In this project, we introduce an experimental approach to the design, analysis and implementation of electronic markets based on double auction. A double auction is a market mechanism allowing multiple buyers and sellers to buy and sell goods, commodities and services in a single market. We introduce a formal model of double auction, which specifies market policies such as matching policies, accepting policies, clearing policies, pricing policies and charging policies. Based on this model, we designed and implemented a set of market policies and tested them with different experimental settings. The most important market policies for a double auction market, accepting policies and matching policies, determine the market share and profit in most market situations. For matching policies, we first studied the properties of the equilibrium matching policy, which has been used in many double auction markets. Based on our analysis, we designed and implemented a new matching algorithm, named maximal matching, which can maximize market liquidity, including the number of transactions and buy/sell-volumes. We prove that, given the number of matches, our maximal matching algorithm also maximizes the auctioneer profit. For accepting policies, we formally define a number of typical accepting policies, such as always accepting, quote-beating accepting and equilibrium-beating accepting, and analyze their properties. We then introduce a new accepting policy, named dynamic accepting policy, which is able to filter out extra-marginal shouts by specifying a price range for the maximum ask bound and minimum bid bound. In addition, we briefly discuss clearing policies, pricing policies and charging policies. Beside the formal discussion of market policies, we introduce a set of criteria for an experimental study on market design. By utilizing the Market Design Game platform JCAT for the Trading Agent Competition (TAC), we analyze our market model and identify how specific market policies influence overall market behaviour. Within the JCAT platform, we implemented our formally designed market model with the several market policies and performed a series of experiments, producing a range of experimental results. In particular, we found that matching policies and accepting policies significantly affect overall market performance. We also found that periodic clearing policy can increase the efficiency of the market more than continuous clearing policy. For charging policy, we explore a market share-based dynamic charging policy, and show that it can improve and stabilize market share as well as observably increasing profit share. We conclude that sudden and disproportionate fee charging activities have a long-term effect on trader migration, resulting in a quick loss of market share and market confidence. The results of our experiments provide a better understanding of the dependencies amongst market policies, and show that an experimental approach can greatly improve the efficiency and effectiveness of market design and e-trading study.
Date of Award | 2012 |
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Original language | English |
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- electronic commerce
- intelligent agents (computer software)
- algorithms
- business
- data processing
- auctions
- market design
Experimental studies on market design and e-trading
Khan, M. T. H. (Author). 2012
Western Sydney University thesis: Master's thesis