Price 1 5 5 2 Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  18. Convert to a Weighted Graph 5 1 5 5 2

  19. Find a Matching of Maximum Weight 5 1 5 5 A matching for a graph is a set of edges which do not share any vertices 2

  20. Find a Matching of Maximum Weight 5 1 5 5 A matching for a graph is a set of edges which do not share any vertices 2

  21. Find a Matching of Maximum Weight 5 1 5 5 2 Algorithms exist to solve this in polynomial time

  22. Find a Matching of Maximum Weight

  23. Find a Matching of Maximum Weight Price Matching of maximal weight maximizes profit! Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  24. What Online Sees… Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  25. What Online Sees… Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  26. What Online Sees… Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  27. What Online Sees… Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  28. What Online Sees… Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  29. What Online Sees… Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  30. What Online Sees… Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  31. What Online Sees… Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  32. What Online Sees… Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  33. What Online Sees… Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  34. What Online Sees… Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  35. What Online Sees… Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  36. What Online Sees… Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  37. What Online Sees… Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  38. What Online Sees… Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  39. Two Online Difficulties Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  40. Getting the Most Matches Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  41. Getting the Most Per Match Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  42. Two Small Problems • Maximizing Liquidity: maximizing the number of matches • The Ice Cream Problem: maximizing profit of one trade

  43. Outline • Introduction • Small Problem #1:Maximizing Liquidity • Small Problem #2:The Ice Cream Problem • Putting it Together • Conclusion • New Results

  44. Maximizing Liquidity

  45. Simplified Matching • Let’s try to maximize the number of trades with positive profit on each trade.

  46. A Maximal Numeric Matching Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  47. Also Maximal Numerically Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  48. Offline: Convert to a Graph No weights needed Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  49. Convert to a Graph No edge here Price Time Buy Bids: people wanting to buy Sell Bids: people wanting to sell

  50. Convert to a Graph

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