Research On Competing Pricing Strategies In Double Auctions

The double auction,as a highly efficient market mechanism,has been widely used by on-line marketplaces.In multiple double auctions,there exist multiple marketplaces competing against each other to attract traders.As the development of the Internet Economy,software agents are often used by traders and marketplaces to determine trading strategies and market strategies,it forms a Multi-Agent System.The pricing strategies,determining the transaction prices of traders,is one of the most important strategies which can affect the market's performance.This thesis will analyze how to determine effective pricing strategies in the context of multiple competing marketplaces.Since trading strategies of traders and pricing strategies of marketplaces are affected by each other,we will use game theory to analyze the strategic behavior of marketplaces when determining pricing strategies.Specifically,we focus on the Nash equilibrium pricing strategies.In more details,the main contributions of this thesis are as follows:1)We propose a game theoretical model to describe the issues that we want to address.Specifically,we define the trading strategies for traders and pricing strategies for marketplaces.We mainly consider two categories of pricing strategies: equilibrium k pricing and discriminatory k pricing.We then derive equations to calculate expected utilities for traders and marketplaces,which will be used to derive Nash equilibrium pricing strategies for marketplaces and trading strategies for traders.2)Based on the game theoretical mode,we first analyze how to set pricing strategies in a static way.We study the relationship between pricing strategies and allocative efficiency.Then,we study which pricing strategies will win in the competition.Moreover,we analyze the impact of pricing strategies on trading strategies.We use fictitious play algorithm to derive the Nash Equilibrium of static multiple double auctions before we do the further analysis.We find that when the marketplace adopts discriminatory k pricing rule,the maximal allocative efficiency is reached by setting k =0.41 or 0.59,but when the marketplace adopts equilibrium k pricing rule,the maximal allocative efficiency is reached by setting k =0.5.Moreover,we find that equilibrium k pricing rule provides higher allocative efficiency than discriminatory k pricing rule.Then,we find that the marketplace setting k =0.5 is more likely to attract traders.Moreover,we find that traders will shade their offers and theirs trading strategies are quite different from the cases where when marketplaces adopt different pricing strategies.3)Furthermore,we study how marketplaces setting their pricing strategies to gain more profit when pricing strategies and trading strategies are dynamically affected by each other in competing environments.We propose a co-learning approach based on fictitious play to derive the Nash Equilibrium of dynamic multiple double auctions.We find that marketplaces will provide extreme bias to one side of traders when setting the transaction price(i.e.set k=0 or set k=1).In dynamic competitions,marketplaces using discriminatory k pricing rule are more likely to win,this is different from that in static competitions.Traders decide which marketplaces to enter based on the bias of marketplaces when setting the transaction price.In this thesis,we analyze how to set an effective pricing strategy.We find a number of insights.For example,we discuss which pricing strategies can provide higher allocative efficiency.Then,we analyze which pricing strategies will win in static double auctions and which pricing strategies can gain more profit for marketplaces in dynamic double auctions.Furthermore,we discuss the impacts of pricing strategies on trading strategies.These insights can provide meaningful reference value for designing an effective competing pricing strategy.